Sample records for quantum chemical predictions

  1. Prediction of contaminant persistence in aqueous phase: a quantum chemical approach.

    PubMed

    Blotevogel, Jens; Mayeno, Arthur N; Sale, Tom C; Borch, Thomas

    2011-03-15

    At contaminated field sites where active remediation measures are not feasible, monitored natural attenuation is sometimes the only alternative for surface water or groundwater decontamination. However, due to slow degradation rates of some contaminants under natural conditions, attenuation processes and their performance assessment can take several years to decades to complete. Here, we apply quantum chemical calculations to predict contaminant persistence in the aqueous phase. For the test compound hexamethylphosphoramide (HMPA), P-N bond hydrolysis is the only thermodynamically favorable reaction that may lead to its degradation under reducing conditions. Through calculation of aqueous Gibbs free energies of activation for all potential reaction mechanisms, it is predicted that HMPA hydrolyzes via an acid-catalyzed mechanism at pH < 8.2, and an uncatalyzed mechanism at pH 8.2-8.5. The estimated half-lives of thousands to hundreds of thousands of years over the groundwater-typical pH range of 6.0 to 8.5 indicate that HMPA will be persistent in the absence of suitable oxidants. At pH 0, where the hydrolysis reaction is rapid enough to enable measurement, the experimentally determined rate constant and half-life are in excellent agreement with the predicted values. Since the quantum chemical methodology described herein can be applied to virtually any contaminant or reaction of interest, it is especially valuable for the prediction of persistence when slow reaction rates impede experimental investigations and appropriate QSARs are unavailable.

  2. Quantum Chemical Prediction of Equilibrium Acidities of Ureas, Deltamides, Squaramides, and Croconamides.

    PubMed

    Ho, Junming; Zwicker, Vincent E; Yuen, Karen K Y; Jolliffe, Katrina A

    2017-10-06

    Robust quantum chemical methods are employed to predict the pK a 's of several families of dual hydrogen-bonding organocatalysts/anion receptors, including deltamides and croconamides as well as their thio derivatives. The average accuracy of these predictions is ∼1 pK a unit and allows for a comparison of the acidity between classes of receptors and for quantitative studies of substituent effects. These computational insights further explain the relationship between pK a and chloride anion affinity of these receptors that will be important for designing future anion receptors and organocatalysts.

  3. Quantum-chemical insights from deep tensor neural networks

    PubMed Central

    Schütt, Kristof T.; Arbabzadah, Farhad; Chmiela, Stefan; Müller, Klaus R.; Tkatchenko, Alexandre

    2017-01-01

    Learning from data has led to paradigm shifts in a multitude of disciplines, including web, text and image search, speech recognition, as well as bioinformatics. Can machine learning enable similar breakthroughs in understanding quantum many-body systems? Here we develop an efficient deep learning approach that enables spatially and chemically resolved insights into quantum-mechanical observables of molecular systems. We unify concepts from many-body Hamiltonians with purpose-designed deep tensor neural networks, which leads to size-extensive and uniformly accurate (1 kcal mol−1) predictions in compositional and configurational chemical space for molecules of intermediate size. As an example of chemical relevance, the model reveals a classification of aromatic rings with respect to their stability. Further applications of our model for predicting atomic energies and local chemical potentials in molecules, reliable isomer energies, and molecules with peculiar electronic structure demonstrate the potential of machine learning for revealing insights into complex quantum-chemical systems. PMID:28067221

  4. Quantum-chemical insights from deep tensor neural networks.

    PubMed

    Schütt, Kristof T; Arbabzadah, Farhad; Chmiela, Stefan; Müller, Klaus R; Tkatchenko, Alexandre

    2017-01-09

    Learning from data has led to paradigm shifts in a multitude of disciplines, including web, text and image search, speech recognition, as well as bioinformatics. Can machine learning enable similar breakthroughs in understanding quantum many-body systems? Here we develop an efficient deep learning approach that enables spatially and chemically resolved insights into quantum-mechanical observables of molecular systems. We unify concepts from many-body Hamiltonians with purpose-designed deep tensor neural networks, which leads to size-extensive and uniformly accurate (1 kcal mol -1 ) predictions in compositional and configurational chemical space for molecules of intermediate size. As an example of chemical relevance, the model reveals a classification of aromatic rings with respect to their stability. Further applications of our model for predicting atomic energies and local chemical potentials in molecules, reliable isomer energies, and molecules with peculiar electronic structure demonstrate the potential of machine learning for revealing insights into complex quantum-chemical systems.

  5. Quantum-chemical insights from deep tensor neural networks

    NASA Astrophysics Data System (ADS)

    Schütt, Kristof T.; Arbabzadah, Farhad; Chmiela, Stefan; Müller, Klaus R.; Tkatchenko, Alexandre

    2017-01-01

    Learning from data has led to paradigm shifts in a multitude of disciplines, including web, text and image search, speech recognition, as well as bioinformatics. Can machine learning enable similar breakthroughs in understanding quantum many-body systems? Here we develop an efficient deep learning approach that enables spatially and chemically resolved insights into quantum-mechanical observables of molecular systems. We unify concepts from many-body Hamiltonians with purpose-designed deep tensor neural networks, which leads to size-extensive and uniformly accurate (1 kcal mol-1) predictions in compositional and configurational chemical space for molecules of intermediate size. As an example of chemical relevance, the model reveals a classification of aromatic rings with respect to their stability. Further applications of our model for predicting atomic energies and local chemical potentials in molecules, reliable isomer energies, and molecules with peculiar electronic structure demonstrate the potential of machine learning for revealing insights into complex quantum-chemical systems.

  6. Rapid prediction of chemical metabolism by human UDP-glucuronosyltransferase isoforms using quantum chemical descriptors derived with the electronegativity equalization method.

    PubMed

    Sorich, Michael J; McKinnon, Ross A; Miners, John O; Winkler, David A; Smith, Paul A

    2004-10-07

    This study aimed to evaluate in silico models based on quantum chemical (QC) descriptors derived using the electronegativity equalization method (EEM) and to assess the use of QC properties to predict chemical metabolism by human UDP-glucuronosyltransferase (UGT) isoforms. Various EEM-derived QC molecular descriptors were calculated for known UGT substrates and nonsubstrates. Classification models were developed using support vector machine and partial least squares discriminant analysis. In general, the most predictive models were generated with the support vector machine. Combining QC and 2D descriptors (from previous work) using a consensus approach resulted in a statistically significant improvement in predictivity (to 84%) over both the QC and 2D models and the other methods of combining the descriptors. EEM-derived QC descriptors were shown to be both highly predictive and computationally efficient. It is likely that EEM-derived QC properties will be generally useful for predicting ADMET and physicochemical properties during drug discovery.

  7. Prediction of Radical Scavenging Activities of Anthocyanins Applying Adaptive Neuro-Fuzzy Inference System (ANFIS) with Quantum Chemical Descriptors

    PubMed Central

    Jhin, Changho; Hwang, Keum Taek

    2014-01-01

    Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS) is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR) models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A) and electronegativity (χ) of flavylium cation, and ionization potential (I) of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively. PMID:25153627

  8. Accurate quantum chemical calculations

    NASA Technical Reports Server (NTRS)

    Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Taylor, Peter R.

    1989-01-01

    An important goal of quantum chemical calculations is to provide an understanding of chemical bonding and molecular electronic structure. A second goal, the prediction of energy differences to chemical accuracy, has been much harder to attain. First, the computational resources required to achieve such accuracy are very large, and second, it is not straightforward to demonstrate that an apparently accurate result, in terms of agreement with experiment, does not result from a cancellation of errors. Recent advances in electronic structure methodology, coupled with the power of vector supercomputers, have made it possible to solve a number of electronic structure problems exactly using the full configuration interaction (FCI) method within a subspace of the complete Hilbert space. These exact results can be used to benchmark approximate techniques that are applicable to a wider range of chemical and physical problems. The methodology of many-electron quantum chemistry is reviewed. Methods are considered in detail for performing FCI calculations. The application of FCI methods to several three-electron problems in molecular physics are discussed. A number of benchmark applications of FCI wave functions are described. Atomic basis sets and the development of improved methods for handling very large basis sets are discussed: these are then applied to a number of chemical and spectroscopic problems; to transition metals; and to problems involving potential energy surfaces. Although the experiences described give considerable grounds for optimism about the general ability to perform accurate calculations, there are several problems that have proved less tractable, at least with current computer resources, and these and possible solutions are discussed.

  9. Quantum indistinguishability in chemical reactions.

    PubMed

    Fisher, Matthew P A; Radzihovsky, Leo

    2018-05-15

    Quantum indistinguishability plays a crucial role in many low-energy physical phenomena, from quantum fluids to molecular spectroscopy. It is, however, typically ignored in most high-temperature processes, particularly for ionic coordinates, implicitly assumed to be distinguishable, incoherent, and thus well approximated classically. We explore enzymatic chemical reactions involving small symmetric molecules and argue that in many situations a full quantum treatment of collective nuclear degrees of freedom is essential. Supported by several physical arguments, we conjecture a "quantum dynamical selection" (QDS) rule for small symmetric molecules that precludes chemical processes that involve direct transitions from orbitally nonsymmetric molecular states. As we propose and discuss, the implications of the QDS rule include ( i ) a differential chemical reactivity of para- and orthohydrogen, ( ii ) a mechanism for inducing intermolecular quantum entanglement of nuclear spins, ( iii ) a mass-independent isotope fractionation mechanism, ( iv ) an explanation of the enhanced chemical activity of "reactive oxygen species", ( v ) illuminating the importance of ortho-water molecules in modulating the quantum dynamics of liquid water, and ( vi ) providing the critical quantum-to-biochemical linkage in the nuclear spin model of the (putative) quantum brain, among others.

  10. Quantum Entanglement and Chemical Reactivity.

    PubMed

    Molina-Espíritu, M; Esquivel, R O; López-Rosa, S; Dehesa, J S

    2015-11-10

    The water molecule and a hydrogenic abstraction reaction are used to explore in detail some quantum entanglement features of chemical interest. We illustrate that the energetic and quantum-information approaches are necessary for a full understanding of both the geometry of the quantum probability density of molecular systems and the evolution of a chemical reaction. The energy and entanglement hypersurfaces and contour maps of these two models show different phenomena. The energy ones reveal the well-known stable geometry of the models, whereas the entanglement ones grasp the chemical capability to transform from one state system to a new one. In the water molecule the chemical reactivity is witnessed through quantum entanglement as a local minimum indicating the bond cleavage in the dissociation process of the molecule. Finally, quantum entanglement is also useful as a chemical reactivity descriptor by detecting the transition state along the intrinsic reaction path in the hypersurface of the hydrogenic abstraction reaction corresponding to a maximally entangled state.

  11. Intrinsic Atomic Orbitals: An Unbiased Bridge between Quantum Theory and Chemical Concepts.

    PubMed

    Knizia, Gerald

    2013-11-12

    Modern quantum chemistry can make quantitative predictions on an immense array of chemical systems. However, the interpretation of those predictions is often complicated by the complex wave function expansions used. Here we show that an exceptionally simple algebraic construction allows for defining atomic core and valence orbitals, polarized by the molecular environment, which can exactly represent self-consistent field wave functions. This construction provides an unbiased and direct connection between quantum chemistry and empirical chemical concepts, and can be used, for example, to calculate the nature of bonding in molecules, in chemical terms, from first principles. In particular, we find consistency with electronegativities (χ), C 1s core-level shifts, resonance substituent parameters (σR), Lewis structures, and oxidation states of transition-metal complexes.

  12. Computational prediction of chemical reactions: current status and outlook.

    PubMed

    Engkvist, Ola; Norrby, Per-Ola; Selmi, Nidhal; Lam, Yu-Hong; Peng, Zhengwei; Sherer, Edward C; Amberg, Willi; Erhard, Thomas; Smyth, Lynette A

    2018-06-01

    Over the past few decades, various computational methods have become increasingly important for discovering and developing novel drugs. Computational prediction of chemical reactions is a key part of an efficient drug discovery process. In this review, we discuss important parts of this field, with a focus on utilizing reaction data to build predictive models, the existing programs for synthesis prediction, and usage of quantum mechanics and molecular mechanics (QM/MM) to explore chemical reactions. We also outline potential future developments with an emphasis on pre-competitive collaboration opportunities. Copyright © 2018 Elsevier Ltd. All rights reserved.

  13. [Application of quantum-chemical methods to prediction of the carcinogenicity of chemical substances].

    PubMed

    Zholdikova, Z I; Kharchevnikova, N V

    2006-01-01

    A version of logical-combinatorial JSM type intelligent system was used to predict the presence and the degree of a carcinogenic effect. This version was based on combined description of chemical substances including both structural and numeric parameters. The new version allows for the fact that the toxicity and danger caused by chemical substances often depend on their biological activation in the organism. The authors substantiate classifying chemicals according to their carcinogenic activity, and illustrate the use of the system to predict the carcinogenicity of polycyclic aromatic hydrocarbons using a model of bioactivation via the formation of diolepoxides, and the carcinogenicity of halogenated alkanes using a model of bioactivation via oxidative dehalogenation. The paper defined the boundary level of an energetic parameter, the exceeding of which correlated with the inhibition of halogenated alkanes's metabolism and the absence of carcinogenic activity.

  14. Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

    PubMed

    Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

    2018-06-13

    An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

  15. Quantum Chemically Estimated Abraham Solute Parameters Using Multiple Solvent-Water Partition Coefficients and Molecular Polarizability.

    PubMed

    Liang, Yuzhen; Xiong, Ruichang; Sandler, Stanley I; Di Toro, Dominic M

    2017-09-05

    Polyparameter Linear Free Energy Relationships (pp-LFERs), also called Linear Solvation Energy Relationships (LSERs), are used to predict many environmentally significant properties of chemicals. A method is presented for computing the necessary chemical parameters, the Abraham parameters (AP), used by many pp-LFERs. It employs quantum chemical calculations and uses only the chemical's molecular structure. The method computes the Abraham E parameter using density functional theory computed molecular polarizability and the Clausius-Mossotti equation relating the index refraction to the molecular polarizability, estimates the Abraham V as the COSMO calculated molecular volume, and computes the remaining AP S, A, and B jointly with a multiple linear regression using sixty-five solvent-water partition coefficients computed using the quantum mechanical COSMO-SAC solvation model. These solute parameters, referred to as Quantum Chemically estimated Abraham Parameters (QCAP), are further adjusted by fitting to experimentally based APs using QCAP parameters as the independent variables so that they are compatible with existing Abraham pp-LFERs. QCAP and adjusted QCAP for 1827 neutral chemicals are included. For 24 solvent-water systems including octanol-water, predicted log solvent-water partition coefficients using adjusted QCAP have the smallest root-mean-square errors (RMSEs, 0.314-0.602) compared to predictions made using APs estimated using the molecular fragment based method ABSOLV (0.45-0.716). For munition and munition-like compounds, adjusted QCAP has much lower RMSE (0.860) than does ABSOLV (4.45) which essentially fails for these compounds.

  16. Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry.

    PubMed

    Rappoport, Dmitrij; Galvin, Cooper J; Zubarev, Dmitry Yu; Aspuru-Guzik, Alán

    2014-03-11

    While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reactive potential energy surfaces and are combined here with quantum chemical structure optimizations, which yield the structures and energies of the reaction intermediates and products. Application of heuristics-aided quantum chemical methodology to the formose reaction reproduces the experimentally observed reaction products, major reaction pathways, and autocatalytic cycles.

  17. Protein structure refinement using a quantum mechanics-based chemical shielding predictor.

    PubMed

    Bratholm, Lars A; Jensen, Jan H

    2017-03-01

    The accurate prediction of protein chemical shifts using a quantum mechanics (QM)-based method has been the subject of intense research for more than 20 years but so far empirical methods for chemical shift prediction have proven more accurate. In this paper we show that a QM-based predictor of a protein backbone and CB chemical shifts (ProCS15, PeerJ , 2016, 3, e1344) is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors. We present a method by which quantum chemistry based predictions of isotropic chemical shielding values (ProCS15) can be used to refine protein structures using Markov Chain Monte Carlo (MCMC) simulations, relating the chemical shielding values to the experimental chemical shifts probabilistically. Two kinds of MCMC structural refinement simulations were performed using force field geometry optimized X-ray structures as starting points: simulated annealing of the starting structure and constant temperature MCMC simulation followed by simulated annealing of a representative ensemble structure. Annealing of the CHARMM structure changes the CA-RMSD by an average of 0.4 Å but lowers the chemical shift RMSD by 1.0 and 0.7 ppm for CA and N. Conformational averaging has a relatively small effect (0.1-0.2 ppm) on the overall agreement with carbon chemical shifts but lowers the error for nitrogen chemical shifts by 0.4 ppm. If an amino acid specific offset is included the ProCS15 predicted chemical shifts have RMSD values relative to experiments that are comparable to popular empirical chemical shift predictors. The annealed representative ensemble structures differ in CA-RMSD relative to the initial structures by an average of 2.0 Å, with >2.0 Å difference for six proteins. In four of the cases, the largest structural differences arise in structurally flexible regions of the protein as determined by NMR, and in the remaining two cases, the large structural

  18. Predicting Hydride Donor Strength via Quantum Chemical Calculations of Hydride Transfer Activation Free Energy.

    PubMed

    Alherz, Abdulaziz; Lim, Chern-Hooi; Hynes, James T; Musgrave, Charles B

    2018-01-25

    We propose a method to approximate the kinetic properties of hydride donor species by relating the nucleophilicity (N) of a hydride to the activation free energy ΔG ⧧ of its corresponding hydride transfer reaction. N is a kinetic parameter related to the hydride transfer rate constant that quantifies a nucleophilic hydridic species' tendency to donate. Our method estimates N using quantum chemical calculations to compute ΔG ⧧ for hydride transfers from hydride donors to CO 2 in solution. A linear correlation for each class of hydrides is then established between experimentally determined N values and the computationally predicted ΔG ⧧ ; this relationship can then be used to predict nucleophilicity for different hydride donors within each class. This approach is employed to determine N for four different classes of hydride donors: two organic (carbon-based and benzimidazole-based) and two inorganic (boron and silicon) hydride classes. We argue that silicon and boron hydrides are driven by the formation of the more stable Si-O or B-O bond. In contrast, the carbon-based hydrides considered herein are driven by the stability acquired upon rearomatization, a feature making these species of particular interest, because they both exhibit catalytic behavior and can be recycled.

  19. Quantum chemical studies of estrogenic compounds

    USDA-ARS?s Scientific Manuscript database

    Quantum chemical methods are potent tools to provide information on the chemical structure and electronic properties of organic molecules. Modern computational chemistry methods have provided a great deal of insight into the binding of estrogenic compounds to estrogenic receptors (ER), an important ...

  20. Predicting allergic contact dermatitis: a hierarchical structure activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors

    NASA Astrophysics Data System (ADS)

    Basak, Subhash C.; Mills, Denise; Hawkins, Douglas M.

    2008-06-01

    A hierarchical classification study was carried out based on a set of 70 chemicals—35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.

  1. Use of statistical and neural net approaches in predicting toxicity of chemicals.

    PubMed

    Basak, S C; Grunwald, G D; Gute, B D; Balasubramanian, K; Opitz, D

    2000-01-01

    Hierarchical quantitative structure-activity relationships (H-QSAR) have been developed as a new approach in constructing models for estimating physicochemical, biomedicinal, and toxicological properties of interest. This approach uses increasingly more complex molecular descriptors in a graduated approach to model building. In this study, statistical and neural network methods have been applied to the development of H-QSAR models for estimating the acute aquatic toxicity (LC50) of 69 benzene derivatives to Pimephales promelas (fathead minnow). Topostructural, topochemical, geometrical, and quantum chemical indices were used as the four levels of the hierarchical method. It is clear from both the statistical and neural network models that topostructural indices alone cannot adequately model this set of congeneric chemicals. Not surprisingly, topochemical indices greatly increase the predictive power of both statistical and neural network models. Quantum chemical indices also add significantly to the modeling of this set of acute aquatic toxicity data.

  2. Quantum-chemical Calculations in the Study of Antitumour Compounds

    NASA Astrophysics Data System (ADS)

    Luzhkov, V. B.; Bogdanov, G. N.

    1986-01-01

    The results of quantum-chemical calculations on antitumour preparations concerning the mechanism of their action at the electronic and molecular levels and structure-activity correlations are discussed in this review. Preparations whose action involves alkylating and free-radial mechanisms, complex-forming agents, and antimetabolites are considered. Modern quantum-chemical methods for calculations on biologically active substances are described. The bibliography includes 106 references.

  3. Predicting carcinogenicity of diverse chemicals using probabilistic neural network modeling approaches

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com; Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow 226 001; Gupta, Shikha

    Robust global models capable of discriminating positive and non-positive carcinogens; and predicting carcinogenic potency of chemicals in rodents were developed. The dataset of 834 structurally diverse chemicals extracted from Carcinogenic Potency Database (CPDB) was used which contained 466 positive and 368 non-positive carcinogens. Twelve non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals and nonlinearity in the data were evaluated using Tanimoto similarity index and Brock–Dechert–Scheinkman statistics. Probabilistic neural network (PNN) and generalized regression neural network (GRNN) models were constructed for classification and function optimization problems using the carcinogenicity end point in rat. Validation of the models wasmore » performed using the internal and external procedures employing a wide series of statistical checks. PNN constructed using five descriptors rendered classification accuracy of 92.09% in complete rat data. The PNN model rendered classification accuracies of 91.77%, 80.70% and 92.08% in mouse, hamster and pesticide data, respectively. The GRNN constructed with nine descriptors yielded correlation coefficient of 0.896 between the measured and predicted carcinogenic potency with mean squared error (MSE) of 0.44 in complete rat data. The rat carcinogenicity model (GRNN) applied to the mouse and hamster data yielded correlation coefficient and MSE of 0.758, 0.71 and 0.760, 0.46, respectively. The results suggest for wide applicability of the inter-species models in predicting carcinogenic potency of chemicals. Both the PNN and GRNN (inter-species) models constructed here can be useful tools in predicting the carcinogenicity of new chemicals for regulatory purposes. - Graphical abstract: Figure (a) shows classification accuracies (positive and non-positive carcinogens) in rat, mouse, hamster, and pesticide data yielded by optimal PNN model. Figure (b) shows generalization and

  4. Lattice of quantum predictions

    NASA Astrophysics Data System (ADS)

    Drieschner, Michael

    1993-10-01

    What is the structure of reality? Physics is supposed to answer this question, but a purely empiristic view is not sufficient to explain its ability to do so. Quantum mechanics has forced us to think more deeply about what a physical theory is. There are preconditions every physical theory must fulfill. It has to contain, e.g., rules for empirically testable predictions. Those preconditions give physics a structure that is “a priori” in the Kantian sense. An example is given how the lattice structure of quantum mechanics can be understood along these lines.

  5. Radiation and quantum chemical studies of chalcone derivatives.

    PubMed

    Gaikwad, P; Priyadarsini, K I; Naumov, S; Rao, B S M

    2010-08-05

    The reactions of oxidizing radicals ((*)OH, Br(2)(*-), and SO(4)(*-)) with -OH-, -CH(3)-, or -NH(2)-substituted indole chalcones and hydroxy benzenoid chalcones were studied by radiation and quantum chemical methods. The (*)OH radical was found to react by addition at diffusion-controlled rates (k = 1.1-1.7 x 10(10) dm(3) mol(-1) s(-1)), but Br(2)(*-) radical reacted by 2 orders of magnitude lower. Quantum chemical calculations at the B3LYP/6-31+G(d,p) level of theory have shown that the (C2-OH)(*), (C11-OH)(*), and (C10-OH)(*) adducts of the indole chalcones and the (C7-OH)(*) and (C8-OH)(*) adducts of the hydroxy benzenoid chalcones are more stable with DeltaH = -39 to -28 kcal mol(-1) and DeltaG = -32 to -19 kcal mol(-1). This suggests that (*)OH addition to the alpha,beta-unsaturated bond is a major reaction channel in both types of chalcones and is barrierless. The stability and lack of dehydration of the (*)OH adducts arise from two factors: strong frontier orbital interaction due to the low energy gap between interacting orbitals and the negligible Coulombic repulsion due to small absolute values of Mulliken charges. The transient absorption spectrum measured in the (*)OH radical reaction with all the indole chalcone derivatives exhibited a maximum at 390 nm, which is in excellent agreement with the computed value (394 nm). The formation of three phenolic products under steady-state radiolysis is in line with the three stable (*)OH adducts predicted by theory. Independent of the substituent, identical spectra (lambda(max) = 330-360 and approximately 580 nm) were obtained on one-electron oxidation of the three indole chalcones. MO calculations predict the deprotonation from the -NH group is more efficient than from the substituent due to the larger electron density on the N1 atom forming the chalcone indolyl radical. Its reduction potential was determined to be 0.56 V from the ABTS(*-)/ABTS(2-) couple. In benzenoid chalcones, the (*)OH adduct spectrum is

  6. QSTR of the toxicity of some organophosphorus compounds by using the quantum chemical and topological descriptors.

    PubMed

    Senior, Samir A; Madbouly, Magdy D; El massry, Abdel-Moneim

    2011-09-01

    Quantum chemical and topological descriptors of some organophosphorus compounds (OP) were correlated with their toxicity LD(50) as a dermal. The quantum chemical parameters were obtained using B3LYP/LANL2DZdp-ECP optimization. Using linear regression analysis, equations were derived to calculate the theoretical LD(50) of the studied compounds. The inclusion of quantum parameters, having both charge indices and topological indices, affects the toxicity of the studied compounds resulting in high correlation coefficient factors for the obtained equations. Two of the new four firstly supposed descriptors give higher correlation coefficients namely the Heteroatom Corrected Extended Connectivity Randic index ((1)X(HCEC)) and the Density Randic index ((1)X(Den)). The obtained linear equations were applied to predict the toxicity of some related structures. It was found that the sulfur atoms in these compounds must be replaced by oxygen atoms to achieve improved toxicity. Copyright © 2011 Elsevier Ltd. All rights reserved.

  7. Double quantum coherence ESR spectroscopy and quantum chemical calculations on a BDPA biradical.

    PubMed

    Haeri, Haleh Hashemi; Spindler, Philipp; Plackmeyer, Jörn; Prisner, Thomas

    2016-10-26

    Carbon-centered radicals are interesting alternatives to otherwise commonly used nitroxide spin labels for dipolar spectroscopy techniques because of their narrow ESR linewidth. Herein, we present a novel BDPA biradical, where two BDPA (α,α,γ,γ-bisdiphenylene-β-phenylallyl) radicals are covalently tethered by a saturated biphenyl acetylene linker. The inter-spin distance between the two spin carrier fragments was measured using double quantum coherence (DQC) ESR methodology. The DQC experiment revealed a mean distance of only 1.8 nm between the two unpaired electron spins. This distance is shorter than the predictions based on a simple modelling of the biradical geometry with the electron spins located at the central carbon atoms. Therefore, DFT (density functional theory) calculations were performed to obtain a picture of the spin delocalization, which may give rise to a modified dipolar interaction tensor, and to find those conformations that correspond best to the experimentally observed inter-spin distance. Quantum chemical calculations showed that the attachment of the biphenyl acetylene linker at the second position of the fluorenyl ring of BDPA did not affect the spin population or geometry of the BDPA radical. Therefore, spin delocalization and geometry optimization of each BDPA moiety could be performed on the monomeric unit alone. The allylic dihedral angle θ 1 between the fluorenyl rings in the monomer subunit was determined to be 30° or 150° using quantum chemical calculations. The proton hyperfine coupling constant calculated from both energy minima was in very good agreement with literature values. Based on the optimal monomer geometries and spin density distributions, the dipolar coupling interaction between both BDPA units could be calculated for several dimer geometries. It was shown that the rotation of the BDPA units around the linker axis (θ 2 ) does not significantly influence the dipolar coupling strength when compared to the allylic

  8. Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) using Complex Quantum Neuron (CQN): Applications to time series prediction.

    PubMed

    Cui, Yiqian; Shi, Junyou; Wang, Zili

    2015-11-01

    Quantum Neural Networks (QNN) models have attracted great attention since it innovates a new neural computing manner based on quantum entanglement. However, the existing QNN models are mainly based on the real quantum operations, and the potential of quantum entanglement is not fully exploited. In this paper, we proposes a novel quantum neuron model called Complex Quantum Neuron (CQN) that realizes a deep quantum entanglement. Also, a novel hybrid networks model Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) is proposed based on Complex Quantum Neuron (CQN). CRQDNN is a three layer model with both CQN and classical neurons. An infinite impulse response (IIR) filter is embedded in the Networks model to enable the memory function to process time series inputs. The Levenberg-Marquardt (LM) algorithm is used for fast parameter learning. The networks model is developed to conduct time series predictions. Two application studies are done in this paper, including the chaotic time series prediction and electronic remaining useful life (RUL) prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Quantum Chemical Studies of Actinides and Lanthanides: From Small Molecules to Nanoclusters

    NASA Astrophysics Data System (ADS)

    Vlaisavljevich, Bess

    Research into actinides is of high interest because of their potential applications as an energy source and for the environmental implications therein. Global concern has arisen since the development of the actinide concept in the 1940s led to the industrial scale use of the commercial nuclear energy cycle and nuclear weapons production. Large quantities of waste have been generated from these processes inspiring efforts to address fundamental questions in actinide science. In this regard, the objective of this work is to use theory to provide insight and predictions into actinide chemistry, where experimental work is extremely challenging because of the intrinsic difficulties of the experiments themselves and the safety issues associated with this type of chemistry. This thesis is a collection of theoretical studies of actinide chemistry falling into three categories: quantum chemical and matrix isolation studies of small molecules, the electronic structure of organoactinide systems, and uranyl peroxide nanoclusters and other solid state actinide compounds. The work herein not only spans a wide range of systems size but also investigates a range of chemical problems. Various quantum chemical approaches have been employed. Wave function-based methods have been used to study the electronic structure of actinide containing molecules of small to middle-size. Among these methods, the complete active space self consistent field (CASSCF) approach with corrections from second-order perturbation theory (CASPT2), the generalized active space SCF (GASSCF) approach, and Moller-Plesset second-order perturbation theory (MP2) have been employed. Likewise, density functional theory (DFT) has been used along with analysis tools like bond energy decomposition, bond orders, and Bader's Atoms in Molecules. From these quantum chemical results, comparison with experimentally obtained structures and spectra are made.

  10. Spectroscopic, quantum chemical calculation and molecular docking of dipfluzine

    NASA Astrophysics Data System (ADS)

    Srivastava, Karnica; Srivastava, Anubha; Tandon, Poonam; Sinha, Kirti; Wang, Jing

    2016-12-01

    Molecular structure and vibrational analysis of dipfluzine (C27H29FN2O) were presented using FT-IR and FT-Raman spectroscopy and quantum chemical calculations. The theoretical ground state geometry and electronic structure of dipfluzine are optimized by the DFT/B3LYP/6-311++G (d,p) method and compared with those of the crystal data. The 1D potential energy scan was performed by varying the dihedral angle using B3LYP functional at 6-31G(d,p) level of theory and thus the most stable conformer of the compound were determined. Molecular electrostatic potential surface (MEPS), frontier orbital analysis and electronic reactivity descriptor were used to predict the chemical reactivity of molecule. Energies of intra- and inter-molecular hydrogen bonds in molecule and their electronic aspects were investigated by natural bond orbital (NBO). To find out the anti-apoptotic activity of the title compound molecular docking studies have been performed against protein Fas.

  11. Polynomial-time quantum algorithm for the simulation of chemical dynamics

    PubMed Central

    Kassal, Ivan; Jordan, Stephen P.; Love, Peter J.; Mohseni, Masoud; Aspuru-Guzik, Alán

    2008-01-01

    The computational cost of exact methods for quantum simulation using classical computers grows exponentially with system size. As a consequence, these techniques can be applied only to small systems. By contrast, we demonstrate that quantum computers could exactly simulate chemical reactions in polynomial time. Our algorithm uses the split-operator approach and explicitly simulates all electron-nuclear and interelectronic interactions in quadratic time. Surprisingly, this treatment is not only more accurate than the Born–Oppenheimer approximation but faster and more efficient as well, for all reactions with more than about four atoms. This is the case even though the entire electronic wave function is propagated on a grid with appropriately short time steps. Although the preparation and measurement of arbitrary states on a quantum computer is inefficient, here we demonstrate how to prepare states of chemical interest efficiently. We also show how to efficiently obtain chemically relevant observables, such as state-to-state transition probabilities and thermal reaction rates. Quantum computers using these techniques could outperform current classical computers with 100 qubits. PMID:19033207

  12. Prediction and Repetition in Quantum Mechanics: The EPR Experiment and Quantum Probability

    NASA Astrophysics Data System (ADS)

    Plotnitsky, Arkady

    2007-02-01

    The article considers the implications of the experiment of A. Einstein, B. Podolsky, and N. Rosen (EPR), and of the exchange (concerning this experiment) between EPR and Bohr concerning the incompleteness, or else nonlocality, of quantum mechanics for our understanding of quantum phenomena and quantum probability. The article specifically argues that in the case of quantum phenomena, including those involved in the experiments of the EPR type, the probabilistic considerations are important even when the predictions concerned can be made with certainty, due to the impossibility, in general, to repeat any given quantum experiment with the same outcome. The article argue that this fact, not properly considered or taken into account by EPR, makes it difficult and ultimately impossible to sustain their argument, which it is consistent with Bohr's counterargument to EPR and with his view of quantum phenomena and quantum mechanics.

  13. Exploiting Locality in Quantum Computation for Quantum Chemistry.

    PubMed

    McClean, Jarrod R; Babbush, Ryan; Love, Peter J; Aspuru-Guzik, Alán

    2014-12-18

    Accurate prediction of chemical and material properties from first-principles quantum chemistry is a challenging task on traditional computers. Recent developments in quantum computation offer a route toward highly accurate solutions with polynomial cost; however, this solution still carries a large overhead. In this Perspective, we aim to bring together known results about the locality of physical interactions from quantum chemistry with ideas from quantum computation. We show that the utilization of spatial locality combined with the Bravyi-Kitaev transformation offers an improvement in the scaling of known quantum algorithms for quantum chemistry and provides numerical examples to help illustrate this point. We combine these developments to improve the outlook for the future of quantum chemistry on quantum computers.

  14. Intramolecular hydrogen bonding in myricetin and myricitrin. Quantum chemical calculations and vibrational spectroscopy

    NASA Astrophysics Data System (ADS)

    Vojta, Danijela; Dominković, Katarina; Miljanić, Snežana; Spanget-Larsen, Jens

    2017-03-01

    The molecular structures of myricetin (3,3‧,4‧,5,5‧,7-hexahydroxyflavone; MCE) and myricitrin (myricetin 3-O-rhamnoside; MCI) are investigated by quantum chemical calculations (B3LYP/6-311G**). Two preferred molecular rotamers of MCI are predicted, corresponding to different conformations of the O-rhamnoside subunit. The rotamers are characterized by different hydrogen bonded cross-links between the hydroxy groups of the rhamnoside substituent and the parent MCE moiety. The predicted OH stretching frequencies are compared with vibrational spectra of MCE and MCI recorded for the sake of this investigation (IR and Raman). In addition, a reassignment of the Cdbnd O stretching bands is suggested.

  15. Quantitative structure-activation barrier relationship modeling for Diels-Alder ligations utilizing quantum chemical structural descriptors.

    PubMed

    Nandi, Sisir; Monesi, Alessandro; Drgan, Viktor; Merzel, Franci; Novič, Marjana

    2013-10-30

    In the present study, we show the correlation of quantum chemical structural descriptors with the activation barriers of the Diels-Alder ligations. A set of 72 non-catalysed Diels-Alder reactions were subjected to quantitative structure-activation barrier relationship (QSABR) under the framework of theoretical quantum chemical descriptors calculated solely from the structures of diene and dienophile reactants. Experimental activation barrier data were obtained from literature. Descriptors were computed using Hartree-Fock theory using 6-31G(d) basis set as implemented in Gaussian 09 software. Variable selection and model development were carried out by stepwise multiple linear regression methodology. Predictive performance of the quantitative structure-activation barrier relationship (QSABR) model was assessed by training and test set concept and by calculating leave-one-out cross-validated Q2 and predictive R2 values. The QSABR model can explain and predict 86.5% and 80% of the variances, respectively, in the activation energy barrier training data. Alternatively, a neural network model based on back propagation of errors was developed to assess the nonlinearity of the sought correlations between theoretical descriptors and experimental reaction barriers. A reasonable predictability for the activation barrier of the test set reactions was obtained, which enabled an exploration and interpretation of the significant variables responsible for Diels-Alder interaction between dienes and dienophiles. Thus, studies in the direction of QSABR modelling that provide efficient and fast prediction of activation barriers of the Diels-Alder reactions turn out to be a meaningful alternative to transition state theory based computation.

  16. Electron-beam generated porous dextran gels: experimental and quantum chemical studies.

    PubMed

    Naumov, Sergej; Knolle, Wolfgang; Becher, Jana; Schnabelrauch, Matthias; Reichelt, Senta

    2014-06-01

    The aim of this work was to investigate the reaction mechanism of electron-beam generated macroporous dextran cryogels by quantum chemical calculation and electron paramagnetic resonance measurements. Electron-beam radiation was used to initiate the cross-linking reaction of methacrylated dextran in semifrozen aqueous solutions. The pore morphology of the resulting cryogels was visualized by scanning electron microscopy. Quantum chemical calculations and electron paramagnetic resonance studies provided information on the most probable reaction pathway and the chain growth radicals. The most probable reaction pathway was a ring opening reaction and the addition of a C-atom to the double-bond of the methacrylated dextran molecule. First detailed quantum chemical calculation on the reaction mechanism of electron-beam initiated cross-linking reaction of methacrylated dextran are presented.

  17. Protein Structure Validation and Refinement Using Amide Proton Chemical Shifts Derived from Quantum Mechanics

    PubMed Central

    Christensen, Anders S.; Linnet, Troels E.; Borg, Mikael; Boomsma, Wouter; Lindorff-Larsen, Kresten; Hamelryck, Thomas; Jensen, Jan H.

    2013-01-01

    We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts - sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level QM results obtained for a small protein with an RMSD of 0.25 ppm (r = 0.94). ProCS is interfaced with the PHAISTOS protein simulation program and is used to infer statistical protein ensembles that reflect experimentally measured amide proton chemical shift values. Such chemical shift-based structural refinements, starting from high-resolution X-ray structures of Protein G, ubiquitin, and SMN Tudor Domain, result in average chemical shifts, hydrogen bond geometries, and trans-hydrogen bond (h3 JNC') spin-spin coupling constants that are in excellent agreement with experiment. We show that the structural sensitivity of the QM-based amide proton chemical shift predictions is needed to obtain this agreement. The ProCS method thus offers a powerful new tool for refining the structures of hydrogen bonding networks to high accuracy with many potential applications such as protein flexibility in ligand binding. PMID:24391900

  18. Quantum chemical investigation of levofloxacin-boron complexes: A computational approach

    NASA Astrophysics Data System (ADS)

    Sayin, Koray; Karakaş, Duran

    2018-04-01

    Quantum chemical calculations are performed over some boron complexes with levofloxacin. Boron complex with fluorine atoms are optimized at three different methods (HF, B3LYP and M062X) with 6-31 + G(d) basis set. The best level is determined as M062X/6-31 + G(d) by comparison of experimental and calculated results of complex (1). The other complexes are optimized by using the best level. Structural properties, IR and NMR spectrum are examined in detail. Biological activities of mentioned complexes are investigated by some quantum chemical descriptors and molecular docking analyses. As a result, biological activities of complex (2) and (4) are close to each other and higher than those of other complexes. Additionally, NLO properties of mentioned complexes are investigated by some quantum chemical parameters. It is found that complex (3) is the best candidate for NLO applications.

  19. Ab initio Quantum Chemical and Experimental Reaction Kinetics Studies in the Combustion of Bipropellants

    DTIC Science & Technology

    2017-03-24

    NUMBER (Include area code) 24 March 2017 Briefing Charts 01 March 2017 - 31 March 2017 Ab initio Quantum Chemical and Experimental Reaction Kinetics...Laboratory AFRL/RQRS 1 Ara Road Edwards AFB, CA 93524 *Email: ghanshyam.vaghjiani@us.af.mil Ab initio Quantum Chemical and Experimental Reaction ...Clearance 17161 Zador et al., Prog. Energ. Combust. Sci., 37 371 (2011) Why Quantum Chemical Reaction Kinetics Studies? DISTRIBUTION A: Approved for

  20. Quantum chemical approach to estimating the thermodynamics of metabolic reactions.

    PubMed

    Jinich, Adrian; Rappoport, Dmitrij; Dunn, Ian; Sanchez-Lengeling, Benjamin; Olivares-Amaya, Roberto; Noor, Elad; Even, Arren Bar; Aspuru-Guzik, Alán

    2014-11-12

    Thermodynamics plays an increasingly important role in modeling and engineering metabolism. We present the first nonempirical computational method for estimating standard Gibbs reaction energies of metabolic reactions based on quantum chemistry, which can help fill in the gaps in the existing thermodynamic data. When applied to a test set of reactions from core metabolism, the quantum chemical approach is comparable in accuracy to group contribution methods for isomerization and group transfer reactions and for reactions not including multiply charged anions. The errors in standard Gibbs reaction energy estimates are correlated with the charges of the participating molecules. The quantum chemical approach is amenable to systematic improvements and holds potential for providing thermodynamic data for all of metabolism.

  1. Quantum Chemical Approach to Estimating the Thermodynamics of Metabolic Reactions

    PubMed Central

    Jinich, Adrian; Rappoport, Dmitrij; Dunn, Ian; Sanchez-Lengeling, Benjamin; Olivares-Amaya, Roberto; Noor, Elad; Even, Arren Bar; Aspuru-Guzik, Alán

    2014-01-01

    Thermodynamics plays an increasingly important role in modeling and engineering metabolism. We present the first nonempirical computational method for estimating standard Gibbs reaction energies of metabolic reactions based on quantum chemistry, which can help fill in the gaps in the existing thermodynamic data. When applied to a test set of reactions from core metabolism, the quantum chemical approach is comparable in accuracy to group contribution methods for isomerization and group transfer reactions and for reactions not including multiply charged anions. The errors in standard Gibbs reaction energy estimates are correlated with the charges of the participating molecules. The quantum chemical approach is amenable to systematic improvements and holds potential for providing thermodynamic data for all of metabolism. PMID:25387603

  2. Quantum chemical study of the inhibition of the corrosion of mild steel in H2SO4 by some antibiotics.

    PubMed

    Eddy, Nnabuk O; Ibok, Udo J; Ebenso, Eno E; El Nemr, Ahmed; El Ashry, El Sayed H

    2009-09-01

    The inhibition efficiency of some antibiotics against mild steel corrosion was studied using weight loss and quantum chemical techniques. Values of inhibition efficiency obtained from weight loss measurements correlated strongly with theoretical values obtained through semi empirical calculations. High correlation coefficients were also obtained between inhibition efficiency of the antibiotics and some quantum chemical parameters, including frontier orbital (E (HOMO) and E (LUMO)), dipole moment, log P, TNC and LSER parameters (critical volume and dipolar-polarisability factor), which indicated that these parameters affect the inhibition efficiency of the compounds. It was also found that quantitative structure activity relation can be used to adequately predict the inhibition effectiveness of these compounds.

  3. Chemical application of diffusion quantum Monte Carlo

    NASA Technical Reports Server (NTRS)

    Reynolds, P. J.; Lester, W. A., Jr.

    1984-01-01

    The diffusion quantum Monte Carlo (QMC) method gives a stochastic solution to the Schroedinger equation. This approach is receiving increasing attention in chemical applications as a result of its high accuracy. However, reducing statistical uncertainty remains a priority because chemical effects are often obtained as small differences of large numbers. As an example, the single-triplet splitting of the energy of the methylene molecule CH sub 2 is given. The QMC algorithm was implemented on the CYBER 205, first as a direct transcription of the algorithm running on the VAX 11/780, and second by explicitly writing vector code for all loops longer than a crossover length C. The speed of the codes relative to one another as a function of C, and relative to the VAX, are discussed. The computational time dependence obtained versus the number of basis functions is discussed and this is compared with that obtained from traditional quantum chemistry codes and that obtained from traditional computer architectures.

  4. New generation of docking programs: Supercomputer validation of force fields and quantum-chemical methods for docking.

    PubMed

    Sulimov, Alexey V; Kutov, Danil C; Katkova, Ekaterina V; Ilin, Ivan S; Sulimov, Vladimir B

    2017-11-01

    Discovery of new inhibitors of the protein associated with a given disease is the initial and most important stage of the whole process of the rational development of new pharmaceutical substances. New inhibitors block the active site of the target protein and the disease is cured. Computer-aided molecular modeling can considerably increase effectiveness of new inhibitors development. Reliable predictions of the target protein inhibition by a small molecule, ligand, is defined by the accuracy of docking programs. Such programs position a ligand in the target protein and estimate the protein-ligand binding energy. Positioning accuracy of modern docking programs is satisfactory. However, the accuracy of binding energy calculations is too low to predict good inhibitors. For effective application of docking programs to new inhibitors development the accuracy of binding energy calculations should be higher than 1kcal/mol. Reasons of limited accuracy of modern docking programs are discussed. One of the most important aspects limiting this accuracy is imperfection of protein-ligand energy calculations. Results of supercomputer validation of several force fields and quantum-chemical methods for docking are presented. The validation was performed by quasi-docking as follows. First, the low energy minima spectra of 16 protein-ligand complexes were found by exhaustive minima search in the MMFF94 force field. Second, energies of the lowest 8192 minima are recalculated with CHARMM force field and PM6-D3H4X and PM7 quantum-chemical methods for each complex. The analysis of minima energies reveals the docking positioning accuracies of the PM7 and PM6-D3H4X quantum-chemical methods and the CHARMM force field are close to one another and they are better than the positioning accuracy of the MMFF94 force field. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Chemical accuracy from quantum Monte Carlo for the benzene dimer.

    PubMed

    Azadi, Sam; Cohen, R E

    2015-09-14

    We report an accurate study of interactions between benzene molecules using variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) methods. We compare these results with density functional theory using different van der Waals functionals. In our quantum Monte Carlo (QMC) calculations, we use accurate correlated trial wave functions including three-body Jastrow factors and backflow transformations. We consider two benzene molecules in the parallel displaced geometry, and find that by highly optimizing the wave function and introducing more dynamical correlation into the wave function, we compute the weak chemical binding energy between aromatic rings accurately. We find optimal VMC and DMC binding energies of -2.3(4) and -2.7(3) kcal/mol, respectively. The best estimate of the coupled-cluster theory through perturbative triplets/complete basis set limit is -2.65(2) kcal/mol [Miliordos et al., J. Phys. Chem. A 118, 7568 (2014)]. Our results indicate that QMC methods give chemical accuracy for weakly bound van der Waals molecular interactions, comparable to results from the best quantum chemistry methods.

  6. Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction.

    PubMed

    Sadowski, Peter; Fooshee, David; Subrahmanya, Niranjan; Baldi, Pierre

    2016-11-28

    Machine learning (ML) and quantum mechanical (QM) methods can be used in two-way synergy to build chemical reaction expert systems. The proposed ML approach identifies electron sources and sinks among reactants and then ranks all source-sink pairs. This addresses a bottleneck of QM calculations by providing a prioritized list of mechanistic reaction steps. QM modeling can then be used to compute the transition states and activation energies of the top-ranked reactions, providing additional or improved examples of ranked source-sink pairs. Retraining the ML model closes the loop, producing more accurate predictions from a larger training set. The approach is demonstrated in detail using a small set of organic radical reactions.

  7. Systematic chemical-genetic and chemical-chemical interaction datasets for prediction of compound synergism

    PubMed Central

    Wildenhain, Jan; Spitzer, Michaela; Dolma, Sonam; Jarvik, Nick; White, Rachel; Roy, Marcia; Griffiths, Emma; Bellows, David S.; Wright, Gerard D.; Tyers, Mike

    2016-01-01

    The network structure of biological systems suggests that effective therapeutic intervention may require combinations of agents that act synergistically. However, a dearth of systematic chemical combination datasets have limited the development of predictive algorithms for chemical synergism. Here, we report two large datasets of linked chemical-genetic and chemical-chemical interactions in the budding yeast Saccharomyces cerevisiae. We screened 5,518 unique compounds against 242 diverse yeast gene deletion strains to generate an extended chemical-genetic matrix (CGM) of 492,126 chemical-gene interaction measurements. This CGM dataset contained 1,434 genotype-specific inhibitors, termed cryptagens. We selected 128 structurally diverse cryptagens and tested all pairwise combinations to generate a benchmark dataset of 8,128 pairwise chemical-chemical interaction tests for synergy prediction, termed the cryptagen matrix (CM). An accompanying database resource called ChemGRID was developed to enable analysis, visualisation and downloads of all data. The CGM and CM datasets will facilitate the benchmarking of computational approaches for synergy prediction, as well as chemical structure-activity relationship models for anti-fungal drug discovery. PMID:27874849

  8. Low temperature regulated growth of PbS quantum dots by wet chemical method

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kumar, Hitanshu, E-mail: hitanshuminhas@gmail.com; Barman, P. B.; Singh, Ragini Raj

    2015-08-28

    Narrow size distribution with regulated synthesis of lead sulfide (PbS) quantum dots (QDs) was achieved through wet chemical method. Different concentrations of 2-mercaptoethanol (capping agent) were used for tailoring the QDs size. Transmission electron microscopy and X-ray diffraction studies revealed that the QDs have mean diameters between 6 to 15 nm. The optical absorption spectra were compared to the predictions of a theoretical model for the electronic structure. The theory agrees well with experiment for QDs larger than 7 nm, but for smaller dots there is some deviation from the theoretical predictions. Consequently, the produced particles are having monodispersity, good water solubility,more » stability and may be good arguments to be biologically compatible due to the use of 2-mercaptoethanol.« less

  9. Predictions of the quantum landscape multiverse

    NASA Astrophysics Data System (ADS)

    Mersini-Houghton, Laura

    2017-02-01

    The 2015 Planck data release has placed tight constraints on the class of inflationary models allowed. The current best fit region favors concave downwards inflationary potentials, since they produce a suppressed tensor to scalar index ratio r. Concave downward potentials have a negative curvature {{V}\\prime \\prime} , therefore a tachyonic mass square that drives fluctuations. Furthermore, their use can become problematic if the field rolls in a part of the potential away from the extrema, since the semiclassical approximation of quantum cosmology, used for deriving the most probable wavefunction of the universe from the landscape and for addressing the quantum to classical transition, breaks down away from the steepest descent region. We here propose a way of dealing with such potentials by inverting the metric signature and solving for the wavefunction of the universe in the Euclidean sector. This method allows us to extend our theory of the origin of the universe from a quantum multiverse, to a more general class of concave inflationary potentials where a straightforward application of the semiclassical approximation fails. The work here completes the derivation of modifications to the Newtonian potential and to the inflationary potential, which originate from the quantum entanglement of our universe with all others in the quantum landscape multiverse, leading to predictions of observational signatures for both types of inflationary models, concave and convex potentials.

  10. Chemical Shifts of the Carbohydrate Binding Domain of Galectin-3 from Magic Angle Spinning NMR and Hybrid Quantum Mechanics/Molecular Mechanics Calculations.

    PubMed

    Kraus, Jodi; Gupta, Rupal; Yehl, Jenna; Lu, Manman; Case, David A; Gronenborn, Angela M; Akke, Mikael; Polenova, Tatyana

    2018-03-22

    Magic angle spinning NMR spectroscopy is uniquely suited to probe the structure and dynamics of insoluble proteins and protein assemblies at atomic resolution, with NMR chemical shifts containing rich information about biomolecular structure. Access to this information, however, is problematic, since accurate quantum mechanical calculation of chemical shifts in proteins remains challenging, particularly for 15 N H . Here we report on isotropic chemical shift predictions for the carbohydrate recognition domain of microcrystalline galectin-3, obtained from using hybrid quantum mechanics/molecular mechanics (QM/MM) calculations, implemented using an automated fragmentation approach, and using very high resolution (0.86 Å lactose-bound and 1.25 Å apo form) X-ray crystal structures. The resolution of the X-ray crystal structure used as an input into the AF-NMR program did not affect the accuracy of the chemical shift calculations to any significant extent. Excellent agreement between experimental and computed shifts is obtained for 13 C α , while larger scatter is observed for 15 N H chemical shifts, which are influenced to a greater extent by electrostatic interactions, hydrogen bonding, and solvation.

  11. Benchmarking quantum mechanical calculations with experimental NMR chemical shifts of 2-HADNT

    NASA Astrophysics Data System (ADS)

    Liu, Yuemin; Junk, Thomas; Liu, Yucheng; Tzeng, Nianfeng; Perkins, Richard

    2015-04-01

    In this study, both GIAO-DFT and GIAO-MP2 calculations of nuclear magnetic resonance (NMR) spectra were benchmarked with experimental chemical shifts. The experimental chemical shifts were determined experimentally for carbon-13 (C-13) of seven carbon atoms for the TNT degradation product 2-hydroxylamino-4,6-dinitrotoluene (2-HADNT). Quantum mechanics GIAO calculations were implemented using Becke-3-Lee-Yang-Parr (B3LYP) and other six hybrid DFT methods (Becke-1-Lee-Yang-Parr (B1LYP), Becke-half-and-half-Lee-Yang-Parr (BH and HLYP), Cohen-Handy-3-Lee-Yang-Parr (O3LYP), Coulomb-attenuating-B3LYP (CAM-B3LYP), modified-Perdew-Wang-91-Lee-Yang-Parr (mPW1LYP), and Xu-3-Lee-Yang-Parr (X3LYP)) which use the same correlation functional LYP. Calculation results showed that the GIAO-MP2 method gives the most accurate chemical shift values, and O3LYP method provides the best prediction of chemical shifts among the B3LYP and other five DFT methods. Three types of atomic partial charges, Mulliken (MK), electrostatic potential (ESP), and natural bond orbital (NBO), were also calculated using MP2/aug-cc-pVDZ method. A reasonable correlation was discovered between NBO partial charges and experimental chemical shifts of carbon-13 (C-13).

  12. An efficient matrix product operator representation of the quantum chemical Hamiltonian

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Keller, Sebastian, E-mail: sebastian.keller@phys.chem.ethz.ch; Reiher, Markus, E-mail: markus.reiher@phys.chem.ethz.ch; Dolfi, Michele, E-mail: dolfim@phys.ethz.ch

    We describe how to efficiently construct the quantum chemical Hamiltonian operator in matrix product form. We present its implementation as a density matrix renormalization group (DMRG) algorithm for quantum chemical applications. Existing implementations of DMRG for quantum chemistry are based on the traditional formulation of the method, which was developed from the point of view of Hilbert space decimation and attained higher performance compared to straightforward implementations of matrix product based DMRG. The latter variationally optimizes a class of ansatz states known as matrix product states, where operators are correspondingly represented as matrix product operators (MPOs). The MPO construction schememore » presented here eliminates the previous performance disadvantages while retaining the additional flexibility provided by a matrix product approach, for example, the specification of expectation values becomes an input parameter. In this way, MPOs for different symmetries — abelian and non-abelian — and different relativistic and non-relativistic models may be solved by an otherwise unmodified program.« less

  13. Cation solvation with quantum chemical effects modeled by a size-consistent multi-partitioning quantum mechanics/molecular mechanics method.

    PubMed

    Watanabe, Hiroshi C; Kubillus, Maximilian; Kubař, Tomáš; Stach, Robert; Mizaikoff, Boris; Ishikita, Hiroshi

    2017-07-21

    In the condensed phase, quantum chemical properties such as many-body effects and intermolecular charge fluctuations are critical determinants of the solvation structure and dynamics. Thus, a quantum mechanical (QM) molecular description is required for both solute and solvent to incorporate these properties. However, it is challenging to conduct molecular dynamics (MD) simulations for condensed systems of sufficient scale when adapting QM potentials. To overcome this problem, we recently developed the size-consistent multi-partitioning (SCMP) quantum mechanics/molecular mechanics (QM/MM) method and realized stable and accurate MD simulations, using the QM potential to a benchmark system. In the present study, as the first application of the SCMP method, we have investigated the structures and dynamics of Na + , K + , and Ca 2+ solutions based on nanosecond-scale sampling, a sampling 100-times longer than that of conventional QM-based samplings. Furthermore, we have evaluated two dynamic properties, the diffusion coefficient and difference spectra, with high statistical certainty. Furthermore the calculation of these properties has not previously been possible within the conventional QM/MM framework. Based on our analysis, we have quantitatively evaluated the quantum chemical solvation effects, which show distinct differences between the cations.

  14. A quantum informational approach for dissecting chemical reactions

    NASA Astrophysics Data System (ADS)

    Duperrouzel, Corinne; Tecmer, Paweł; Boguslawski, Katharina; Barcza, Gergely; Legeza, Örs; Ayers, Paul W.

    2015-02-01

    We present a conceptionally different approach to dissect bond-formation processes in metal-driven catalysis using concepts from quantum information theory. Our method uses the entanglement and correlation among molecular orbitals to analyze changes in electronic structure that accompany chemical processes. As a proof-of-principle example, the evolution of nickel-ethene bond-formation is dissected, which allows us to monitor the interplay of back-bonding and π-donation along the reaction coordinate. Furthermore, the reaction pathway of nickel-ethene complexation is analyzed using quantum chemistry methods, revealing the presence of a transition state. Our study supports the crucial role of metal-to-ligand back-donation in the bond-forming process of nickel-ethene.

  15. The Alexandria library, a quantum-chemical database of molecular properties for force field development.

    PubMed

    Ghahremanpour, Mohammad M; van Maaren, Paul J; van der Spoel, David

    2018-04-10

    Data quality as well as library size are crucial issues for force field development. In order to predict molecular properties in a large chemical space, the foundation to build force fields on needs to encompass a large variety of chemical compounds. The tabulated molecular physicochemical properties also need to be accurate. Due to the limited transparency in data used for development of existing force fields it is hard to establish data quality and reusability is low. This paper presents the Alexandria library as an open and freely accessible database of optimized molecular geometries, frequencies, electrostatic moments up to the hexadecupole, electrostatic potential, polarizabilities, and thermochemistry, obtained from quantum chemistry calculations for 2704 compounds. Values are tabulated and where available compared to experimental data. This library can assist systematic development and training of empirical force fields for a broad range of molecules.

  16. The Alexandria library, a quantum-chemical database of molecular properties for force field development

    NASA Astrophysics Data System (ADS)

    Ghahremanpour, Mohammad M.; van Maaren, Paul J.; van der Spoel, David

    2018-04-01

    Data quality as well as library size are crucial issues for force field development. In order to predict molecular properties in a large chemical space, the foundation to build force fields on needs to encompass a large variety of chemical compounds. The tabulated molecular physicochemical properties also need to be accurate. Due to the limited transparency in data used for development of existing force fields it is hard to establish data quality and reusability is low. This paper presents the Alexandria library as an open and freely accessible database of optimized molecular geometries, frequencies, electrostatic moments up to the hexadecupole, electrostatic potential, polarizabilities, and thermochemistry, obtained from quantum chemistry calculations for 2704 compounds. Values are tabulated and where available compared to experimental data. This library can assist systematic development and training of empirical force fields for a broad range of molecules.

  17. Quantum chemical parameters in QSAR: what do I use when?

    USGS Publications Warehouse

    Hickey, James P.; Ostrander, Gary K.

    1996-01-01

    This chapter provides a brief overview of the numerous quantum chemical parameters that have been/are currently being used in quantitative structure activity relationships (QSAR), along with a representative bibliography. The parameters will be grouped according to their mechanistic interpretations, and representative biological and physical chemical applications will be mentioned. Parmater computation methods and the appropriate software are highlighted, as are sources for software.

  18. No extension of quantum theory can have improved predictive power.

    PubMed

    Colbeck, Roger; Renner, Renato

    2011-08-02

    According to quantum theory, measurements generate random outcomes, in stark contrast with classical mechanics. This raises the question of whether there could exist an extension of the theory that removes this indeterminism, as suspected by Einstein, Podolsky and Rosen. Although this has been shown to be impossible, existing results do not imply that the current theory is maximally informative. Here we ask the more general question of whether any improved predictions can be achieved by any extension of quantum theory. Under the assumption that measurements can be chosen freely, we answer this question in the negative: no extension of quantum theory can give more information about the outcomes of future measurements than quantum theory itself. Our result has significance for the foundations of quantum mechanics, as well as applications to tasks that exploit the inherent randomness in quantum theory, such as quantum cryptography.

  19. No extension of quantum theory can have improved predictive power

    PubMed Central

    Colbeck, Roger; Renner, Renato

    2011-01-01

    According to quantum theory, measurements generate random outcomes, in stark contrast with classical mechanics. This raises the question of whether there could exist an extension of the theory that removes this indeterminism, as suspected by Einstein, Podolsky and Rosen. Although this has been shown to be impossible, existing results do not imply that the current theory is maximally informative. Here we ask the more general question of whether any improved predictions can be achieved by any extension of quantum theory. Under the assumption that measurements can be chosen freely, we answer this question in the negative: no extension of quantum theory can give more information about the outcomes of future measurements than quantum theory itself. Our result has significance for the foundations of quantum mechanics, as well as applications to tasks that exploit the inherent randomness in quantum theory, such as quantum cryptography. PMID:21811240

  20. On the nonlocal predictions of quantum optics

    NASA Technical Reports Server (NTRS)

    Marshall, Trevor W.; Santos, Emilio; Vidiella-Barranco, Antonio

    1994-01-01

    We give a definition of locality in quantum optics based upon Bell's work, and show that locality has been violated in no experiment performed up to now. We argue that the interpretation of the Wigner function as a probability density gives a very attractive local realistic picture of quantum optics provided that this function is nonnegative. We conjecture that this is the case for all states which can be realized in the laboratory. In particular, we believe that the usual representation of 'single photon states' by a Fock state of the Hilbert space is not correct and that a more physical, although less simple mathematically, representation involves density matrices. We study in some detail the experiment showing anticorrelation after a beam splitter and prove that it naturally involves a positive Wigner function. Our (quantum) predictions for this experiment disagree with the ones reported in the literature.

  1. QSPR models for various physical properties of carbohydrates based on molecular mechanics and quantum chemical calculations.

    PubMed

    Dyekjaer, Jane Dannow; Jónsdóttir, Svava Osk

    2004-01-22

    Quantitative Structure-Property Relationships (QSPR) have been developed for a series of monosaccharides, including the physical properties of partial molar heat capacity, heat of solution, melting point, heat of fusion, glass-transition temperature, and solid state density. The models were based on molecular descriptors obtained from molecular mechanics and quantum chemical calculations, combined with other types of descriptors. Saccharides exhibit a large degree of conformational flexibility, therefore a methodology for selecting the energetically most favorable conformers has been developed, and was used for the development of the QSPR models. In most cases good correlations were obtained for monosaccharides. For five of the properties predictions were made for disaccharides, and the predicted values for the partial molar heat capacities were in excellent agreement with experimental values.

  2. Predictability sieve, pointer states, and the classicality of quantum trajectories

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dalvit, D. A. R.; Zurek, W. H.; Dziarmaga, J.

    2005-12-15

    We study various measures of classicality of the states of open quantum systems subject to decoherence. Classical states are expected to be stable in spite of decoherence, and are thought to leave conspicuous imprints on the environment. Here these expected features of environment-induced superselection are quantified using four different criteria: predictability sieve (which selects states that produce least entropy), purification time (which looks for states that are the easiest to find out from the imprint they leave on the environment), efficiency threshold (which finds states that can be deduced from measurements on a smallest fraction of the environment), and puritymore » loss time (that looks for states for which it takes the longest to lose a set fraction of their initial purity). We show that when pointer states--the most predictable states of an open quantum system selected by the predictability sieve--are well defined, all four criteria agree that they are indeed the most classical states. We illustrate this with two examples: an underdamped harmonic oscillator, for which coherent states are unanimously chosen by all criteria, and a free particle undergoing quantum Brownian motion, for which most criteria select almost identical Gaussian states (although, in this case, the predictability sieve does not select well defined pointer states)« less

  3. Chemical reaction CO+OH • → CO 2+H • autocatalyzed by carbon dioxide: Quantum chemical study of the potential energy surfaces

    DOE PAGES

    Masunov, Artem E.; Wait, Elizabeth; Vasu, Subith S.

    2016-06-28

    The supercritical carbon dioxide medium, used to increase efficiency in oxy combustion fossil energy technology, may drastically alter both rates and mechanisms of chemical reactions. Here we investigate potential energy surface of the second most important combustion reaction with quantum chemistry methods. Two types of effects are reported: formation of the covalent intermediates and formation of van der Waals complexes by spectator CO 2 molecule. While spectator molecule alter the activation barrier only slightly, the covalent bonding opens a new reaction pathway. The mechanism includes sequential covalent binding of CO 2 to OH radical and CO molecule, hydrogen transfer frommore » oxygen to carbon atoms, and CH bond dissociation. This reduces the activation barrier by 11 kcal/mol at the rate-determining step and is expected to accelerate the reaction rate. The finding of predicted catalytic effect is expected to play an important role not only in combustion but also in a broad array of chemical processes taking place in supercritical CO 2 medium. Furthermore, tt may open a new venue for controlling reaction rates for chemical manufacturing.« less

  4. Quantum Degeneracy in Atomic Point Contacts Revealed by Chemical Force and Conductance

    NASA Astrophysics Data System (ADS)

    Sugimoto, Yoshiaki; Ondráček, Martin; Abe, Masayuki; Pou, Pablo; Morita, Seizo; Perez, Ruben; Flores, Fernando; Jelínek, Pavel

    2013-09-01

    Quantum degeneracy is an important concept in quantum mechanics with large implications to many processes in condensed matter. Here, we show the consequences of electron energy level degeneracy on the conductance and the chemical force between two bodies at the atomic scale. We propose a novel way in which a scanning probe microscope can detect the presence of degenerate states in atomic-sized contacts even at room temperature. The tunneling conductance G and chemical binding force F between two bodies both tend to decay exponentially with distance in a certain distance range, usually maintaining direct proportionality G∝F. However, we show that a square relation G∝F2 arises as a consequence of quantum degeneracy between the interacting frontier states of the scanning tip and a surface atom. We demonstrate this phenomenon on the Si(111)-(7×7) surface reconstruction where the Si adatom possesses a strongly localized dangling-bond state at the Fermi level.

  5. PREDICTING CHEMICAL RESIDUES IN AQUATIC FOOD CHAINS

    EPA Science Inventory

    The need to accurately predict chemical accumulation in aquatic organisms is critical for a variety of environmental applications including the assessment of contaminated sediments. Approaches for predicting chemical residues can be divided into two general classes, empirical an...

  6. Quantum chemical study of methane oxidation species

    NASA Technical Reports Server (NTRS)

    Jackels, Charles F.

    1993-01-01

    The research funded by this project has focused on quantum chemical investigations of molecular species thought to be important in the chemistry of the earth's upper and lower atmospheres. The body of this report contains brief discussions of the results of the several phases of this investigation. In many instances these results have been presented at scientific meetings and/or published in refereed journals. Those bibliographic references are given. In addition to the study of specific chemical systems, there were several phases during the course of this investigation where much of the effort went into the development and modification of computer codes necessary to carry out these calculations on the wide range of computer equipment used during this study. This type of code maintenance and development work did not generally result in publications and presentations, but a brief review is given.

  7. Chemically Triggered Formation of Two-Dimensional Epitaxial Quantum Dot Superlattices.

    PubMed

    Walravens, Willem; De Roo, Jonathan; Drijvers, Emile; Ten Brinck, Stephanie; Solano, Eduardo; Dendooven, Jolien; Detavernier, Christophe; Infante, Ivan; Hens, Zeger

    2016-07-26

    Two dimensional superlattices of epitaxially connected quantum dots enable size-quantization effects to be combined with high charge carrier mobilities, an essential prerequisite for highly performing QD devices based on charge transport. Here, we demonstrate that surface active additives known to restore nanocrystal stoichiometry can trigger the formation of epitaxial superlattices of PbSe and PbS quantum dots. More specifically, we show that both chalcogen-adding (sodium sulfide) and lead oleate displacing (amines) additives induce small area epitaxial superlattices of PbSe quantum dots. In the latter case, the amine basicity is a sensitive handle to tune the superlattice symmetry, with strong and weak bases yielding pseudohexagonal or quasi-square lattices, respectively. Through density functional theory calculations and in situ titrations monitored by nuclear magnetic resonance spectroscopy, we link this observation to the concomitantly different coordination enthalpy and ligand displacement potency of the amine. Next to that, an initial ∼10% reduction of the initial ligand density prior to monolayer formation and addition of a mild, lead oleate displacing chemical trigger such as aniline proved key to induce square superlattices with long-range, square micrometer order; an effect that is the more pronounced the larger the quantum dots. Because the approach applies to PbS quantum dots as well, we conclude that it offers a reproducible and rational method for the formation of highly ordered epitaxial quantum dot superlattices.

  8. Quantum Monte Carlo tunneling from quantum chemistry to quantum annealing

    NASA Astrophysics Data System (ADS)

    Mazzola, Guglielmo; Smelyanskiy, Vadim N.; Troyer, Matthias

    2017-10-01

    Quantum tunneling is ubiquitous across different fields, from quantum chemical reactions and magnetic materials to quantum simulators and quantum computers. While simulating the real-time quantum dynamics of tunneling is infeasible for high-dimensional systems, quantum tunneling also shows up in quantum Monte Carlo (QMC) simulations, which aim to simulate quantum statistics with resources growing only polynomially with the system size. Here we extend the recent results obtained for quantum spin models [Phys. Rev. Lett. 117, 180402 (2016), 10.1103/PhysRevLett.117.180402], and we study continuous-variable models for proton transfer reactions. We demonstrate that QMC simulations efficiently recover the scaling of ground-state tunneling rates due to the existence of an instanton path, which always connects the reactant state with the product. We discuss the implications of our results in the context of quantum chemical reactions and quantum annealing, where quantum tunneling is expected to be a valuable resource for solving combinatorial optimization problems.

  9. Standoff detection of explosives and chemical agents using broadly tuned external-cavity quantum cascade lasers (EC-QCLs)

    NASA Astrophysics Data System (ADS)

    Takeuchi, Eric B.; Rayner, Timothy; Weida, Miles; Crivello, Salvatore; Day, Timothy

    2007-10-01

    Civilian soft targets such as transportation systems are being targeted by terrorists using IEDs and suicide bombers. Having the capability to remotely detect explosives, precursors and other chemicals would enable these assets to be protected with minimal interruption of the flow of commerce. Mid-IR laser technology offers the potential to detect explosives and other chemicals in real-time and from a safe standoff distance. While many of these agents possess "fingerprint" signatures in the mid-IR (i.e. in the 3-20 micron regime), their effective interrogation by a practical, field-deployable system has been limited by size, complexity, reliability and cost constraints of the base laser technology. Daylight Solutions has addressed these shortcomings by developing compact, portable, broadly tunable mid-IR laser sources based upon external-cavity quantum cascade technology. This technology is now being applied by Daylight in system level architectures for standoff and remote detection of explosives, precursors and chemical agents. Several of these architectures and predicted levels of performance will be presented.

  10. Predictions of Chemical Species via Diode Laser Spectroscopy

    NASA Technical Reports Server (NTRS)

    Chen, Shin-Juh; Silver, Joel A.; Dahm, Werner J. A.; Piltch, Nancy D.; Salzman, Jack (Technical Monitor)

    2001-01-01

    A technique to predict temperature and chemical species in flames from absorbance measurement of one chemical species is presented. Predicted temperature and mole fractions of methane and water agreed well with measured and published results.

  11. Molecular structure and conformations of para-methylbenzene sulfonamide and ortho-methylbenzene sulfonamide: gas electron diffraction and quantum chemical calculations study.

    PubMed

    Petrov, Vjacheslav M; Girichev, Georgiy V; Oberhammer, Heinz; Petrova, Valentina N; Giricheva, Nina I; Bardina, Anna V; Ivanov, Sergey N

    2008-04-03

    The molecular structure and conformational properties of para-methylbenzene sulfonamide (4-MBSA) and ortho-methylbenzene sulfonamide (2-MBSA) have been studied by gas electron diffraction (GED) and quantum chemical methods (B3LYP/6-311+G** and MP2/6-31G**). Quantum chemical calculations predict the existence of two conformers for 4-MBSA with the S-N bond perpendicular to the benzene plane and the NH2 group either eclipsing or staggering the S-O bonds of the SO2 group. Both conformers possess CS symmetry. The eclipsed form is predicted to be favored by DeltaE = 0.63 kcal/mol (B3LYP) or 1.00 kcal/mol (MP2). According to the calculations, the S-N bond in 2-MBSA can possess planar direction opposite the methyl group (phi(C2C1SN) = 180 degrees ) or nonplanar direction (phi(C2C1SN) approximately 60 degrees ). In both cases, the NH2 group can adopt eclipsed or staggered orientation, resulting in a total of four stable conformers. The nonplanar eclipsed conformer (C1 symmetry) and the planar eclipsed form (CS symmetry) are predicted to be favored. According to the GED analysis, the saturated vapor over solid 4-MBSA at T = 151(3) degrees C consists as mixture of the eclipsed (78(19) %) and staggered (22(19) %) forms. The saturated vapor over solid 2-MBSA at T = 157(3) degrees C consists as a mixture of the nonplanar eclipsed (69(11) %) and planar eclipsed (31(11) %) forms.

  12. Proton chemical shift tensors determined by 3D ultrafast MAS double-quantum NMR spectroscopy

    NASA Astrophysics Data System (ADS)

    Zhang, Rongchun; Mroue, Kamal H.; Ramamoorthy, Ayyalusamy

    2015-10-01

    Proton NMR spectroscopy in the solid state has recently attracted much attention owing to the significant enhancement in spectral resolution afforded by the remarkable advances in ultrafast magic angle spinning (MAS) capabilities. In particular, proton chemical shift anisotropy (CSA) has become an important tool for obtaining specific insights into inter/intra-molecular hydrogen bonding. However, even at the highest currently feasible spinning frequencies (110-120 kHz), 1H MAS NMR spectra of rigid solids still suffer from poor resolution and severe peak overlap caused by the strong 1H-1H homonuclear dipolar couplings and narrow 1H chemical shift (CS) ranges, which render it difficult to determine the CSA of specific proton sites in the standard CSA/single-quantum (SQ) chemical shift correlation experiment. Herein, we propose a three-dimensional (3D) 1H double-quantum (DQ) chemical shift/CSA/SQ chemical shift correlation experiment to extract the CS tensors of proton sites whose signals are not well resolved along the single-quantum chemical shift dimension. As extracted from the 3D spectrum, the F1/F3 (DQ/SQ) projection provides valuable information about 1H-1H proximities, which might also reveal the hydrogen-bonding connectivities. In addition, the F2/F3 (CSA/SQ) correlation spectrum, which is similar to the regular 2D CSA/SQ correlation experiment, yields chemical shift anisotropic line shapes at different isotropic chemical shifts. More importantly, since the F2/F1 (CSA/DQ) spectrum correlates the CSA with the DQ signal induced by two neighboring proton sites, the CSA spectrum sliced at a specific DQ chemical shift position contains the CSA information of two neighboring spins indicated by the DQ chemical shift. If these two spins have different CS tensors, both tensors can be extracted by numerical fitting. We believe that this robust and elegant single-channel proton-based 3D experiment provides useful atomistic-level structural and dynamical information for

  13. Cluster Quantum Chemical Study of the Grignard Reagent Formation

    NASA Astrophysics Data System (ADS)

    Tulub, A. V.; Porsev, V. V.

    The main stages of the Grignard reagent formation are described in a framework of quantum chemical cluster model. We have established two kinds of the adsorption of CH3Hal on Mgn clusters, one of which leads to radical formation and the second is responsible for radical free dissociate adsorption. The charge redistribution in cluster CH3MgnHal result to the strong electrostatic interaction with ether and Grignard reagent formation without any activation barrier.

  14. Lighting up micromotors with quantum dots for smart chemical sensing.

    PubMed

    Jurado-Sánchez, B; Escarpa, A; Wang, J

    2015-09-25

    A new "on-the-fly" chemical optical detection strategy based on the incorporation of fluorescence CdTe quantum dots (QDs) on the surface of self-propelled tubular micromotors is presented. The motion-accelerated binding of trace Hg to the QDs selectively quenches the fluorescence emission and leads to an effective discrimination between different mercury species and other co-existing ions.

  15. Predicted phototoxicities of carbon nano-material by quantum mechanical calculations.

    PubMed

    Betowski, Don

    2017-08-01

    The purpose of this research was to develop a predictive model for the phototoxicity potential of carbon nanomaterials (fullerenols and single-walled carbon nanotubes). This model is based on the quantum mechanical (ab initio) calculations on these carbon-based materials and comparison of the triplet excited states of these materials to published work relating phototoxicity of polynuclear aromatic hydrocarbons (PAH) to their predictive triplet excited state energy. A successful outcome will add another tool to the arsenal of predictive methods for the U.S. EPA program offices as they assess the toxicity of compounds in use or coming into commerce. The basis of this research was obtaining the best quantum mechanical structure of the carbon nanomaterial and was fundamental in determining the triplet excited state energy. The triplet excited state, in turn, is associated with the phototoxicity of the material. This project relies heavily on the interaction of the predictive results (physical chemistry) and the experimental results obtained by biologists and toxicologists. The results of the experiments (toxicity testing) will help refine the predictive model, while the predictions will alert the scientists to red flag compounds. It is hoped that a guidance document for the U.S. EPA will be forthcoming to help determine the toxicity of compounds. This can be a screening tool that would rely on further testing for those compounds found by these predictions to be a phototoxic danger to health and the environment. Copyright © 2017. Published by Elsevier Inc.

  16. Quantum chemical modeling of enzymatic reactions: the case of 4-oxalocrotonate tautomerase.

    PubMed

    Sevastik, Robin; Himo, Fahmi

    2007-12-01

    The reaction mechanism of 4-oxalocrotonate tautomerase (4-OT) is studied using the density functional theory method B3LYP. This enzyme catalyzes the isomerisation of unconjugated alpha-keto acids to their conjugated isomers. Two different quantum chemical models of the active site are devised and the potential energy curves for the reaction are computed. The calculations support the proposed reaction mechanism in which Pro-1 acts as a base to shuttle a proton from the C3 to the C5 position of the substrate. The first step (proton transfer from C3 to proline) is shown to be the rate-limiting step. The energy of the charge-separated intermediate (protonated proline-deprotonated substrate) is calculated to be quite low, in accordance with measured pKa values. The results of the two models are used to evaluate the methodology employed in modeling enzyme active sites using quantum chemical cluster models.

  17. Effect analysis of quantum chemical descriptors and substituent characteristics on Henry's law constants of polybrominated diphenyl ethers at different temperatures.

    PubMed

    Long, Jiang; Youli, Qiu; Yu, Li

    2017-11-01

    Twelve substituent descriptors, 17 quantum chemical descriptors and 1/T were selected to establish a quantitative structure-property relationship (QSPR) model of Henry's law constants for 7 polybrominated diphenyl ethers (PBDEs) at five different temperatures. Then, the lgH of 202 congeners at different temperatures were predicted. The variation rule and regulating mechanism of lgH was studied from the perspectives of both quantum chemical descriptors and substituent characteristics. The R 2 for modeling and testing sets of the final QSPR model are 0.977 and 0.979, respectively, thus indicating good fitness and predictive ability for Henry' law constants of PBDEs at different temperatures. The favorable hydrogen binding sites are the 5,5',6,6'-positions for high substituent congeners and the O atom of the ether bond for low substituent congeners, which affects the interaction between PBDEs and water molecules. lgH is negatively and linearly correlated with 1/T, and the variation trends of lgH with temperature are primarily regulated by individual substituent characteristics, wherein: the more substituents involved, the smaller the lgH. The significant sequence for the main effect of substituent positions is para>meta>ortho, where the ortho-positions are mainly involved in second-order interaction effect (64.01%). Having two substituents in the same ring also provides a significant effect, with 81.36% of second-order interaction effects, particularly where there is an adjacent distribution (55.02%). Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Spectroscopic and chemical reactivity analysis of D-Myo-Inositol using quantum chemical approach and its experimental verification

    NASA Astrophysics Data System (ADS)

    Mishra, Devendra P.; Srivastava, Anchal; Shukla, R. K.

    2017-07-01

    This paper describes the spectroscopic (^1H and ^{13}C NMR, FT-IR and UV-Visible), chemical, nonlinear optical and thermodynamic properties of D-Myo-Inositol using quantum chemical technique and its experimental verification. The structural parameters of the compound are determined from the optimized geometry by B3LYP method with 6 {-}311{+}{+}G(d,p) basis set. It was found that the optimized parameters thus obtained are almost in agreement with the experimental ones. A detailed interpretation of the infrared spectra of D-Myo-Inositol is also reported in the present work. After optimization, the proton and carbon NMR chemical shifts of the studied compound are calculated using GIAO and 6 {-}311{+}{+}G(d,p) basis set. The search of organic materials with improved charge transfer properties requires precise quantum chemical calculations of space-charge density distribution, state and transition dipole moments and HOMO-LUMO states. The nature of the transitions in the observed UV-Visible spectrum of the compound has been studied by the time-dependent density functional theory (TD-DFT). The global reactivity descriptors like chemical potential, electronegativity, hardness, softness and electrophilicity index, have been calculated using DFT. The thermodynamic calculation related to the title compound was also performed at B3LYP/ 6 {-}311{+}{+}G(d,p) level of theory. The standard statistical thermodynamic functions like heat capacity at constant pressure, entropy and enthalpy change were obtained from the theoretical harmonic frequencies of the optimized molecule. It is observed that the values of heat capacity, entropy and enthalpy increase with increase in temperature from 100 to 1000 K, which is attributed to the enhancement of molecular vibration with the increase in temperature.

  19. Development and evaluation of predictive model for bovine serum albumin-water partition coefficients of neutral organic chemicals.

    PubMed

    Ma, Guangcai; Yuan, Quan; Yu, Haiying; Lin, Hongjun; Chen, Jianrong; Hong, Huachang

    2017-04-01

    The binding of organic chemicals to serum albumin can significantly reduce their unbound concentration in blood and affect their biological reactions. In this study, we developed a new QSAR model for bovine serum albumin (BSA) - water partition coefficients (K BSA/W ) of neutral organic chemicals with large structural variance, logK BSA/W values covering 3.5 orders of magnitude (1.19-4.76). All chemical geometries were optimized by semi-empirical PM6 algorithm. Several quantum chemical parameters that reflect various intermolecular interactions as well as hydrophobicity were selected to develop QSAR model. The result indicates the regression model derived from logK ow , the most positive net atomic charges on an atom, Connolly solvent excluded volume, polarizability, and Abraham acidity could explain the partitioning mechanism of organic chemicals between BSA and water. The simulated external validation and cross validation verifies the developed model has good statistical robustness and predictive ability, thus can be used to estimate the logK BSA/W values for chemicals in application domain, accordingly to provide basic data for the toxicity assessment of the chemicals. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. Tuning electronic properties in graphene quantum dots by chemical functionalization: Density functional theory calculations

    NASA Astrophysics Data System (ADS)

    Abdelsalam, Hazem; Elhaes, Hanan; Ibrahim, Medhat A.

    2018-03-01

    The energy gap and dipole moment of chemically functionalized graphene quantum dots are investigated by density functional theory. The energy gap can be tuned through edge passivation by different elements or groups. Edge passivation by oxygen considerably decreases the energy gap in hexagonal nanodots. Edge states in triangular quantum dots can also be manipulated by passivation with fluorine. The dipole moment depends on: (a) shape and edge termination of the quantum dot, (b) attached group, and (c) position to which the groups are attached. Depending on the position of attached groups, the total dipole can be increased, decreased, or eliminated.

  1. Rhorix: An interface between quantum chemical topology and the 3D graphics program blender

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mills, Matthew J. L.; Sale, Kenneth L.; Simmons, Blake A.

    Journal of Computational Chemistry Published by Wiley Periodicals, Inc. Chemical research is assisted by the creation of visual representations that map concepts (such as atoms and bonds) to 3D objects. These concepts are rooted in chemical theory that predates routine solution of the Schrödinger equation for systems of interesting size. The method of Quantum Chemical Topology (QCT) provides an alternative, parameter-free means to understand chemical phenomena directly from quantum mechanical principles. Representation of the topological elements of QCT has lagged behind the best tools available. Here, we describe a general abstraction (and corresponding file format) that permits the definition ofmore » mappings between topological objects and their 3D representations. Possible mappings are discussed and a canonical example is suggested, which has been implemented as a Python “Add-On” named Rhorix for the state-of-the-art 3D modeling program Blender. This allows chemists to use modern drawing tools and artists to access QCT data in a familiar context. Finally, a number of examples are discussed..« less

  2. Rhorix: An interface between quantum chemical topology and the 3D graphics program blender

    PubMed Central

    Sale, Kenneth L.; Simmons, Blake A.; Popelier, Paul L. A.

    2017-01-01

    Chemical research is assisted by the creation of visual representations that map concepts (such as atoms and bonds) to 3D objects. These concepts are rooted in chemical theory that predates routine solution of the Schrödinger equation for systems of interesting size. The method of Quantum Chemical Topology (QCT) provides an alternative, parameter‐free means to understand chemical phenomena directly from quantum mechanical principles. Representation of the topological elements of QCT has lagged behind the best tools available. Here, we describe a general abstraction (and corresponding file format) that permits the definition of mappings between topological objects and their 3D representations. Possible mappings are discussed and a canonical example is suggested, which has been implemented as a Python “Add‐On” named Rhorix for the state‐of‐the‐art 3D modeling program Blender. This allows chemists to use modern drawing tools and artists to access QCT data in a familiar context. A number of examples are discussed. © 2017 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:28857244

  3. Rhorix: An interface between quantum chemical topology and the 3D graphics program blender

    DOE PAGES

    Mills, Matthew J. L.; Sale, Kenneth L.; Simmons, Blake A.; ...

    2017-08-31

    Journal of Computational Chemistry Published by Wiley Periodicals, Inc. Chemical research is assisted by the creation of visual representations that map concepts (such as atoms and bonds) to 3D objects. These concepts are rooted in chemical theory that predates routine solution of the Schrödinger equation for systems of interesting size. The method of Quantum Chemical Topology (QCT) provides an alternative, parameter-free means to understand chemical phenomena directly from quantum mechanical principles. Representation of the topological elements of QCT has lagged behind the best tools available. Here, we describe a general abstraction (and corresponding file format) that permits the definition ofmore » mappings between topological objects and their 3D representations. Possible mappings are discussed and a canonical example is suggested, which has been implemented as a Python “Add-On” named Rhorix for the state-of-the-art 3D modeling program Blender. This allows chemists to use modern drawing tools and artists to access QCT data in a familiar context. Finally, a number of examples are discussed..« less

  4. Proton chemical shift tensors determined by 3D ultrafast MAS double-quantum NMR spectroscopy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhang, Rongchun; Mroue, Kamal H.; Ramamoorthy, Ayyalusamy, E-mail: ramamoor@umich.edu

    2015-10-14

    Proton NMR spectroscopy in the solid state has recently attracted much attention owing to the significant enhancement in spectral resolution afforded by the remarkable advances in ultrafast magic angle spinning (MAS) capabilities. In particular, proton chemical shift anisotropy (CSA) has become an important tool for obtaining specific insights into inter/intra-molecular hydrogen bonding. However, even at the highest currently feasible spinning frequencies (110–120 kHz), {sup 1}H MAS NMR spectra of rigid solids still suffer from poor resolution and severe peak overlap caused by the strong {sup 1}H–{sup 1}H homonuclear dipolar couplings and narrow {sup 1}H chemical shift (CS) ranges, which rendermore » it difficult to determine the CSA of specific proton sites in the standard CSA/single-quantum (SQ) chemical shift correlation experiment. Herein, we propose a three-dimensional (3D) {sup 1}H double-quantum (DQ) chemical shift/CSA/SQ chemical shift correlation experiment to extract the CS tensors of proton sites whose signals are not well resolved along the single-quantum chemical shift dimension. As extracted from the 3D spectrum, the F1/F3 (DQ/SQ) projection provides valuable information about {sup 1}H–{sup 1}H proximities, which might also reveal the hydrogen-bonding connectivities. In addition, the F2/F3 (CSA/SQ) correlation spectrum, which is similar to the regular 2D CSA/SQ correlation experiment, yields chemical shift anisotropic line shapes at different isotropic chemical shifts. More importantly, since the F2/F1 (CSA/DQ) spectrum correlates the CSA with the DQ signal induced by two neighboring proton sites, the CSA spectrum sliced at a specific DQ chemical shift position contains the CSA information of two neighboring spins indicated by the DQ chemical shift. If these two spins have different CS tensors, both tensors can be extracted by numerical fitting. We believe that this robust and elegant single-channel proton-based 3D experiment provides useful

  5. Predicted phototoxicities of carbon nano-material by quantum mechanical calculations.

    EPA Science Inventory

    The basis of this research is obtaining the best quantum mechanical structure of carbon nanomaterials and is fundamental in determining their other properties. Therefore, their predictive phototoxicity is directly related to the materials’ structure. The results of this project w...

  6. Recent Trends in Quantum Chemical Modeling of Enzymatic Reactions.

    PubMed

    Himo, Fahmi

    2017-05-24

    The quantum chemical cluster approach is a powerful method for investigating enzymatic reactions. Over the past two decades, a large number of highly diverse systems have been studied and a great wealth of mechanistic insight has been developed using this technique. This Perspective reviews the current status of the methodology. The latest technical developments are highlighted, and challenges are discussed. Some recent applications are presented to illustrate the capabilities and progress of this approach, and likely future directions are outlined.

  7. The Radical Pair Mechanism and the Avian Chemical Compass: Quantum Coherence and Entanglement

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhang, Yiteng; Kais, Sabre; Berman, Gennady Petrovich

    2015-02-02

    We review the spin radical pair mechanism which is a promising explanation of avian navigation. This mechanism is based on the dependence of product yields on 1) the hyperfine interaction involving electron spins and neighboring nuclear spins and 2) the intensity and orientation of the geomagnetic field. One surprising result is that even at ambient conditions quantum entanglement of electron spins can play an important role in avian magnetoreception. This review describes the general scheme of chemical reactions involving radical pairs generated from singlet and triplet precursors; the spin dynamics of the radical pairs; and the magnetic field dependence ofmore » product yields caused by the radical pair mechanism. The main part of the review includes a description of the chemical compass in birds. We review: the general properties of the avian compass; the basic scheme of the radical pair mechanism; the reaction kinetics in cryptochrome; quantum coherence and entanglement in the avian compass; and the effects of noise. We believe that the quantum avian compass can play an important role in avian navigation and can also provide the foundation for a new generation of sensitive and selective magnetic-sensing nano-devices.« less

  8. Quantum-chemical investigations of spectroscopic properties of a fluorescence probe

    NASA Astrophysics Data System (ADS)

    Titova, T. Yu.; Morozova, Yu. P.; Zharkova, O. M.; Artyukhov, V. Ya.; Korolev, B. V.

    2012-09-01

    The prodan molecule (6-propionyl-2-dimethylamino naphthalene) - fluorescence probe - is investigated by quantum-chemical methods of intermediate neglect of differential overlap (INDO) and molecular electrostatic potential (MEP). The dipole moments of the ground and excited states, the nature and position of energy levels, the centers of specific solvation, the rate constants of photoprocesses, and the fluorescence quantum yield are estimated. To elucidate the role of the dimethylamino group in the formation of bands and spectral characteristics, the molecule only with the propionyl group (pron) is investigated. The long-wavelength absorption bands of prodan and pron molecules are interpreted. The results obtained for the prodan molecule by the INDO method with original spectroscopic parameterization are compared with the literature data obtained by the DFT/CIS, ZINDO/S, and AM1/CISD methods.

  9. Predicted phototoxicities of carbon nano-material by quantum mechanical calculations

    EPA Science Inventory

    The purpose of this research is to develop a predictive model for the phototoxicity potential of carbon nanomaterials (fullerenols and single-walled carbon nanotubes). This model is based on the quantum mechanical (ab initio) calculations on these carbon-based materials and compa...

  10. Quantum Chemical Mass Spectrometry: Verification and Extension of the Mobile Proton Model for Histidine

    NASA Astrophysics Data System (ADS)

    Cautereels, Julie; Blockhuys, Frank

    2017-06-01

    The quantum chemical mass spectrometry for materials science (QCMS2) method is used to verify the proposed mechanism for proton transfer - the Mobile Proton Model (MPM) - by histidine for ten XHS tripeptides, based on quantum chemical calculations at the DFT/B3LYP/6-311+G* level of theory. The fragmentations of the different intermediate structures in the MPM mechanism are studied within the QCMS2 framework, and the energetics of the proposed mechanism itself and those of the fragmentations of the intermediate structures are compared, leading to the computational confirmation of the MPM. In addition, the calculations suggest that the mechanism should be extended from considering only the formation of five-membered ring intermediates to include larger-ring intermediates. [Figure not available: see fulltext.

  11. Prediction of Chemical Function: Model Development and ...

    EPA Pesticide Factsheets

    The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

  12. Quantum chemical methods for the investigation of photoinitiated processes in biological systems: theory and applications.

    PubMed

    Dreuw, Andreas

    2006-11-13

    With the advent of modern computers and advances in the development of efficient quantum chemical computer codes, the meaningful computation of large molecular systems at a quantum mechanical level became feasible. Recent experimental effort to understand photoinitiated processes in biological systems, for instance photosynthesis or vision, at a molecular level also triggered theoretical investigations in this field. In this Minireview, standard quantum chemical methods are presented that are applicable and recently used for the calculation of excited states of photoinitiated processes in biological molecular systems. These methods comprise configuration interaction singles, the complete active space self-consistent field method, and time-dependent density functional theory and its variants. Semiempirical approaches are also covered. Their basic theoretical concepts and mathematical equations are briefly outlined, and their properties and limitations are discussed. Recent successful applications of the methods to photoinitiated processes in biological systems are described and theoretical tools for the analysis of excited states are presented.

  13. EPA'S TOXCAST PROGRAM FOR PREDICTING TOXICITY AND PRIORITIZING ENVIRONMENTAL CHEMICALS

    EPA Science Inventory

    ToxCast is a research program to predict or forecast toxicity by evaluating a broad spectrum of chemicals and effects; physical-chemical properties, predicted bioactivities, HTS and cell-based assays, and genomics. Data will be interpretively linked to known or predicted toxicol...

  14. Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach.

    PubMed

    Ramakrishnan, Raghunathan; Dral, Pavlo O; Rupp, Matthias; von Lilienfeld, O Anatole

    2015-05-12

    Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry. We introduce a composite strategy that adds machine learning corrections to computationally inexpensive approximate legacy quantum methods. After training, highly accurate predictions of enthalpies, free energies, entropies, and electron correlation energies are possible, for significantly larger molecular sets than used for training. For thermochemical properties of up to 16k isomers of C7H10O2 we present numerical evidence that chemical accuracy can be reached. We also predict electron correlation energy in post Hartree-Fock methods, at the computational cost of Hartree-Fock, and we establish a qualitative relationship between molecular entropy and electron correlation. The transferability of our approach is demonstrated, using semiempirical quantum chemistry and machine learning models trained on 1 and 10% of 134k organic molecules, to reproduce enthalpies of all remaining molecules at density functional theory level of accuracy.

  15. Prospect of quantum anomalous Hall and quantum spin Hall effect in doped kagome lattice Mott insulators.

    PubMed

    Guterding, Daniel; Jeschke, Harald O; Valentí, Roser

    2016-05-17

    Electronic states with non-trivial topology host a number of novel phenomena with potential for revolutionizing information technology. The quantum anomalous Hall effect provides spin-polarized dissipation-free transport of electrons, while the quantum spin Hall effect in combination with superconductivity has been proposed as the basis for realizing decoherence-free quantum computing. We introduce a new strategy for realizing these effects, namely by hole and electron doping kagome lattice Mott insulators through, for instance, chemical substitution. As an example, we apply this new approach to the natural mineral herbertsmithite. We prove the feasibility of the proposed modifications by performing ab-initio density functional theory calculations and demonstrate the occurrence of the predicted effects using realistic models. Our results herald a new family of quantum anomalous Hall and quantum spin Hall insulators at affordable energy/temperature scales based on kagome lattices of transition metal ions.

  16. Quantum chemical study of a derivative of 3-substituted dithiocarbamic flavanone

    NASA Astrophysics Data System (ADS)

    Gosav, Steluta; Paduraru, Nicoleta; Maftei, Dan; Birsa, Mihail Lucian; Praisler, Mirela

    2017-02-01

    The aim of this work is to characterize a quite novel 3-dithiocarbamic flavonoid by vibrational spectroscopy in conjunction with Density Functional Theory (DFT) calculations. Quantum mechanics calculations of energies, geometries and vibrational wavenumbers in the ground state were carried out by using hybrid functional B3LYP with 6-311G(d,p) as basis set. The results indicate a remarkable agreement between the calculated molecular geometries, as well as vibrational frequencies, and the corresponding experimental data. In addition, a complete assignment of all the absorption bands present in the vibrational spectrum has been performed. In order to assess its chemical potential, quantum molecular descriptors characterizing the interactions between the 3-dithiocarbamic flavonoid and its biological receptors have been computed. The frontier molecular orbitals and the HOMO-LUMO energy gap have been used in order to explain the way in which the new molecule can interact with other species and to characterize its molecular chemical stability/reactivity. The molecular electrostatic potential (MEP) map, computed in order to identify the sites of the studied flavonoid that are most likely to interact with electrophilic and nucleophilic species, is discussed.

  17. Quantum-gravity predictions for the fine-structure constant

    NASA Astrophysics Data System (ADS)

    Eichhorn, Astrid; Held, Aaron; Wetterich, Christof

    2018-07-01

    Asymptotically safe quantum fluctuations of gravity can uniquely determine the value of the gauge coupling for a large class of grand unified models. In turn, this makes the electromagnetic fine-structure constant calculable. The balance of gravity and matter fluctuations results in a fixed point for the running of the gauge coupling. It is approached as the momentum scale is lowered in the transplanckian regime, leading to a uniquely predicted value of the gauge coupling at the Planck scale. The precise value of the predicted fine-structure constant depends on the matter content of the grand unified model. It is proportional to the gravitational fluctuation effects for which computational uncertainties remain to be settled.

  18. Correlation of chemical shifts predicted by molecular dynamics simulations for partially disordered proteins.

    PubMed

    Karp, Jerome M; Eryilmaz, Ertan; Erylimaz, Ertan; Cowburn, David

    2015-01-01

    There has been a longstanding interest in being able to accurately predict NMR chemical shifts from structural data. Recent studies have focused on using molecular dynamics (MD) simulation data as input for improved prediction. Here we examine the accuracy of chemical shift prediction for intein systems, which have regions of intrinsic disorder. We find that using MD simulation data as input for chemical shift prediction does not consistently improve prediction accuracy over use of a static X-ray crystal structure. This appears to result from the complex conformational ensemble of the disordered protein segments. We show that using accelerated molecular dynamics (aMD) simulations improves chemical shift prediction, suggesting that methods which better sample the conformational ensemble like aMD are more appropriate tools for use in chemical shift prediction for proteins with disordered regions. Moreover, our study suggests that data accurately reflecting protein dynamics must be used as input for chemical shift prediction in order to correctly predict chemical shifts in systems with disorder.

  19. Type I and II β-turns prediction using NMR chemical shifts.

    PubMed

    Wang, Ching-Cheng; Lai, Wen-Chung; Chuang, Woei-Jer

    2014-07-01

    A method for predicting type I and II β-turns using nuclear magnetic resonance (NMR) chemical shifts is proposed. Isolated β-turn chemical-shift data were collected from 1,798 protein chains. One-dimensional statistical analyses on chemical-shift data of three classes β-turn (type I, II, and VIII) showed different distributions at four positions, (i) to (i + 3). Considering the central two residues of type I β-turns, the mean values of Cο, Cα, H(N), and N(H) chemical shifts were generally (i + 1) > (i + 2). The mean values of Cβ and Hα chemical shifts were (i + 1) < (i + 2). The distributions of the central two residues in type II and VIII β-turns were also distinguishable by trends of chemical shift values. Two-dimensional cluster analyses on chemical-shift data show positional distributions more clearly. Based on these propensities of chemical shift classified as a function of position, rules were derived using scoring matrices for four consecutive residues to predict type I and II β-turns. The proposed method achieves an overall prediction accuracy of 83.2 and 84.2% with the Matthews correlation coefficient values of 0.317 and 0.632 for type I and II β-turns, indicating that its higher accuracy for type II turn prediction. The results show that it is feasible to use NMR chemical shifts to predict the β-turn types in proteins. The proposed method can be incorporated into other chemical-shift based protein secondary structure prediction methods.

  20. Protein structure refinement using a quantum mechanics-based chemical shielding predictor† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6sc04344e Click here for additional data file.

    PubMed Central

    2017-01-01

    The accurate prediction of protein chemical shifts using a quantum mechanics (QM)-based method has been the subject of intense research for more than 20 years but so far empirical methods for chemical shift prediction have proven more accurate. In this paper we show that a QM-based predictor of a protein backbone and CB chemical shifts (ProCS15, PeerJ, 2016, 3, e1344) is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors. We present a method by which quantum chemistry based predictions of isotropic chemical shielding values (ProCS15) can be used to refine protein structures using Markov Chain Monte Carlo (MCMC) simulations, relating the chemical shielding values to the experimental chemical shifts probabilistically. Two kinds of MCMC structural refinement simulations were performed using force field geometry optimized X-ray structures as starting points: simulated annealing of the starting structure and constant temperature MCMC simulation followed by simulated annealing of a representative ensemble structure. Annealing of the CHARMM structure changes the CA-RMSD by an average of 0.4 Å but lowers the chemical shift RMSD by 1.0 and 0.7 ppm for CA and N. Conformational averaging has a relatively small effect (0.1–0.2 ppm) on the overall agreement with carbon chemical shifts but lowers the error for nitrogen chemical shifts by 0.4 ppm. If an amino acid specific offset is included the ProCS15 predicted chemical shifts have RMSD values relative to experiments that are comparable to popular empirical chemical shift predictors. The annealed representative ensemble structures differ in CA-RMSD relative to the initial structures by an average of 2.0 Å, with >2.0 Å difference for six proteins. In four of the cases, the largest structural differences arise in structurally flexible regions of the protein as determined by NMR, and in the remaining two cases, the large

  1. Combined EXAFS Spectroscopic and Quantum Chemical Study on the Complex Formation of Am(III) with Formate.

    PubMed

    Fröhlich, Daniel R; Kremleva, Alena; Rossberg, André; Skerencak-Frech, Andrej; Koke, Carsten; Krüger, Sven; Rösch, Notker; Panak, Petra J

    2017-06-19

    The complexation of Am(III) with formate in aqueous solution is studied as a function of the pH value using a combination of extended X-ray absorption fine structure (EXAFS) spectroscopy, iterative transformation factor analysis (ITFA), and quantum chemical calculations. The Am L III -edge EXAFS spectra are analyzed to determine the molecular structure (coordination numbers; Am-O and Am-C distances) of the formed Am(III)-formate species and to track the shift of the Am(III) speciation with increasing pH. The experimental data are compared to predictions from density functional calculations. The results indicate that formate binds to Am(III) in a monodentate fashion, in agreement with crystal structures of lanthanide formates. Furthermore, the investigations are complemented by thermodynamic speciation calculations to verify further the results obtained.

  2. Prediction of enzyme binding: human thrombin inhibition study by quantum chemical and artificial intelligence methods based on X-ray structures.

    PubMed

    Mlinsek, G; Novic, M; Hodoscek, M; Solmajer, T

    2001-01-01

    Thrombin is a serine protease which plays important roles in the human body, the key one being the control of thrombus formation. The inhibition of thrombin has become a target for new antithrombotics. The aim of our work was to (i) construct a model which would enable us to predict Ki values for the binding of an inhibitor into the active site of thrombin based on a database of known X-ray structures of inhibitor-enzyme complexes and (ii) to identify the structural and electrostatic characteristics of inhibitor molecules crucially important to their effective binding. To retain as much of the 3D structural information of the bound inhibitor as possible, we implemented the quantum mechanical/molecular mechanical (QM/MM) procedure for calculating the molecular electrostatic potential (MEP) at the van der Waals surfaces of atoms in the protein's active site. The inhibitor was treated quantum mechanically, while the rest of the complex was treated by classical means. The obtained MEP values served as inputs into the counter-propagation artificial neural network (CP-ANN), and a genetic algorithm was subsequently used to search for the combination of atoms that predominantly influences the binding. The constructed CP-ANN model yielded Ki values predictions with a correlation coefficient of 0.96, with Ki values extended over 7 orders of magnitude. Our approach also shows the relative importance of the various amino acid residues present in the active site of the enzyme for inhibitor binding. The list of residues selected by our automatic procedure is in good correlation with the current consensus regarding the importance of certain crucial residues in thrombin's active site.

  3. Surface emitting ring quantum cascade lasers for chemical sensing

    NASA Astrophysics Data System (ADS)

    Szedlak, Rolf; Hayden, Jakob; Martín-Mateos, Pedro; Holzbauer, Martin; Harrer, Andreas; Schwarz, Benedikt; Hinkov, Borislav; MacFarland, Donald; Zederbauer, Tobias; Detz, Hermann; Andrews, Aaron Maxwell; Schrenk, Werner; Acedo, Pablo; Lendl, Bernhard; Strasser, Gottfried

    2018-01-01

    We review recent advances in chemical sensing applications based on surface emitting ring quantum cascade lasers (QCLs). Such lasers can be implemented in monolithically integrated on-chip laser/detector devices forming compact gas sensors, which are based on direct absorption spectroscopy according to the Beer-Lambert law. Furthermore, we present experimental results on radio frequency modulation up to 150 MHz of surface emitting ring QCLs. This technique provides detailed insight into the modulation characteristics of such lasers. The gained knowledge facilitates the utilization of ring QCLs in combination with spectroscopic techniques, such as heterodyne phase-sensitive dispersion spectroscopy for gas detection and analysis.

  4. Predicting the chemical stability of monatomic chains

    NASA Astrophysics Data System (ADS)

    Lin, Zheng-Zhe; Chen, Xi

    2013-02-01

    A simple model for evaluating the thermal atomic transfer rates in nanosystems (Lin Z.-Z. et al., EPL, 94 (2011) 40002) was developed to predict the chemical reaction rates of nanosystems with small gas molecules. The accuracy of the model was verified by MD simulations for molecular adsorption and desorption on a monatomic chain. By the prediction, a monatomic carbon chain should survive for 1.2 × 102 years in the ambient of 1 atm O2 at room temperature, and it is very invulnerable to N2, H2O, NO2, CO and CO2, while a monatomic gold chain quickly ruptures in vacuum. It is worth noting that since the model can be easily applied via common ab initio calculations, it could be widely used in the prediction of chemical stability of nanosystems.

  5. Entanglement model of homeopathy as an example of generalized entanglement predicted by weak quantum theory.

    PubMed

    Walach, H

    2003-08-01

    Homeopathy is scientifically banned, both for lack of consistent empirical findings, but more so for lack of a sound theoretical model to explain its purported effects. This paper makes an attempt to introduce an explanatory idea based on a generalized version of quantum mechanics (QM), the weak quantum theory (WQT). WQT uses the algebraic formalism of QM proper, but drops some restrictions and definitions typical for QM. This results in a general axiomatic framework similar to QM, but more generalized and applicable to all possible systems. Most notably, WQT predicts entanglement, which in QM is known as Einstein-Podolsky-Rosen (EPR) correlatedness within quantum systems. According to WQT, this entanglement is not only tied to quantum systems, but is to be expected whenever a global and a local variable describing a system are complementary. This idea is used here to reconstruct homeopathy as an exemplification of generalized entanglement as predicted by WQT. It transpires that homeopathy uses two instances of generalized entanglement: one between the remedy and the original substance (potentiation principle) and one between the individual symptoms of a patient and the general symptoms of a remedy picture (similarity principle). By bringing these two elements together, double entanglement ensues, which is reminiscent of cryptographic and teleportation applications of entanglement in QM proper. Homeopathy could be a macroscopic analogue to quantum teleportation. This model is exemplified and some predictions are derived, which make it possible to test the model. Copyright 2003 S. Karger GmbH, Freiburg

  6. Simulating chemistry using quantum computers.

    PubMed

    Kassal, Ivan; Whitfield, James D; Perdomo-Ortiz, Alejandro; Yung, Man-Hong; Aspuru-Guzik, Alán

    2011-01-01

    The difficulty of simulating quantum systems, well known to quantum chemists, prompted the idea of quantum computation. One can avoid the steep scaling associated with the exact simulation of increasingly large quantum systems on conventional computers, by mapping the quantum system to another, more controllable one. In this review, we discuss to what extent the ideas in quantum computation, now a well-established field, have been applied to chemical problems. We describe algorithms that achieve significant advantages for the electronic-structure problem, the simulation of chemical dynamics, protein folding, and other tasks. Although theory is still ahead of experiment, we outline recent advances that have led to the first chemical calculations on small quantum information processors.

  7. Development of a model for predicting reaction rate constants of organic chemicals with ozone at different temperatures.

    PubMed

    Li, Xuehua; Zhao, Wenxing; Li, Jing; Jiang, Jingqiu; Chen, Jianji; Chen, Jingwen

    2013-08-01

    To assess the persistence and fate of volatile organic compounds in the troposphere, the rate constants for the reaction with ozone (kO3) are needed. As kO3 values are only available for hundreds of compounds, and experimental determination of kO3 is costly and time-consuming, it is of importance to develop predictive models on kO3. In this study, a total of 379 logkO3 values at different temperatures were used to develop and validate a model for the prediction of kO3, based on quantum chemical descriptors, Dragon descriptors and structural fragments. Molecular descriptors were screened by stepwise multiple linear regression, and the model was constructed by partial least-squares regression. The cross validation coefficient QCUM(2) of the model is 0.836, and the external validation coefficient Qext(2) is 0.811, indicating that the model has high robustness and good predictive performance. The most significant descriptor explaining logkO3 is the BELm2 descriptor with connectivity information weighted atomic masses. kO3 increases with increasing BELm2, and decreases with increasing ionization potential. The applicability domain of the proposed model was visualized by the Williams plot. The developed model can be used to predict kO3 at different temperatures for a wide range of organic chemicals, including alkenes, cycloalkenes, haloalkenes, alkynes, oxygen-containing compounds, nitrogen-containing compounds (except primary amines) and aromatic compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Quantum chemical approaches to [NiFe] hydrogenase.

    PubMed

    Vaissier, Valerie; Van Voorhis, Troy

    2017-05-09

    The mechanism by which [NiFe] hydrogenase catalyses the oxidation of molecular hydrogen is a significant yet challenging topic in bioinorganic chemistry. With far-reaching applications in renewable energy and carbon mitigation, significant effort has been invested in the study of these complexes. In particular, computational approaches offer a unique perspective on how this enzyme functions at an electronic and atomistic level. In this article, we discuss state-of-the art quantum chemical methods and how they have helped deepen our comprehension of [NiFe] hydrogenase. We outline the key strategies that can be used to compute the (i) geometry, (ii) electronic structure, (iii) thermodynamics and (iv) kinetic properties associated with the enzymatic activity of [NiFe] hydrogenase and other bioinorganic complexes. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

  9. Strained-layer InGaAs/GaAs/AlGaAs single quantum well lasers with high internal quantum efficiency

    NASA Technical Reports Server (NTRS)

    Larsson, Anders; Cody, Jeffrey; Lang, Robert J.

    1989-01-01

    Low threshold current density strained-layer In(0.2)Ga(0.8)As/GaAs/AlGaAs single quantum well lasers, emitting at 980 nm, have been grown by molecular beam epitaxy. Contrary to what has been reported for broad-area lasers with pseudomorphic InGaAs active layers grown by metalorganic chemical vapor deposition, these layers exhibit a high internal quantum efficiency (about 90 percent). The maximum external differential quantum efficiency is 70 percent, limited by an anomalously high internal loss possibly caused by a large lateral spreading of the optical mode. In addition, experimental results supporting the theoretically predicted strain-induced reduction of the valence-band nonparabolicity and density of states are presented.

  10. Reassigning the Structures of Natural Products Using NMR Chemical Shifts Computed with Quantum Mechanics: A Laboratory Exercise

    ERIC Educational Resources Information Center

    Palazzo, Teresa A.; Truong, Tiana T.; Wong, Shirley M. T.; Mack, Emma T.; Lodewyk, Michael W.; Harrison, Jason G.; Gamage, R. Alan; Siegel, Justin B.; Kurth, Mark J.; Tantillo, Dean J.

    2015-01-01

    An applied computational chemistry laboratory exercise is described in which students use modern quantum chemical calculations of chemical shifts to assign the structure of a recently isolated natural product. A pre/post assessment was used to measure student learning gains and verify that students demonstrated proficiency of key learning…

  11. Include dispersion in quantum chemical modeling of enzymatic reactions: the case of isoaspartyl dipeptidase.

    PubMed

    Zhang, Hai-Mei; Chen, Shi-Lu

    2015-06-09

    The lack of dispersion in the B3LYP functional has been proposed to be the main origin of big errors in quantum chemical modeling of a few enzymes and transition metal complexes. In this work, the essential dispersion effects that affect quantum chemical modeling are investigated. With binuclear zinc isoaspartyl dipeptidase (IAD) as an example, dispersion is included in the modeling of enzymatic reactions by two different procedures, i.e., (i) geometry optimizations followed by single-point calculations of dispersion (approach I) and (ii) the inclusion of dispersion throughout geometry optimization and energy evaluation (approach II). Based on a 169-atom chemical model, the calculations show a qualitative consistency between approaches I and II in energetics and most key geometries, demonstrating that both approaches are available with the latter preferential since both geometry and energy are dispersion-corrected in approach II. When a smaller model without Arg233 (147 atoms) was used, an inconsistency was observed, indicating that the missing dispersion interactions are essentially responsible for determining equilibrium geometries. Other technical issues and mechanistic characteristics of IAD are also discussed, in particular with respect to the effects of Arg233.

  12. High-throughput dietary exposure predictions for chemical migrants from food contact substances for use in chemical prioritization.

    PubMed

    Biryol, Derya; Nicolas, Chantel I; Wambaugh, John; Phillips, Katherine; Isaacs, Kristin

    2017-11-01

    Under the ExpoCast program, United States Environmental Protection Agency (EPA) researchers have developed a high-throughput (HT) framework for estimating aggregate exposures to chemicals from multiple pathways to support rapid prioritization of chemicals. Here, we present methods to estimate HT exposures to chemicals migrating into food from food contact substances (FCS). These methods consisted of combining an empirical model of chemical migration with estimates of daily population food intakes derived from food diaries from the National Health and Nutrition Examination Survey (NHANES). A linear regression model for migration at equilibrium was developed by fitting available migration measurements as a function of temperature, food type (i.e., fatty, aqueous, acidic, alcoholic), initial chemical concentration in the FCS (C 0 ) and chemical properties. The most predictive variables in the resulting model were C 0 , molecular weight, log K ow , and food type (R 2 =0.71, p<0.0001). Migration-based concentrations for 1009 chemicals identified via publicly-available data sources as being present in polymer FCSs were predicted for 12 food groups (combinations of 3 storage temperatures and food type). The model was parameterized with screening-level estimates of C 0 based on the functional role of chemicals in FCS. By combining these concentrations with daily intakes for food groups derived from NHANES, population ingestion exposures of chemical in mg/kg-bodyweight/day (mg/kg-BW/day) were estimated. Calibrated aggregate exposures were estimated for 1931 chemicals by fitting HT FCS and consumer product exposures to exposures inferred from NHANES biomonitoring (R 2 =0.61, p<0.001); both FCS and consumer product pathway exposures were significantly predictive of inferred exposures. Including the FCS pathway significantly impacted the ratio of predicted exposures to those estimated to produce steady-state blood concentrations equal to in-vitro bioactive concentrations

  13. Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies.

    PubMed

    Hansen, Katja; Montavon, Grégoire; Biegler, Franziska; Fazli, Siamac; Rupp, Matthias; Scheffler, Matthias; von Lilienfeld, O Anatole; Tkatchenko, Alexandre; Müller, Klaus-Robert

    2013-08-13

    The accurate and reliable prediction of properties of molecules typically requires computationally intensive quantum-chemical calculations. Recently, machine learning techniques applied to ab initio calculations have been proposed as an efficient approach for describing the energies of molecules in their given ground-state structure throughout chemical compound space (Rupp et al. Phys. Rev. Lett. 2012, 108, 058301). In this paper we outline a number of established machine learning techniques and investigate the influence of the molecular representation on the methods performance. The best methods achieve prediction errors of 3 kcal/mol for the atomization energies of a wide variety of molecules. Rationales for this performance improvement are given together with pitfalls and challenges when applying machine learning approaches to the prediction of quantum-mechanical observables.

  14. Sensitivity of ab Initio vs Empirical Methods in Computing Structural Effects on NMR Chemical Shifts for the Example of Peptides.

    PubMed

    Sumowski, Chris Vanessa; Hanni, Matti; Schweizer, Sabine; Ochsenfeld, Christian

    2014-01-14

    The structural sensitivity of NMR chemical shifts as computed by quantum chemical methods is compared to a variety of empirical approaches for the example of a prototypical peptide, the 38-residue kaliotoxin KTX comprising 573 atoms. Despite the simplicity of empirical chemical shift prediction programs, the agreement with experimental results is rather good, underlining their usefulness. However, we show in our present work that they are highly insensitive to structural changes, which renders their use for validating predicted structures questionable. In contrast, quantum chemical methods show the expected high sensitivity to structural and electronic changes. This appears to be independent of the quantum chemical approach or the inclusion of solvent effects. For the latter, explicit solvent simulations with increasing number of snapshots were performed for two conformers of an eight amino acid sequence. In conclusion, the empirical approaches neither provide the expected magnitude nor the patterns of NMR chemical shifts determined by the clearly more costly ab initio methods upon structural changes. This restricts the use of empirical prediction programs in studies where peptide and protein structures are utilized for the NMR chemical shift evaluation such as in NMR refinement processes, structural model verifications, or calculations of NMR nuclear spin relaxation rates.

  15. Fast Quantum Algorithm for Predicting Descriptive Statistics of Stochastic Processes

    NASA Technical Reports Server (NTRS)

    Williams Colin P.

    1999-01-01

    Stochastic processes are used as a modeling tool in several sub-fields of physics, biology, and finance. Analytic understanding of the long term behavior of such processes is only tractable for very simple types of stochastic processes such as Markovian processes. However, in real world applications more complex stochastic processes often arise. In physics, the complicating factor might be nonlinearities; in biology it might be memory effects; and in finance is might be the non-random intentional behavior of participants in a market. In the absence of analytic insight, one is forced to understand these more complex stochastic processes via numerical simulation techniques. In this paper we present a quantum algorithm for performing such simulations. In particular, we show how a quantum algorithm can predict arbitrary descriptive statistics (moments) of N-step stochastic processes in just O(square root of N) time. That is, the quantum complexity is the square root of the classical complexity for performing such simulations. This is a significant speedup in comparison to the current state of the art.

  16. Mechanism of Microwave-Assisted Pyrolysis of Glucose to Furfural Revealed by Isotopic Tracer and Quantum Chemical Calculations.

    PubMed

    Bao, Liwei; Shi, Lei; Luo, Hu; Kong, Lingzhao; Li, Shenggang; Wei, Wei; Sun, Yuhan

    2017-08-10

    Glucose labeled with 13 C or 18 O was used to investigate the mechanism of its conversion into furfural by microwaveassisted pyrolysis. The isotopic content and location in furfural were determined from GC-MS and 13 C NMR spectroscopic measurements and data analysis. The results suggest that the carbon skeleton in furfural is mainly derived from C1 to C5 of glucose, whereas the C of the aldehyde group and the O of the furan ring in furfural primarily originate from C1 and O5 of glucose, respectively. For the first time, the source of O in the furan ring of furfural was elucidated directly by experiment, providing results that are consistent with predictions from recent quantum chemical calculations. Moreover, further theoretical calculations indicate substantially lower energy barriers than previous predictions by considering the potential catalytic effect of formic acid, which is one of the pyrolysis products. The catalytic role of formic acid is further confirmed by experimental evidence. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Quantum Mechanics predicts evolutionary biology.

    PubMed

    Torday, J S

    2018-07-01

    Nowhere are the shortcomings of conventional descriptive biology more evident than in the literature on Quantum Biology. In the on-going effort to apply Quantum Mechanics to evolutionary biology, merging Quantum Mechanics with the fundamentals of evolution as the First Principles of Physiology-namely negentropy, chemiosmosis and homeostasis-offers an authentic opportunity to understand how and why physics constitutes the basic principles of biology. Negentropy and chemiosmosis confer determinism on the unicell, whereas homeostasis constitutes Free Will because it offers a probabilistic range of physiologic set points. Similarly, on this basis several principles of Quantum Mechanics also apply directly to biology. The Pauli Exclusion Principle is both deterministic and probabilistic, whereas non-localization and the Heisenberg Uncertainty Principle are both probabilistic, providing the long-sought after ontologic and causal continuum from physics to biology and evolution as the holistic integration recognized as consciousness for the first time. Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. An integrated multi-label classifier with chemical-chemical interactions for prediction of chemical toxicity effects.

    PubMed

    Liu, Tao; Chen, Lei; Pan, Xiaoyong

    2018-05-31

    Chemical toxicity effect is one of the major reasons for declining candidate drugs. Detecting the toxicity effects of all chemicals can accelerate the procedures of drug discovery. However, it is time-consuming and expensive to identify the toxicity effects of a given chemical through traditional experiments. Designing quick, reliable and non-animal-involved computational methods is an alternative way. In this study, a novel integrated multi-label classifier was proposed. First, based on five types of chemical-chemical interactions retrieved from STITCH, each of which is derived from one aspect of chemicals, five individual classifiers were built. Then, several integrated classifiers were built by integrating some or all individual classifiers. By testing the integrated classifiers on a dataset with chemicals and their toxicity effects in Accelrys Toxicity database and non-toxic chemicals with their performance evaluated by jackknife test, an optimal integrated classifier was selected as the proposed classifier, which provided quite high prediction accuracies and wide applications. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  19. Predictive Modeling of Chemical Hazard by Integrating Numerical Descriptors of Chemical Structures and Short-term Toxicity Assay Data

    PubMed Central

    Rusyn, Ivan; Sedykh, Alexander; Guyton, Kathryn Z.; Tropsha, Alexander

    2012-01-01

    Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR–like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage. PMID:22387746

  20. Structural and vibrational spectral investigations of melaminium maleate monohydrate by FTIR, FT-Raman and quantum chemical calculations

    NASA Astrophysics Data System (ADS)

    Arjunan, V.; Kalaivani, M.; Marchewka, M. K.; Mohan, S.

    2013-04-01

    The structural investigations of the molecular complex of melamine with maleic acid, namely melaminium maleate monohydrate have been carried out by quantum chemical methods in addition to FTIR, FT-Raman and far-infrared spectral studies. The quantum chemical studies were performed with DFT (B3LYP) method using 6-31G**, cc-pVDZ and 6-311++G** basis sets to determine the energy, structural and thermodynamic parameters of melaminium maleate monohydrate. The hydrogen atom from maleic acid was transferred to the melamine molecule giving the singly protonated melaminium cation. The ability of ions to form spontaneous three-dimensional structure through weak Osbnd H⋯O and Nsbnd H⋯O hydrogen bonds shows notable vibrational effects.

  1. Predicting drug side-effect profiles: a chemical fragment-based approach

    PubMed Central

    2011-01-01

    Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. Results In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments) and side-effects. This is made possible using sparse canonical correlation analysis (SCCA). In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. Conclusions The proposed method is expected to be useful in various stages of the drug development process. PMID:21586169

  2. 1-Methoxy-1-silacyclohexane: Synthesis, molecular structure and conformational behavior by gas electron diffraction, Raman spectroscopy and quantum chemical calculations

    NASA Astrophysics Data System (ADS)

    Shlykov, Sergey A.; Puchkov, Boris V.; Arnason, Ingvar; Wallevik, Sunna Ó.; Giricheva, Nina I.; Girichev, Georgiy V.; Zhabanov, Yuriy A.

    2018-02-01

    The synthesis and results of gas electron diffraction (GED), temperature-dependent Raman spectroscopy, along with detailed quantum chemical (QC) study of 1-methoxy-1-silacyclohexane 1 are reported. Within the series of the QC results, DFT(B3LYP, PBE0, M06, M062X), and MP2, the conformational preference predictions are rather contradictive. From the both GED and Raman experimental methods applied, the vapour and liquid phases of 1 were found to exist as a mixture of two conformers, gauche-axial and gauche-equatorial, with almost equal contributions, while the trans-forms are much less stable. In addition, theoretical calculations on the cyclohexane analog, methoxycyclohexane 2, are performed in order to compare with the conformational properties of 1. The latter is predicted not to diminish the axial/equatorial ratio, as contrasted to the expectations at switching the point of the substituent attachment from Si to C.

  3. High Color-Purity Green, Orange, and Red Light-Emitting Didoes Based on Chemically Functionalized Graphene Quantum Dots

    NASA Astrophysics Data System (ADS)

    Kwon, Woosung; Kim, Young-Hoon; Kim, Ji-Hee; Lee, Taehyung; Do, Sungan; Park, Yoonsang; Jeong, Mun Seok; Lee, Tae-Woo; Rhee, Shi-Woo

    2016-04-01

    Chemically derived graphene quantum dots (GQDs) to date have showed very broad emission linewidth due to many kinds of chemical bondings with different energy levels, which significantly degrades the color purity and color tunability. Here, we show that use of aniline derivatives to chemically functionalize GQDs generates new extrinsic energy levels that lead to photoluminescence of very narrow linewidths. We use transient absorption and time-resolved photoluminescence spectroscopies to study the electronic structures and related electronic transitions of our GQDs, which reveals that their underlying carrier dynamics is strongly related to the chemical properties of aniline derivatives. Using these functionalized GQDs as lumophores, we fabricate light-emitting didoes (LEDs) that exhibit green, orange, and red electroluminescence that has high color purity. The maximum current efficiency of 3.47 cd A-1 and external quantum efficiency of 1.28% are recorded with our LEDs; these are the highest values ever reported for LEDs based on carbon-nanoparticle phosphors. This functionalization of GQDs with aniline derivatives represents a new method to fabricate LEDs that produce natural color.

  4. Predictable quantum efficient detector based on n-type silicon photodiodes

    NASA Astrophysics Data System (ADS)

    Dönsberg, Timo; Manoocheri, Farshid; Sildoja, Meelis; Juntunen, Mikko; Savin, Hele; Tuovinen, Esa; Ronkainen, Hannu; Prunnila, Mika; Merimaa, Mikko; Tang, Chi Kwong; Gran, Jarle; Müller, Ingmar; Werner, Lutz; Rougié, Bernard; Pons, Alicia; Smîd, Marek; Gál, Péter; Lolli, Lapo; Brida, Giorgio; Rastello, Maria Luisa; Ikonen, Erkki

    2017-12-01

    The predictable quantum efficient detector (PQED) consists of two custom-made induced junction photodiodes that are mounted in a wedged trap configuration for the reduction of reflectance losses. Until now, all manufactured PQED photodiodes have been based on a structure where a SiO2 layer is thermally grown on top of p-type silicon substrate. In this paper, we present the design, manufacturing, modelling and characterization of a new type of PQED, where the photodiodes have an Al2O3 layer on top of n-type silicon substrate. Atomic layer deposition is used to deposit the layer to the desired thickness. Two sets of photodiodes with varying oxide thicknesses and substrate doping concentrations were fabricated. In order to predict recombination losses of charge carriers, a 3D model of the photodiode was built into Cogenda Genius semiconductor simulation software. It is important to note that a novel experimental method was developed to obtain values for the 3D model parameters. This makes the prediction of the PQED responsivity a completely autonomous process. Detectors were characterized for temperature dependence of dark current, spatial uniformity of responsivity, reflectance, linearity and absolute responsivity at the wavelengths of 488 nm and 532 nm. For both sets of photodiodes, the modelled and measured responsivities were generally in agreement within the measurement and modelling uncertainties of around 100 parts per million (ppm). There is, however, an indication that the modelled internal quantum deficiency may be underestimated by a similar amount. Moreover, the responsivities of the detectors were spatially uniform within 30 ppm peak-to-peak variation. The results obtained in this research indicate that the n-type induced junction photodiode is a very promising alternative to the existing p-type detectors, and thus give additional credibility to the concept of modelled quantum detector serving as a primary standard. Furthermore, the manufacturing of

  5. Characterization of heterocyclic rings through quantum chemical topology.

    PubMed

    Griffiths, Mark Z; Popelier, Paul L A

    2013-07-22

    Five-membered rings are found in a myriad of molecules important in a wide range of areas such as catalysis, nutrition, and drug and agrochemical design. Systematic insight into their largely unexplored chemical space benefits from first principle calculations presented here. This study comprehensively investigates a grand total of 764 different rings, all geometry optimized at the B3LYP/6-311+G(2d,p) level, from the perspective of Quantum Chemical Topology (QCT). For the first time, a 3D space of local topological properties was introduced, in order to characterize rings compactly. This space is called RCP space, after the so-called ring critical point. This space is analogous to BCP space, named after the bond critical point, which compactly and successfully characterizes a chemical bond. The relative positions of the rings in RCP space are determined by the nature of the ring scaffold, such as the heteroatoms within the ring or the number of π-bonds. The summed atomic QCT charges of the five ring atoms revealed five features (number and type of heteroatom, number of π-bonds, substituent and substitution site) that dictate a ring's net charge. Each feature independently contributes toward a ring's net charge. Each substituent has its own distinct and systematic effect on the ring's net charge, irrespective of the ring scaffold. Therefore, this work proves the possibility of designing a ring with specific properties by fine-tuning it through manipulation of these five features.

  6. Predicting Chemical Toxicity from Proteomics and Computational Chemistry

    DTIC Science & Technology

    2008-07-30

    similarity spaces, BD Gute and SC Basak, SAR QSAR Environ. Res., 17, 37-51 (2006). Predicting pharmacological and toxicological activity of heterocyclic...affinity of dibenzofurans: a hierarchical QSAR approach, authored jointly by Basak and Mills; Division of Chemical Toxicology iii. Prediction of blood...biodescriptors vis-ä-vis chemodescriptors in predictive toxicology e) Development of integrated QSTR models using the combined set of chemodescriptors and

  7. Characterization and Prediction of Chemical Functions and ...

    EPA Pesticide Factsheets

    Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents). We combined these functions with weight fraction data for 4115 personal care products (PCPs) to characterize the composition of 66 different product categories (e.g., shampoos). We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR) classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties). We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-b

  8. Artificial Neural Network Prediction of Chemical-Disease Relationships using Readily Available Chemical Properties

    DTIC Science & Technology

    2014-03-27

    C15H13N3O4S Potassium Bromide 0119000100 BrK Potassium Permanganate 0158030400 MnO4K Prazosin 0383410801 C19H21N5O4 Propranolol-HCl 0259350302...chemicals and correctly match it to a single disease category. Potassium permanganate and ethylene glycol can both be correctly linked to disease group...chemical is linked to the same disease, the network is unable to predict the same disease for the multiple chemicals. Potassium permanganate and

  9. EPAs ToxCast Research Program: Developing Predictive Bioactivity Signatures for Chemicals

    EPA Science Inventory

    The international community needs better predictive tools for assessing the hazards and risks of chemicals. It is technically feasible to collect bioactivity data on virtually all chemicals of potential concern ToxCast is providing a proof of concept for obtaining predictive, b...

  10. Towards quantum chemistry on a quantum computer.

    PubMed

    Lanyon, B P; Whitfield, J D; Gillett, G G; Goggin, M E; Almeida, M P; Kassal, I; Biamonte, J D; Mohseni, M; Powell, B J; Barbieri, M; Aspuru-Guzik, A; White, A G

    2010-02-01

    Exact first-principles calculations of molecular properties are currently intractable because their computational cost grows exponentially with both the number of atoms and basis set size. A solution is to move to a radically different model of computing by building a quantum computer, which is a device that uses quantum systems themselves to store and process data. Here we report the application of the latest photonic quantum computer technology to calculate properties of the smallest molecular system: the hydrogen molecule in a minimal basis. We calculate the complete energy spectrum to 20 bits of precision and discuss how the technique can be expanded to solve large-scale chemical problems that lie beyond the reach of modern supercomputers. These results represent an early practical step toward a powerful tool with a broad range of quantum-chemical applications.

  11. Chemical and explosive detections using photo-acoustic effect and quantum cascade lasers

    NASA Astrophysics Data System (ADS)

    Choa, Fow-Sen

    2013-12-01

    Photoacoustic (PA) effect is a sensitive spectroscopic technique for chemical sensing. In recent years, with the development of quantum cascade lasers (QCLs), significant progress has been achieved for PA sensing applications. Using high-power, tunable mid-IR QCLs as laser sources, PA chemical sensor systems have demonstrated parts-pertrillion- level detection sensitivity. Many of these high sensitivity measurements were demonstrated locally in PA cells. Recently, we have demonstrated standoff PA detection of isopropanol vapor for more than 41 feet distance using a quantum cascade laser and a microphone with acoustic reflectors. We also further demonstrated solid phase TNT detections at a standoff distance of 8 feet. To further calibrate the detection sensitivity, we use nerve gas simulants that were generated and calibrated by a commercial vapor generator. Standoff detection of gas samples with calibrated concentration of 2.3 ppm was achieved at a detection distance of more than 2 feet. An extended detection distance up to 14 feet was observed for a higher gas concentration of 13.9 ppm. For field operations, array of microphones and microphone-reflector pairs can be utilized to achieve noise rejection and signal enhancement. We have experimentally demonstrated that the signal and noise spectra of the 4 microphone/4 reflector system with a combined SNR of 12.48 dB. For the 16-microphone and one reflector case, an SNR of 17.82 was achieved. These successful chemical sensing demonstrations will likely create new demands for widely tunable QCLs with ultralow threshold (for local fire-alarm size detection systems) and high-power (for standoff detection systems) performances.

  12. Structural and vibrational spectral investigations of melaminium maleate monohydrate by FTIR, FT-Raman and quantum chemical calculations.

    PubMed

    Arjunan, V; Kalaivani, M; Marchewka, M K; Mohan, S

    2013-04-15

    The structural investigations of the molecular complex of melamine with maleic acid, namely melaminium maleate monohydrate have been carried out by quantum chemical methods in addition to FTIR, FT-Raman and far-infrared spectral studies. The quantum chemical studies were performed with DFT (B3LYP) method using 6-31G(**), cc-pVDZ and 6-311++G(**) basis sets to determine the energy, structural and thermodynamic parameters of melaminium maleate monohydrate. The hydrogen atom from maleic acid was transferred to the melamine molecule giving the singly protonated melaminium cation. The ability of ions to form spontaneous three-dimensional structure through weak OH···O and NH···O hydrogen bonds shows notable vibrational effects. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. Chemical structure-based predictive model for methanogenic anaerobic biodegradation potential.

    PubMed

    Meylan, William; Boethling, Robert; Aronson, Dallas; Howard, Philip; Tunkel, Jay

    2007-09-01

    Many screening-level models exist for predicting aerobic biodegradation potential from chemical structure, but anaerobic biodegradation generally has been ignored by modelers. We used a fragment contribution approach to develop a model for predicting biodegradation potential under methanogenic anaerobic conditions. The new model has 37 fragments (substructures) and classifies a substance as either fast or slow, relative to the potential to be biodegraded in the "serum bottle" anaerobic biodegradation screening test (Organization for Economic Cooperation and Development Guideline 311). The model correctly classified 90, 77, and 91% of the chemicals in the training set (n = 169) and two independent validation sets (n = 35 and 23), respectively. Accuracy of predictions of fast and slow degradation was equal for training-set chemicals, but fast-degradation predictions were less accurate than slow-degradation predictions for the validation sets. Analysis of the signs of the fragment coefficients for this and the other (aerobic) Biowin models suggests that in the context of simple group contribution models, the majority of positive and negative structural influences on ultimate degradation are the same for aerobic and methanogenic anaerobic biodegradation.

  14. Biomimetic, Mild Chemical Synthesis of CdTe-GSH Quantum Dots with Improved Biocompatibility

    PubMed Central

    Pérez-Donoso, José M.; Monrás, Juan P.; Bravo, Denisse; Aguirre, Adam; Quest, Andrew F.; Osorio-Román, Igor O.; Aroca, Ricardo F.; Chasteen, Thomas G.; Vásquez, Claudio C.

    2012-01-01

    Multiple applications of nanotechnology, especially those involving highly fluorescent nanoparticles (NPs) or quantum dots (QDs) have stimulated the research to develop simple, rapid and environmentally friendly protocols for synthesizing NPs exhibiting novel properties and increased biocompatibility. In this study, a simple protocol for the chemical synthesis of glutathione (GSH)-capped CdTe QDs (CdTe-GSH) resembling conditions found in biological systems is described. Using only CdCl2, K2TeO3 and GSH, highly fluorescent QDs were obtained under pH, temperature, buffer and oxygen conditions that allow microorganisms growth. These CdTe-GSH NPs displayed similar size, chemical composition, absorbance and fluorescence spectra and quantum yields as QDs synthesized using more complicated and expensive methods. CdTe QDs were not freely incorporated into eukaryotic cells thus favoring their biocompatibility and potential applications in biomedicine. In addition, NPs entry was facilitated by lipofectamine, resulting in intracellular fluorescence and a slight increase in cell death by necrosis. Toxicity of the as prepared CdTe QDs was lower than that observed with QDs produced by other chemical methods, probably as consequence of decreased levels of Cd+2 and higher amounts of GSH. We present here the simplest, fast and economical method for CdTe QDs synthesis described to date. Also, this biomimetic protocol favors NPs biocompatibility and helps to establish the basis for the development of new, “greener” methods to synthesize cadmium-containing QDs. PMID:22292028

  15. A novel model to predict gas-phase hydroxyl radical oxidation kinetics of polychlorinated compounds.

    PubMed

    Luo, Shuang; Wei, Zongsu; Spinney, Richard; Yang, Zhihui; Chai, Liyuan; Xiao, Ruiyang

    2017-04-01

    In this study, a novel model based on aromatic meta-substituent grouping was presented to predict the second-order rate constants (k) for OH oxidation of PCBs in gas-phase. Since the oxidation kinetics are dependent on the chlorination degree and position, we hypothesized that it may be more accurate for k value prediction if we group PCB congeners based on substitution positions (i.e., ortho (o), meta (m), and para (p)). To test this hypothesis, we examined the correlation of polarizability (α), a quantum chemical based descriptor for k values, with an empirical Hammett constant (σ + ) on each substitution position. Our result shows that α is highly linearly correlated to ∑σ o,m,p + based on aromatic meta-substituents leading to the grouping based predictive model. With the new model, the calculated k values exhibited an excellent agreement with experimental measurements, and greater predictive power than the quantum chemical based quantitative structure activity relationship (QSAR) model. Further, the relationship of α and ∑σ o,m,p + for PCDDs congeners, together with highest occupied molecular orbital (HOMO) distribution, were used to validate the aromatic meta-substituent grouping method. This newly developed model features a combination of good predictability of quantum chemical based QSAR model and simplicity of Hammett relationship, showing a great potential for fast and computational tractable prediction of k values for gas-phase OH oxidation of polychlorinated compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Incorporation of Mn2+ into CdSe quantum dots by chemical bath co-deposition method for photovoltaic enhancement of quantum dot-sensitized solar cells

    NASA Astrophysics Data System (ADS)

    Zhang, Chenguang; Liu, Shaowen; Liu, Xingwei; Deng, Fei; Xiong, Yan; Tsai, Fang-Chang

    2018-03-01

    A photoelectric conversion efficiency (PCE) of 4.9% was obtained under 100 mW cm-2 illumination by quantum-dot-sensitized solar cells (QDSSCs) using a CdS/Mn : CdSe sensitizer. CdS quantum dots (QDs) were deposited on a TiO2 mesoporous oxide film by successive ionic layer absorption and reaction. Mn2+ doping into CdSe QDs is an innovative and simple method-chemical bath co-deposition, that is, mixing the Mn ion source with CdSe precursor solution for Mn : CdSe QD deposition. Compared with the CdS/CdSe sensitizer without Mn2+ incorporation, the PCE was increased from 3.4% to 4.9%. The effects of Mn2+ doping on the chemical, physical and photovoltaic properties of the QDSSCs were investigated by energy dispersive spectrometry, absorption spectroscopy, photocurrent density-voltage characteristics and electrochemical impedance spectroscopy. Mn-doped CdSe QDs in QDSSCs can obtain superior light absorption, faster electron transport and slower charge recombination than CdSe QDs.

  17. Application of high level wavefunction methods in quantum mechanics/molecular mechanics hybrid schemes.

    PubMed

    Mata, Ricardo A

    2010-05-21

    In this Perspective, several developments in the field of quantum mechanics/molecular mechanics (QM/MM) approaches are reviewed. Emphasis is placed on the use of correlated wavefunction theory and new state of the art methods for the treatment of large quantum systems. Until recently, computational chemistry approaches to large/complex chemical problems have seldom been considered as tools for quantitative predictions. However, due to the tremendous development of computational resources and new quantum chemical methods, it is nowadays possible to describe the electronic structure of biomolecules at levels of theory which a decade ago were only possible for system sizes of up to 20 atoms. These advances are here outlined in the context of QM/MM. The article concludes with a short outlook on upcoming developments and possible bottlenecks for future applications.

  18. Integrating Biological and Chemical Data for Hepatotoxicity Prediction (SOT)

    EPA Science Inventory

    The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. A set of 677 chemicals were represented by 711 bioactivity descriptors (from ToxCast assays),...

  19. Empirical, thermodynamic and quantum-chemical investigations of inclusion complexation between flavanones and (2-hydroxypropyl)-cyclodextrins.

    PubMed

    Liu, Benguo; Li, Wei; Nguyen, Tien An; Zhao, Jian

    2012-09-15

    The inclusion complexation of (2-hydroxypropyl)-cyclodextrins with flavanones was investigated by phase solubility measurements, as well as thermodynamic and quantum chemical methods. Inclusion complexes were formed between (2-hydroxypropyl)-α-cyclodextrin (HP-α-CD), (2-hydroxypropyl)-β-cyclodextrin (HP-β-CD), (2-hydroxypropyl)-γ-cyclodextrin (HP-γ-CD) and β-cyclodextrin (β-CD) and four flavanones (naringenin, naringin, hesperetin and dihydromyricetin) in aqueous solutions and their phase solubility was determined. For all the flavanones, the stability constants of their complexes formed with different CDs followed the rank order: HP-β-CD (MW 1540)>HP-β-CD (MW 1460)>HP-β-CD (MW 1380)>β-CD>HP-γ-CD>HP-α-CD. Experimental results and quantum chemical calculations showed that the ability of flavanones to form inclusion complex with (2-hydroxypropyl)-cyclodextrins was determined by both the steric effect and hydrophobicity of the flavanones. For flavanones that have similar molecular volumes, the hydrophobicity of the molecule was the main determining factor of its ability to form inclusion complexes with HP-β-CD, and the hydrophobicity parameter Log P is highly correlated with the stability constant of the complexes. Results of thermodynamic study demonstrated that hydrophobic interaction is the main driving force for the formation process of the flavanone-CD inclusion complexes. Quantum chemical analysis of the most active hydroxyl groups and HOMO (the highest occupied molecular orbital) showed that the B ring of the flavanones was most likely involved in hydrogen bonding with the side groups in the cavity of the CDs, through which the inclusion complex was stabilised. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. Development of estrogen receptor beta binding prediction model using large sets of chemicals.

    PubMed

    Sakkiah, Sugunadevi; Selvaraj, Chandrabose; Gong, Ping; Zhang, Chaoyang; Tong, Weida; Hong, Huixiao

    2017-11-03

    We developed an ER β binding prediction model to facilitate identification of chemicals specifically bind ER β or ER α together with our previously developed ER α binding model. Decision Forest was used to train ER β binding prediction model based on a large set of compounds obtained from EADB. Model performance was estimated through 1000 iterations of 5-fold cross validations. Prediction confidence was analyzed using predictions from the cross validations. Informative chemical features for ER β binding were identified through analysis of the frequency data of chemical descriptors used in the models in the 5-fold cross validations. 1000 permutations were conducted to assess the chance correlation. The average accuracy of 5-fold cross validations was 93.14% with a standard deviation of 0.64%. Prediction confidence analysis indicated that the higher the prediction confidence the more accurate the predictions. Permutation testing results revealed that the prediction model is unlikely generated by chance. Eighteen informative descriptors were identified to be important to ER β binding prediction. Application of the prediction model to the data from ToxCast project yielded very high sensitivity of 90-92%. Our results demonstrated ER β binding of chemicals could be accurately predicted using the developed model. Coupling with our previously developed ER α prediction model, this model could be expected to facilitate drug development through identification of chemicals that specifically bind ER β or ER α .

  1. Quantum chemical modeling of the inhibition mechanism of monoamine oxidase by oxazolidinone and analogous heterocyclic compounds.

    PubMed

    Erdem, Safiye Sağ; Özpınar, Gül Altınbaş; Boz, Ümüt

    2014-02-01

    Monoamine oxidase (MAO, EC 1.4.3.4) is responsible from the oxidation of a variety of amine neurotransmitters. MAO inhibitors are used for the treatment of depression or Parkinson's disease. They also inhibit the catabolism of dietary amines. According to one hypothesis, inactivation results from the formation of a covalent adduct to a cysteine residue in the enzyme. If the adduct is stable enough, the enzyme is inhibited for a long time. After a while, enzyme can turn to its active form as a result of adduct breakdown by β-elimination. In this study, the proposed inactivation mechanism was modeled and tested by quantum chemical calculations. Eight heterocyclic methylthioamine derivatives were selected to represent the proposed covalent adducts. Activation energies related to their β-elimination reactions were calculated using ab initio and density functional theory methods. Calculated activation energies were in good agreement with the relative stabilities of the hypothetical adducts predicted in the literature by enzyme inactivation measurements.

  2. Quantum Dot and Polymer Composite Cross-Reactive Array for Chemical Vapor Detection.

    PubMed

    Bright, Collin J; Nallon, Eric C; Polcha, Michael P; Schnee, Vincent P

    2015-12-15

    A cross-reactive chemical sensing array was made from CdSe Quantum Dots (QDs) and five different organic polymers by inkjet printing to create segmented fluorescent composite regions on quartz substrates. The sensor array was challenged with exposures from two sets of analytes, including one set of 14 different functionalized benzenes and one set of 14 compounds related to security concerns, including the explosives trinitrotoluene (TNT) and ammonium nitrate. The array was broadly responsive to analytes with different chemical functionalities due to the multiple sensing mechanisms that altered the QDs' fluorescence. The sensor array displayed excellent discrimination between members within both sets. Classification accuracy of more than 93% was achieved, including the complete discrimination of very similar dinitrobenzene isomers and three halogenated, substituted benzene compounds. The simple fabrication, broad responsivity, and high discrimination capacity of this type of cross-reactive array are ideal qualities for the development of sensors with excellent sensitivity to chemical and explosive threats while maintaining low false alarm rates.

  3. SeqAPASS: Predicting chemical susceptibility to threatened/endangered species

    EPA Science Inventory

    Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS; https://seqapass.epa.gov/seqapass/) application was devel...

  4. THE FUTURE OF TOXICOLOGY-PREDICTIVE TOXICOLOGY: AN EXPANDED VIEW OF CHEMICAL TOXICITY

    EPA Science Inventory

    A chemistry approach to predictive toxicology relies on structure−activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. T...

  5. Estimating system parameters for solvent-water and plant cuticle-water using quantum chemically estimated Abraham solute parameters.

    PubMed

    Liang, Yuzhen; Torralba-Sanchez, Tifany L; Di Toro, Dominic M

    2018-04-18

    Polyparameter Linear Free Energy Relationships (pp-LFERs) using Abraham system parameters have many useful applications. However, developing the Abraham system parameters depends on the availability and quality of the Abraham solute parameters. Using Quantum Chemically estimated Abraham solute Parameters (QCAP) is shown to produce pp-LFERs that have lower root mean square errors (RMSEs) of predictions for solvent-water partition coefficients than parameters that are estimated using other presently available methods. pp-LFERs system parameters are estimated for solvent-water, plant cuticle-water systems, and for novel compounds using QCAP solute parameters and experimental partition coefficients. Refitting the system parameter improves the calculation accuracy and eliminates the bias. Refitted models for solvent-water partition coefficients using QCAP solute parameters give better results (RMSE = 0.278 to 0.506 log units for 24 systems) than those based on ABSOLV (0.326 to 0.618) and QSPR (0.294 to 0.700) solute parameters. For munition constituents and munition-like compounds not included in the calibration of the refitted model, QCAP solute parameters produce pp-LFER models with much lower RMSEs for solvent-water partition coefficients (RMSE = 0.734 and 0.664 for original and refitted model, respectively) than ABSOLV (4.46 and 5.98) and QSPR (2.838 and 2.723). Refitting plant cuticle-water pp-LFER including munition constituents using QCAP solute parameters also results in lower RMSE (RMSE = 0.386) than that using ABSOLV (0.778) and QSPR (0.512) solute parameters. Therefore, for fitting a model in situations for which experimental data exist and system parameters can be re-estimated, or for which system parameters do not exist and need to be developed, QCAP is the quantum chemical method of choice.

  6. PREDICTING THE EFFECTIVENESS OF CHEMICAL-PROTECTIVE CLOTHING MODEL AND TEST METHOD DEVELOPMENT

    EPA Science Inventory

    A predictive model and test method were developed for determining the chemical resistance of protective polymeric gloves exposed to liquid organic chemicals. The prediction of permeation through protective gloves by solvents was based on theories of the solution thermodynamics of...

  7. Quantum-chemical calculations and electron diffraction study of the equilibrium molecular structure of vitamin K3

    NASA Astrophysics Data System (ADS)

    Khaikin, L. S.; Tikhonov, D. S.; Grikina, O. E.; Rykov, A. N.; Stepanov, N. F.

    2014-05-01

    The equilibrium molecular structure of 2-methyl-1,4-naphthoquinone (vitamin K3) having C s symmetry is experimentally characterized for the first time by means of gas-phase electron diffraction using quantum-chemical calculations and data on the vibrational spectra of related compounds.

  8. Prediction of Spin-Polarization Effects in Quantum Wire Transport

    NASA Astrophysics Data System (ADS)

    Fasol, Gerhard; Sakaki, Hiroyuki

    1994-01-01

    We predict a new effect for transport in quantum wires: spontaneous spin polarization. Most work on transport in mesoscopic devices has assumed a model of non interacting, spin-free electrons. We introduce spin, electron pair scattering and microscopic crystal properties into the design of mesoscopic devices. The new spin polarization effect results from the fact that in a single mode quantum wire, electron and hole bands still have two spin subbands. In general, these two spin subbands are expected to be split even in zero magnetic field. At sufficiently low temperatures the electron pair scattering rates for one spin subband ( e.g., the spin-down) can be much larger than for the other spin subband. This effect can be used for an active spin polarizer device: hot electrons in one subband ( e.g., `spin up') pass with weak pair scattering, while electrons in the opposite subband ( e.g., `spin down'), have high probability of scattering into the `spin-up' subband, resulting in spin polarization of a hot electron beam.

  9. Chemical potentials and thermodynamic characteristics of ideal Bose- and Fermi-gases in the region of quantum degeneracy

    NASA Astrophysics Data System (ADS)

    Sotnikov, A. G.; Sereda, K. V.; Slyusarenko, Yu. V.

    2017-01-01

    Calculations of chemical potentials for ideal monatomic gases with Bose-Einstein and Fermi-Dirac statistics as functions of temperature, across the temperature region that is typical for the collective quantum degeneracy effect, are presented. Numerical calculations are performed without any additional approximations, and explicit dependences of the chemical potentials on temperature are constructed at a fixed density of gas particles. Approximate polynomial dependences of chemical potentials on temperature are obtained that allow for the results to be used in further studies without re-applying the involved numerical methods. The ease of using the obtained representations is demonstrated on examples of deformation of distribution for a population of energy states at low temperatures, and on the impact of quantum statistics (exchange interaction) on the equations of state for ideal gases and some of the thermodynamic properties thereof. The results of this study essentially unify two opposite limiting cases in an intermediate region that are used to describe the equilibrium states of ideal gases, which are well known from university courses on statistical physics, thus adding value from an educational point of view.

  10. Quantum cascade transmitters for ultrasensitive chemical agent and explosives detection

    NASA Astrophysics Data System (ADS)

    Schultz, John F.; Taubman, Matthew S.; Harper, Warren W.; Williams, Richard M.; Myers, Tanya L.; Cannon, Bret D.; Sheen, David M.; Anheier, Norman C., Jr.; Allen, Paul J.; Sundaram, S. K.; Johnson, Bradley R.; Aker, Pamela M.; Wu, Ming C.; Lau, Erwin K.

    2003-07-01

    The small size, high power, promise of access to any wavelength between 3.5 and 16 microns, substantial tuning range about a chosen center wavelength, and general robustness of quantum cascade (QC) lasers provide opportunities for new approaches to ultra-sensitive chemical detection and other applications in the mid-wave infrared. PNNL is developing novel remote and sampling chemical sensing systems based on QC lasers, using QC lasers loaned by Lucent Technologies. In recent months laboratory cavity-enhanced sensing experiments have achieved absorption sensitivities of 8.5 x 10-11 cm-1 Hz-1/2, and the PNNL team has begun monostatic and bi-static frequency modulated, differential absorption lidar (FM DIAL) experiments at ranges of up to 2.5 kilometers. In related work, PNNL and UCLA are developing miniature QC laser transmitters with the multiplexed tunable wavelengths, frequency and amplitude stability, modulation characteristics, and power levels needed for chemical sensing and other applications. Current miniaturization concepts envision coupling QC oscillators, QC amplifiers, frequency references, and detectors with miniature waveguides and waveguide-based modulators, isolators, and other devices formed from chalcogenide or other types of glass. Significant progress has been made on QC laser stabilization and amplification, and on development and characterization of high-purity chalcogenide glasses, waveguide writing techniques, and waveguide metrology.

  11. Prediction of chemical speciation in stabilized/solidified wastes using a general chemical equilibrium model. Part 1: Chemical representation of cementitious binders

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Park, J.Y.; Batchelor, B.

    1999-03-01

    Chemical equilibrium models are useful to evaluate stabilized/solidified waste. A general equilibrium model, SOLTEQ, a modified version of MINTEQA2 for S/S, was applied to predict the chemical speciations in the stabilized/solidified waste form. A method was developed to prepare SOLTEQ input data that can chemically represent various stabilized/solidified binders. Taylor`s empirical model was used to describe partitioning of alkali ions. As a result, SOLTEQ could represent chemical speciation in pure binder systems such as ordinary Portland cement and ordinary Portland cement + fly ash. Moreover, SOLTEQ could reasonably describe the effects on the chemical speciation due to variations in water-to-cement,more » fly ash contents, and hydration times of various binder systems. However, this application of SOLTEQ was not accurate in predicting concentrations of Ca, Si, and SO{sub 4} ions, due to uncertainties in the CSH solubility model and K{sub sp} values of cement hydrates at high pH values.« less

  12. Characterization and intramolecular bonding patterns of busulfan: Experimental and quantum chemical approach

    NASA Astrophysics Data System (ADS)

    Karthick, T.; Tandon, Poonam; Singh, Swapnil; Agarwal, Parag; Srivastava, Anubha

    2017-02-01

    The investigations of structural conformers, molecular interactions and vibrational characterization of pharmaceutical drug are helpful to understand their behaviour. In the present work, the 2D potential energy surface (PES) scan has been performed on the dihedral angles C6sbnd O4sbnd S1sbnd C5 and C25sbnd S22sbnd O19sbnd C16 to find the stable conformers of busulfan. In order to show the effects of long range interactions, the structures on the global minima of PES scan have been further optimized by B3LYP/6-311 ++G(d,p) method with and without empirical dispersion functional in Gaussian 09W package. The presence of n → σ* and σ → σ* interactions which lead to stability of the molecule have been predicted by natural bond orbital analysis. The strong and weak hydrogen bonds between the functional groups of busulfan were analyzed using quantum topological atoms in molecules analysis. In order to study the long-range forces, such as van der Waals interactions, steric effect in busulfan, the reduced density gradient as well as isosurface defining these interactions has been plotted using Multiwfn software. The spectroscopic characterization on the solid phase of busulfan has been studied by experimental FT-IR and FT-Raman spectra. From the 13C and 1H NMR spectra, the chemical shifts of individual C and H atoms of busulfan have been predicted. The maximum absorption wavelengths corresponding to the electronic transitions between the highest occupied molecular orbital and the lowest unoccupied molecular orbital of busulfan have been found by UV-vis spectrum.

  13. Quantum Chemical and Docking Insights into Bioavailability Enhancement of Curcumin by Piperine in Pepper.

    PubMed

    Patil, Vaishali M; Das, Sukanya; Balasubramanian, Krishnan

    2016-05-26

    We combine quantum chemical and molecular docking techniques to provide new insights into how piperine molecule in various forms of pepper enhances bioavailability of a number of drugs including curcumin in turmeric for which it increases its bioavailability by a 20-fold. We have carried out docking studies of quantum chemically optimized piperine structure binding to curcumin, CYP3A4 in cytochrome P450, p-Glycoprotein and UDP-glucuronosyltransferase (UGT), the enzyme responsible for glucuronosylation, which increases the solubility of curcumin. All of these studies establish that piperine binds to multiple sites on the enzymes and also intercalates with curcumin forming a hydrogen bonded complex with curcumin. The conjugated network of double bonds and the presence of multiple charge centers of piperine offer optimal binding sites for piperine to bind to enzymes such as UDP-GDH, UGT, and CYP3A4. Piperine competes for curcumin's intermolecular hydrogen bonding and its stacking propensity by hydrogen bonding with enolic proton of curcumin. This facilitates its metabolic transport, thereby increasing its bioavailability both through intercalation into curcumin layers through intermolecular hydrogen bonding, and by inhibiting enzymes that cause glucuronosylation of curcumin.

  14. Remote Chemical Sensing Using Quantum Cascade Lasers

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Harper, Warren W.; Schultz, John F.

    2003-01-30

    Spectroscopic chemical sensing research at Pacific Northwest National Laboratory (PNNL) is focused on developing advanced sensors for detecting the production of nuclear, chemical, or biological weapons; use of chemical weapons; or the presence of explosives, firearms, narcotics, or other contraband of significance to homeland security in airports, cargo terminals, public buildings, or other sensitive locations. For most of these missions, the signature chemicals are expected to occur in very low concentrations, and in mixture with ambient air or airborne waste streams that contain large numbers of other species that may interfere with spectroscopic detection, or be mistaken for signatures ofmore » illicit activity. PNNL’s emphasis is therefore on developing remote and sampling sensors with extreme sensitivity, and resistance to interferents, or selectivity. PNNL’s research activities include: 1. Identification of signature chemicals and quantification of their spectral characteristics, 2. Identification and development of laser and other technologies that enable breakthroughs in sensitivity and selectivity, 3. Development of promising sensing techniques through experimentation and modeling the physical phenomenology and practical engineering limitations affecting their performance, and 4. Development and testing of data collection methods and analysis algorithms. Close coordination of all aspects of the research is important to ensure that all parts are focused on productive avenues of investigation. Close coordination of experimental development and numerical modeling is particularly important because the theoretical component provides understanding and predictive capability, while the experiments validate calculations and ensure that all phenomena and engineering limitations are considered.« less

  15. Predicting hepatotoxicity using ToxCast in vitro bioactivity and chemical structure

    EPA Science Inventory

    Background: The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. We represented chemicals based on bioactivity and chemical structure descriptors ...

  16. An investigation into the effective surface passivation of quantum dots by a photo-assisted chemical method

    NASA Astrophysics Data System (ADS)

    Joo, So-Yeong; Park, Hyun-Su; Kim, Do-yeon; Kim, Bum-Sung; Lee, Chan Gi; Kim, Woo-Byoung

    2018-01-01

    In this study, we have developed an effective amino passivation process for quantum dots (QDs) at room temperature and have investigated a passivation mechanism using a photo-assisted chemical method. As a result of the reverse reaction of the H2O molecules, the etching kinetics of the photo-assisted chemical method increased upon increasing the 3-amino-1-propanol (APOL)/H2O ratio of the etching solution. Photon-excited electron-hole pairs lead to strong bonding between the organic and surface atoms of the QDs, and results in an increase of the quantum yield (QY%). This passivation method is also applicable to CdSe/ZnSe core/shell structures of QDs, due to the passivation of mid-gap defects states at the interface. The QY% of the as-synthesized CdSe QDs is dramatically enhanced by the amino passivation from 37% to 75% and the QY% of the CdSe/ZnSe core/shell QDs is also improved by ˜28%.

  17. Quantum mechanical model for the anticarcinogenic effect of extremely-low-frequency electromagnetic fields on early chemical hepatocarcinogenesis

    NASA Astrophysics Data System (ADS)

    Godina-Nava, Juan José; Torres-Vega, Gabino; López-Riquelme, Germán Octavio; López-Sandoval, Eduardo; Samana, Arturo Rodolfo; García Velasco, Fermín; Hernández-Aguilar, Claudia; Domínguez-Pacheco, Arturo

    2017-02-01

    Using the conventional Haberkorn approach, it is evaluated the recombination of the radical pair (RP) singlet spin state to study theoretically the cytoprotective effect of an extremely-low-frequency electromagnetic field (ELF-EMF) on early stages of hepatic cancer chemically induced in rats. The proposal is that ELF-EMF modulates the interconversion rate of singlet and triplet spin states of the RP populations modifying the products from the metabolization of carcinogens. Previously, we found that the daily treatment with ELF-EMF 120 Hz inhibited the number and area of preneoplastic lesions in chemical carcinogenesis. The singlet spin population is evaluated diagonalizing the spin density matrix through the Lanczos method in a radical pair mechanism (RPM). Using four values of the interchange energy, we have studied the variations over the singlet population. The low magnetic field effect as a test of the influence over the enzymatic chemical reaction is evaluated calculating the quantum yield. Through a bootstrap technique the range is found for the singlet decay rate for the process. Applying the quantum measurements concept, we addressed the impact toward hepatic cells. The result contributes to improving our understanding of the chemical carcinogenesis process affected by charged particles that damage the DNA.

  18. Three isomers detected for the whisky lactone: 5-butyl-4-methyl tetrahydrofuran-2-one by Fourier transform microwave spectroscopy and quantum chemical calculations

    NASA Astrophysics Data System (ADS)

    Kawashima, Yoshiyuki; Katsuragi, Ryusuke; Hirota, Eizi

    2017-05-01

    The ground-state rotational spectra of the whisky lactone (WL) : 5-butyl-4-methyl tetrahydrofuran-2-one were observed and analyzed by molecular beam Fourier transform microwave spectroscopy combined with quantum chemical calculations. We have detected three stereo-isomers: the trans-TTT form with a methyl CH3 group attached to C(4) in an equatorial position (eq) and a butyl C4H9 group to C(5) in an eq position, for which 110 b-type and 113 a-type transitions were assigned, the cis-TTT form with a CH3 to C(4) in an axial position (ax) and a C4H9 to C(5) in eq, for which 96 a-type, 101 b-type, and 45 c-type transitions were observed, and the cis-GTT form with a CH3 to C(4) in ax and a C4H9 to C(5) in eq, for which 158 a-type, 52 b-type, and 17 c-type transitions were observed, where TTT and GTT denote the conformations about the C(6)sbnd C(5), C(7)sbnd C(6), and C(8)sbnd C(7) bonds, with T and G designating trans and gauche, respectively. The rotational constants thus derived agree with the predictions made by quantum chemical calculations, MP2/6-311++G(d, p) within 1.2%. The trans-TTT form was calculated to be the most stable. The splittings due to internal rotation of the terminal methyl in the butyl group were observed for all the three stereo-isomers and were analyzed by the XIAM program to determine the threefold potential barrier V3 to be 966.4 (25), 978.8 (11), and 1098.7 (48) in cm-1 for the trans-TTT (eq, eq), the cis-TTT (ax, eq), and the cis-GTT (ax, eq) forms, respectively, to be compared with quantum chemically calculated values: 1055, 1055, and 1053 in cm-1.

  19. Quantum chemical modeling of zeolite-catalyzed methylation reactions: toward chemical accuracy for barriers.

    PubMed

    Svelle, Stian; Tuma, Christian; Rozanska, Xavier; Kerber, Torsten; Sauer, Joachim

    2009-01-21

    The methylation of ethene, propene, and t-2-butene by methanol over the acidic microporous H-ZSM-5 catalyst has been investigated by a range of computational methods. Density functional theory (DFT) with periodic boundary conditions (PBE functional) fails to describe the experimentally determined decrease of apparent energy barriers with the alkene size due to inadequate description of dispersion forces. Adding a damped dispersion term expressed as a parametrized sum over atom pair C(6) contributions leads to uniformly underestimated barriers due to self-interaction errors. A hybrid MP2:DFT scheme is presented that combines MP2 energy calculations on a series of cluster models of increasing size with periodic DFT calculations, which allows extrapolation to the periodic MP2 limit. Additionally, errors caused by the use of finite basis sets, contributions of higher order correlation effects, zero-point vibrational energy, and thermal contributions to the enthalpy were evaluated and added to the "periodic" MP2 estimate. This multistep approach leads to enthalpy barriers at 623 K of 104, 77, and 48 kJ/mol for ethene, propene, and t-2-butene, respectively, which deviate from the experimentally measured values by 0, +13, and +8 kJ/mol. Hence, enthalpy barriers can be calculated with near chemical accuracy, which constitutes significant progress in the quantum chemical modeling of reactions in heterogeneous catalysis in general and microporous zeolites in particular.

  20. Quantum Chemical Modeling of Enzymatic Reactions: The Case of Decarboxylation.

    PubMed

    Liao, Rong-Zhen; Yu, Jian-Guo; Himo, Fahmi

    2011-05-10

    We present a systematic study of the decarboxylation step of the enzyme aspartate decarboxylase with the purpose of assessing the quantum chemical cluster approach for modeling this important class of decarboxylase enzymes. Active site models ranging in size from 27 to 220 atoms are designed, and the barrier and reaction energy of this step are evaluated. To model the enzyme surrounding, homogeneous polarizable medium techniques are used with several dielectric constants. The main conclusion is that when the active site model reaches a certain size, the solvation effects from the surroundings saturate. Similar results have previously been obtained from systematic studies of other classes of enzymes, suggesting that they are of a quite general nature.

  1. Graphene-based quantum Hall resistance standards grown by chemical vapor deposition on silicon carbide

    NASA Astrophysics Data System (ADS)

    Ribeiro-Palau, Rebeca; Lafont, Fabien; Kazazis, Dimitris; Michon, Adrien; Couturaud, Olivier; Consejo, Christophe; Jouault, Benoit; Poirier, Wilfrid; Schopfer, Felicien

    2015-03-01

    Replace GaAs-based quantum Hall resistance standards (GaAs-QHRS) by a more convenient one, based on graphene (Gr-QHRS), is an ongoing goal in metrology. The new Gr-QHRS are expected to work in less demanding experimental conditions than GaAs ones. It will open the way to a broad dissemination of quantum standards, potentially towards industrial end-users, and it will support the implementation of a new International System of Units based on fixed fundamental constants. Here, we present accurate quantum Hall resistance measurements in large graphene Hall bars, grown by the hybrid scalable technique of propane/hydrogen chemical vapor deposition (CVD) on silicon carbide (SiC). This new Gr-QHRS shows a relative accuracy of 1 ×10-9 of the Hall resistance under the lowest magnetic field ever achieved in graphene. These experimental conditions surpass those of the most wildely used GaAs-QHRS. These results confirm the promises of graphene for resistance metrology applications and emphasizes the quality of the graphene produced by the CVD on SiC for applications as demanding as the resistance metrology.

  2. MODELING A MIXTURE: PBPK/PD APPROACHES FOR PREDICTING CHEMICAL INTERACTIONS.

    EPA Science Inventory

    Since environmental chemical exposures generally involve multiple chemicals, there are both regulatory and scientific drivers to develop methods to predict outcomes of these exposures. Even using efficient statistical and experimental designs, it is not possible to test in vivo a...

  3. Incorporation of Mn2+ into CdSe quantum dots by chemical bath co-deposition method for photovoltaic enhancement of quantum dot-sensitized solar cells.

    PubMed

    Zhang, Chenguang; Liu, Shaowen; Liu, Xingwei; Deng, Fei; Xiong, Yan; Tsai, Fang-Chang

    2018-03-01

    A photoelectric conversion efficiency (PCE) of 4.9% was obtained under 100 mW cm -2 illumination by quantum-dot-sensitized solar cells (QDSSCs) using a CdS/Mn : CdSe sensitizer. CdS quantum dots (QDs) were deposited on a TiO 2 mesoporous oxide film by successive ionic layer absorption and reaction. Mn 2+ doping into CdSe QDs is an innovative and simple method-chemical bath co-deposition, that is, mixing the Mn ion source with CdSe precursor solution for Mn : CdSe QD deposition. Compared with the CdS/CdSe sensitizer without Mn 2+ incorporation, the PCE was increased from 3.4% to 4.9%. The effects of Mn 2+ doping on the chemical, physical and photovoltaic properties of the QDSSCs were investigated by energy dispersive spectrometry, absorption spectroscopy, photocurrent density-voltage characteristics and electrochemical impedance spectroscopy. Mn-doped CdSe QDs in QDSSCs can obtain superior light absorption, faster electron transport and slower charge recombination than CdSe QDs.

  4. Incorporation of Mn2+ into CdSe quantum dots by chemical bath co-deposition method for photovoltaic enhancement of quantum dot-sensitized solar cells

    PubMed Central

    Zhang, Chenguang; Liu, Shaowen; Liu, Xingwei; Deng, Fei

    2018-01-01

    A photoelectric conversion efficiency (PCE) of 4.9% was obtained under 100 mW cm−2 illumination by quantum-dot-sensitized solar cells (QDSSCs) using a CdS/Mn : CdSe sensitizer. CdS quantum dots (QDs) were deposited on a TiO2 mesoporous oxide film by successive ionic layer absorption and reaction. Mn2+ doping into CdSe QDs is an innovative and simple method—chemical bath co-deposition, that is, mixing the Mn ion source with CdSe precursor solution for Mn : CdSe QD deposition. Compared with the CdS/CdSe sensitizer without Mn2+ incorporation, the PCE was increased from 3.4% to 4.9%. The effects of Mn2+ doping on the chemical, physical and photovoltaic properties of the QDSSCs were investigated by energy dispersive spectrometry, absorption spectroscopy, photocurrent density–voltage characteristics and electrochemical impedance spectroscopy. Mn-doped CdSe QDs in QDSSCs can obtain superior light absorption, faster electron transport and slower charge recombination than CdSe QDs. PMID:29657776

  5. Predicting the bioconcentration factor of highly hydrophobic organic chemicals.

    PubMed

    Garg, Rajni; Smith, Carr J

    2014-07-01

    Bioconcentration refers to the process of uptake and buildup of chemicals in living organisms. Experimental measurement of bioconcentration factor (BCF) is time-consuming and expensive, and is not feasible for a large number of chemicals of regulatory concern. Quantitative structure-activity relationship (QSAR) models are used for estimating BCF values to help in risk assessment of a chemical. This paper presents the results of a QSAR study conducted to address an important problem encountered in the prediction of the BCF of highly hydrophobic chemicals. A new QSAR model is derived using a dataset of diverse organic chemicals previously tested in a United States Environmental Protection Agency laboratory. It is noted that the linear relationship between the BCF and hydrophobic parameter, i.e., calculated octanol-water partition coefficient (ClogP), breaks down for highly hydrophobic chemicals. The parabolic QSAR equation, log BCF=3.036 ClogP-0.197 ClogP(2)-0.808 MgVol (n=28, r(2)=0.817, q(2)=0.761, s=0.558) (experimental log BCF range=0.44-5.29, ClogP range=3.16-11.27), suggests that a non-linear relationship between BCF and the hydrophobic parameter, along with inclusion of additional molecular size, weight and/or volume parameters, should be considered while developing a QSAR model for more reliable prediction of the BCF of highly hydrophobic chemicals. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  6. Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

    PubMed

    Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

    2017-09-21

    Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

  7. Quantum predictions for an unmeasured system cannot be simulated with a finite-memory classical system

    NASA Astrophysics Data System (ADS)

    Tavakoli, Armin; Cabello, Adán

    2018-03-01

    We consider an ideal experiment in which unlimited nonprojective quantum measurements are sequentially performed on a system that is initially entangled with a distant one. At each step of the sequence, the measurements are randomly chosen between two. However, regardless of which measurement is chosen or which outcome is obtained, the quantum state of the pair always remains entangled. We show that the classical simulation of the reduced state of the distant system requires not only unlimited rounds of communication, but also that the distant system has infinite memory. Otherwise, a thermodynamical argument predicts heating at a distance. Our proposal can be used for experimentally ruling out nonlocal finite-memory classical models of quantum theory.

  8. Predicting soil formation on the basis of transport-limited chemical weathering

    NASA Astrophysics Data System (ADS)

    Yu, Fang; Hunt, Allen Gerhard

    2018-01-01

    Soil production is closely related to chemical weathering. It has been shown that, under the assumption that chemical weathering is limited by solute transport, the process of soil production is predictable. However, solute transport in soil cannot be described by Gaussian transport. In this paper, we propose an approach based on percolation theory describing non-Gaussian transport of solute to predict soil formation (the net production of soil) by considering both soil production from chemical weathering and removal of soil from erosion. Our prediction shows agreement with observed soil depths in the field. Theoretical soil formation rates are also compared with published rates predicted using soil age-profile thickness (SAST) method. Our formulation can be incorporated directly into landscape evolution models on a point-to-point basis as long as such models account for surface water routing associated with overland flow. Further, our treatment can be scaled-up to address complications associated with continental-scale applications, including those from climate change, such as changes in vegetation, or surface flow organization. The ability to predict soil formation rates has implications for understanding Earth's climate system on account of the relationship to chemical weathering of silicate minerals with the associated drawdown of atmospheric carbon, but it is also important in geomorphology for understanding landscape evolution, including for example, the shapes of hillslopes, and the net transport of sediments to sedimentary basins.

  9. QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes.

    PubMed

    Basant, Nikita; Gupta, Shikha

    2017-06-01

    The safety assessment process of chemicals requires information on their mutagenic potential. The experimental determination of mutagenicity of a large number of chemicals is tedious and time and cost intensive, thus compelling for alternative methods. We have established local and global QSAR models for discriminating low and high mutagenic compounds and predicting their mutagenic activity in a quantitative manner in Salmonella typhimurium (TA) bacterial strains (TA98 and TA100). The decision treeboost (DTB)-based classification QSAR models discriminated among two categories with accuracies of >96% and the regression QSAR models precisely predicted the mutagenic activity of diverse chemicals yielding high correlations (R 2 ) between the experimental and model-predicted values in the respective training (>0.96) and test (>0.94) sets. The test set root mean squared error (RMSE) and mean absolute error (MAE) values emphasized the usefulness of the developed models for predicting new compounds. Relevant structural features of diverse chemicals that were responsible and influence the mutagenic activity were identified. The applicability domains of the developed models were defined. The developed models can be used as tools for screening new chemicals for their mutagenicity assessment for regulatory purpose.

  10. Modelling Chemical Reasoning to Predict and Invent Reactions.

    PubMed

    Segler, Marwin H S; Waller, Mark P

    2017-05-02

    The ability to reason beyond established knowledge allows organic chemists to solve synthetic problems and invent novel transformations. Herein, we propose a model that mimics chemical reasoning, and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180 000 randomly selected binary reactions. The data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-)discovering novel transformations (even including transition metal-catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph and because each single reaction prediction is typically achieved in a sub-second time frame, the model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Prediction of Chemical Function: Model Development and Application

    EPA Science Inventory

    The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (...

  12. Universality of quantum gravity corrections.

    PubMed

    Das, Saurya; Vagenas, Elias C

    2008-11-28

    We show that the existence of a minimum measurable length and the related generalized uncertainty principle (GUP), predicted by theories of quantum gravity, influence all quantum Hamiltonians. Thus, they predict quantum gravity corrections to various quantum phenomena. We compute such corrections to the Lamb shift, the Landau levels, and the tunneling current in a scanning tunneling microscope. We show that these corrections can be interpreted in two ways: (a) either that they are exceedingly small, beyond the reach of current experiments, or (b) that they predict upper bounds on the quantum gravity parameter in the GUP, compatible with experiments at the electroweak scale. Thus, more accurate measurements in the future should either be able to test these predictions, or further tighten the above bounds and predict an intermediate length scale between the electroweak and the Planck scale.

  13. Experimental and quantum-chemical studies on the three-particle fragmentation of neutral triatomic hydrogen

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Galster, Ulrich; Baumgartner, Frank; Mueller, Ulrich

    2005-12-15

    Dissociation of well-defined H{sub 3} Rydberg states into three ground state hydrogen atoms reveals characteristic correlation patterns in the center-of-mass motion of the three fragments. We present an extensive experimental dataset of momentum correlation maps for all lower Rydberg states of H{sub 3} and D{sub 3}. In particular the states with principal quantum number n=2 feature simple correlation patterns with regular occurence of mutual affinities. Energetically higher-lying states typically show more complex patterns which are unique for each state. Quantum-chemical calculations on adiabatic potential energy surfaces of H{sub 3} Rydberg states are presented to illuminate the likely origin of thesemore » differences. We discuss the likely dissociation mechanisms and paths which are responsible for the observed continuum correlation.« less

  14. 3D-QSAR based on quantum-chemical molecular fields: toward an improved description of halogen interactions.

    PubMed

    Güssregen, Stefan; Matter, Hans; Hessler, Gerhard; Müller, Marco; Schmidt, Friedemann; Clark, Timothy

    2012-09-24

    Current 3D-QSAR methods such as CoMFA or CoMSIA make use of classical force-field approaches for calculating molecular fields. Thus, they can not adequately account for noncovalent interactions involving halogen atoms like halogen bonds or halogen-π interactions. These deficiencies in the underlying force fields result from the lack of treatment of the anisotropy of the electron density distribution of those atoms, known as the "σ-hole", although recent developments have begun to take specific interactions such as halogen bonding into account. We have now replaced classical force field derived molecular fields by local properties such as the local ionization energy, local electron affinity, or local polarizability, calculated using quantum-mechanical (QM) techniques that do not suffer from the above limitation for 3D-QSAR. We first investigate the characteristics of QM-based local property fields to show that they are suitable for statistical analyses after suitable pretreatment. We then analyze these property fields with partial least-squares (PLS) regression to predict biological affinities of two data sets comprising factor Xa and GABA-A/benzodiazepine receptor ligands. While the resulting models perform equally well or even slightly better in terms of consistency and predictivity than the classical CoMFA fields, the most important aspect of these augmented field-types is that the chemical interpretation of resulting QM-based property field models reveals unique SAR trends driven by electrostatic and polarizability effects, which cannot be extracted directly from CoMFA electrostatic maps. Within the factor Xa set, the interaction of chlorine and bromine atoms with a tyrosine side chain in the protease S1 pocket are correctly predicted. Within the GABA-A/benzodiazepine ligand data set, PLS models of high predictivity resulted for our QM-based property fields, providing novel insights into key features of the SAR for two receptor subtypes and cross

  15. PREDICTING EVAPORATION RATES AND TIMES FOR SPILLS OF CHEMICAL MIXTURES

    EPA Science Inventory


    Spreadsheet and short-cut methods have been developed for predicting evaporation rates and evaporation times for spills (and constrained baths) of chemical mixtures. Steady-state and time-varying predictions of evaporation rates can be made for six-component mixtures, includ...

  16. In silico prediction of potential chemical reactions mediated by human enzymes.

    PubMed

    Yu, Myeong-Sang; Lee, Hyang-Mi; Park, Aaron; Park, Chungoo; Ceong, Hyithaek; Rhee, Ki-Hyeong; Na, Dokyun

    2018-06-13

    Administered drugs are often converted into an ineffective or activated form by enzymes in our body. Conventional in silico prediction approaches focused on therapeutically important enzymes such as CYP450. However, there are more than thousands of different cellular enzymes that potentially convert administered drug into other forms. We developed an in silico model to predict which of human enzymes including metabolic enzymes as well as CYP450 family can catalyze a given chemical compound. The prediction is based on the chemical and physical similarity between known enzyme substrates and a query chemical compound. Our in silico model was developed using multiple linear regression and the model showed high performance (AUC = 0.896) despite of the large number of enzymes. When evaluated on a test dataset, it also showed significantly high performance (AUC = 0.746). Interestingly, evaluation with literature data showed that our model can be used to predict not only enzymatic reactions but also drug conversion and enzyme inhibition. Our model was able to predict enzymatic reactions of a query molecule with a high accuracy. This may foster to discover new metabolic routes and to accelerate the computational development of drug candidates by enabling the prediction of the potential conversion of administered drugs into active or inactive forms.

  17. Quantum-mechanical parameters for the risk assessment of multi-walled carbon-nanotubes: A study using adsorption of probe compounds and its application to biomolecules.

    PubMed

    Chayawan; Vikas

    2016-11-01

    This work forwards new insights into the risk-assessment of multi-walled carbon-nanotubes (MWCNTs) while analysing the role of quantum-mechanical interactions between the electrons in the adsorption of probe compounds and biomolecules by MWCNTs. For this, the quantitative models are developed using quantum-chemical descriptors and their electron-correlation contribution. The major quantum-chemical factors contributing to the adsorption are found to be mean polarizability, electron-correlation energy, and electron-correlation contribution to the absolute electronegativity and LUMO energy. The proposed models, based on only three quantum-chemical factors, are found to be even more robust and predictive than the previously known five or four factors based linear free-energy and solvation-energy relationships. The proposed models are employed to predict the adsorption of biomolecules including steroid hormones and DNA bases. The steroid hormones are predicted to be strongly adsorbed by the MWCNTs, with the order: hydrocortisone > aldosterone > progesterone > ethinyl-oestradiol > testosterone > oestradiol, whereas the DNA bases are found to be relatively less adsorbed but follow the order as: guanine > adenine > thymine > cytosine > uracil. Besides these, the developed electron-correlation based models predict several insecticides, pesticides, herbicides, fungicides, plasticizers and antimicrobial agents in cosmetics, to be strongly adsorbed by the carbon-nanotubes. The present study proposes that the instantaneous inter-electronic interactions may be quite significant in various physico-chemical processes involving MWCNTs, and can be used as a reliable predictor for their risk assessment. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Development of bovine serum albumin-water partition coefficients predictive models for ionogenic organic chemicals based on chemical form adjusted descriptors.

    PubMed

    Ding, Feng; Yang, Xianhai; Chen, Guosong; Liu, Jining; Shi, Lili; Chen, Jingwen

    2017-10-01

    The partition coefficients between bovine serum albumin (BSA) and water (K BSA/w ) for ionogenic organic chemicals (IOCs) were different greatly from those of neutral organic chemicals (NOCs). For NOCs, several excellent models were developed to predict their logK BSA/w . However, it was found that the conventional descriptors are inappropriate for modeling logK BSA/w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for K BSA/w of IOCs. In this study, molecular descriptors that can be used to characterize the ionization effects (e.g. chemical form adjusted descriptors) were calculated and used to develop predictive models for logK BSA/w of IOCs. The models developed had high goodness-of-fit, robustness, and predictive ability. The predictor variables selected to construct the models included the chemical form adjusted averages of the negative potentials on the molecular surface (V s-adj - ), the chemical form adjusted molecular dipole moment (dipolemoment adj ), the logarithm of the n-octanol/water distribution coefficient (logD). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the logK BSA/w data gap for other IOCs within the applicability domain. Furthermore, the chemical form adjusted descriptors calculated in this study also could be used to construct predictive models on other endpoints of IOCs. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Quantum chemical determination of young?s modulus of lignin. Calculations on ß-O-4' model compound

    Treesearch

    Thomas Elder

    2007-01-01

    The calculation of Young?s modulus of lignin has been examined by subjecting a dimeric model compound to strain, coupled with the determination of energy and stress. The computational results, derived from quantum chemical calculations, are in agreement with available experimental results. Changes in geometry indicate that modifications in dihedral angles occur in...

  20. [Application of near infrared reflectance spectroscopy to predict meat chemical compositions: a review].

    PubMed

    Tao, Lin-Li; Yang, Xiu-Juan; Deng, Jun-Ming; Zhang, Xi

    2013-11-01

    In contrast to conventional methods for the determination of meat chemical composition, near infrared reflectance spectroscopy enables rapid, simple, secure and simultaneous assessment of numerous meat properties. The present review focuses on the use of near infrared reflectance spectroscopy to predict meat chemical compositions. The potential of near infrared reflectance spectroscopy to predict crude protein, intramuscular fat, fatty acid, moisture, ash, myoglobin and collagen of beef, pork, chicken and lamb is reviewed. This paper discusses existing questions and reasons in the current research. According to the published results, although published results vary considerably, they suggest that near-infrared reflectance spectroscopy shows a great potential to replace the expensive and time-consuming chemical analysis of meat composition. In particular, under commercial conditions where simultaneous measurements of different chemical components are required, near infrared reflectance spectroscopy is expected to be the method of choice. The majority of studies selected feature-related wavelengths using principal components regression, developed the calibration model using partial least squares and modified partial least squares, and estimated the prediction accuracy by means of cross-validation using the same sample set previously used for the calibration. Meat fatty acid composition predicted by near-infrared spectroscopy and non-destructive prediction and visualization of chemical composition in meat using near-infrared hyperspectral imaging and multivariate regression are the hot studying field now. On the other hand, near infrared reflectance spectroscopy shows great difference for predicting different attributes of meat quality which are closely related to the selection of calibration sample set, preprocessing of near-infrared spectroscopy and modeling approach. Sample preparation also has an important effect on the reliability of NIR prediction; in particular

  1. A comparative experimental and quantum chemical study on monomeric and dimeric structures of 3,5-dibromoanthranilic acid.

    PubMed

    Karabacak, Mehmet; Cinar, Mehmet

    2012-10-01

    This study presents the structural and spectroscopic characterization of 3,5-dibromoanthranilic acid with help of experimental techniques (FT-IR, FT-Raman, UV, NMR) and quantum chemical calculations. The vibrational spectra of title compound were recorded in solid state with FT-IR and FT-Raman in the range of 4000-400 and 4000-50 cm(-1), respectively. The vibrational frequencies were also computed using B3LYP method of DFT with 6-311++G(d,p) basis set. The fundamental assignments were done on the basis of the total energy distribution (TED) of the vibrational modes, calculated with scaled quantum mechanical (SQM) method. The (1)H, (13)C and DEPT NMR spectra were recorded in DMSO solution and calculated by gauge-invariant atomic orbitals (GIAO) method. The UV absorption spectra of the compound were recorded in the range of 200-400 nm in ethanol, water and DMSO solutions. Solvent effects were calculated using time-dependent density functional theory and CIS method. The ground state geometrical structure of compound was predicted by B3LYP method and compared with the crystallographic structure of similar compounds. All calculations were made for monomeric and dimeric structure of compound. Moreover, molecular electrostatic potential (MEP) and thermodynamic properties were performed. Mulliken atomic charges of neutral and anionic form of the molecule were computed and compared with anthranilic acid. Copyright © 2012 Elsevier B.V. All rights reserved.

  2. Robust scoring functions for protein-ligand interactions with quantum chemical charge models.

    PubMed

    Wang, Jui-Chih; Lin, Jung-Hsin; Chen, Chung-Ming; Perryman, Alex L; Olson, Arthur J

    2011-10-24

    Ordinary least-squares (OLS) regression has been used widely for constructing the scoring functions for protein-ligand interactions. However, OLS is very sensitive to the existence of outliers, and models constructed using it are easily affected by the outliers or even the choice of the data set. On the other hand, determination of atomic charges is regarded as of central importance, because the electrostatic interaction is known to be a key contributing factor for biomolecular association. In the development of the AutoDock4 scoring function, only OLS was conducted, and the simple Gasteiger method was adopted. It is therefore of considerable interest to see whether more rigorous charge models could improve the statistical performance of the AutoDock4 scoring function. In this study, we have employed two well-established quantum chemical approaches, namely the restrained electrostatic potential (RESP) and the Austin-model 1-bond charge correction (AM1-BCC) methods, to obtain atomic partial charges, and we have compared how different charge models affect the performance of AutoDock4 scoring functions. In combination with robust regression analysis and outlier exclusion, our new protein-ligand free energy regression model with AM1-BCC charges for ligands and Amber99SB charges for proteins achieve lowest root-mean-squared error of 1.637 kcal/mol for the training set of 147 complexes and 2.176 kcal/mol for the external test set of 1427 complexes. The assessment for binding pose prediction with the 100 external decoy sets indicates very high success rate of 87% with the criteria of predicted root-mean-squared deviation of less than 2 Å. The success rates and statistical performance of our robust scoring functions are only weakly class-dependent (hydrophobic, hydrophilic, or mixed).

  3. Quantum descriptors for predictive toxicology of halogenated aliphatic hydrocarbons.

    PubMed

    Trohalaki, S; Pachter, R

    2003-04-01

    In order to improve Quantitative Structure-Activity Relationships (QSARs) for halogenated aliphatics (HA) and to better understand the biophysical mechanism of toxic response to these ubiquitous chemicals, we employ improved quantum-mechanical descriptors to account for HA electrophilicity. We demonstrate that, unlike the lowest unoccupied molecular orbital energy, ELUMO, which was previously used as a descriptor, the electron affinity can be systematically improved by application of higher levels of theory. We also show that employing the reciprocal of ELUMO, which is more consistent with frontier molecular orbital (FMO) theory, improves the correlations with in vitro toxicity data. We offer explanations based on FMO theory for a result from our previous work, in which the LUMO energies of HA anions correlated surprisingly well with in vitro toxicity data. Additional descriptors are also suggested and interpreted in terms of the accepted biophysical mechanism of toxic response to HAs and new QSARs are derived for various chemical categories that compose the data set employed. These alternate descriptors provide important insight and could benefit other classes of compounds where the biophysical mechanism of toxic response involves dissociative attachment.

  4. Conformational, structural, vibrational and quantum chemical analysis on 4-aminobenzohydrazide and 4-hydroxybenzohydrazide--a comparative study.

    PubMed

    Arjunan, V; Jayaprakash, A; Carthigayan, K; Periandy, S; Mohan, S

    2013-05-01

    Experimental and theoretical quantum chemical studies were carried out on 4-hydroxybenzohydrazide (4HBH) and 4-aminobenzohydrazide (4ABH) using FTIR and FT-Raman spectral data. The structural characteristics and vibrational spectroscopic analysis were carried performed by quantum chemical methods with the hybrid exchange-correlation functional B3LYP using 6-31G(**), 6-311++G(**) and aug-cc-pVDZ basis sets. The most stable conformer of the title compounds have been determined from the analysis of potential energy surface. The stable molecular geometries, electronic and thermodynamic parameters, IR intensities, harmonic vibrational frequencies, depolarisation ratio and Raman intensities have been computed. Molecular electrostatic potential and frontier molecular orbitals were constructed to understand the electronic properties. The potential energy distributions (PEDs) were calculated to explain the mixing of fundamental modes. The theoretical geometrical parameters and the fundamental frequencies were compared with the experimental. The interactions of hydroxy and amino group substitutions on the characteristic vibrations of the ring and hydrazide group have been analysed. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Recent developments of the quantum chemical cluster approach for modeling enzyme reactions.

    PubMed

    Siegbahn, Per E M; Himo, Fahmi

    2009-06-01

    The quantum chemical cluster approach for modeling enzyme reactions is reviewed. Recent applications have used cluster models much larger than before which have given new modeling insights. One important and rather surprising feature is the fast convergence with cluster size of the energetics of the reactions. Even for reactions with significant charge separation it has in some cases been possible to obtain full convergence in the sense that dielectric cavity effects from outside the cluster do not contribute to any significant extent. Direct comparisons between quantum mechanics (QM)-only and QM/molecular mechanics (MM) calculations for quite large clusters in a case where the results differ significantly have shown that care has to be taken when using the QM/MM approach where there is strong charge polarization. Insights from the methods used, generally hybrid density functional methods, have also led to possibilities to give reasonable error limits for the results. Examples are finally given from the most extensive study using the cluster model, the one of oxygen formation at the oxygen-evolving complex in photosystem II.

  6. Quantum chemistry simulation on quantum computers: theories and experiments.

    PubMed

    Lu, Dawei; Xu, Boruo; Xu, Nanyang; Li, Zhaokai; Chen, Hongwei; Peng, Xinhua; Xu, Ruixue; Du, Jiangfeng

    2012-07-14

    It has been claimed that quantum computers can mimic quantum systems efficiently in the polynomial scale. Traditionally, those simulations are carried out numerically on classical computers, which are inevitably confronted with the exponential growth of required resources, with the increasing size of quantum systems. Quantum computers avoid this problem, and thus provide a possible solution for large quantum systems. In this paper, we first discuss the ideas of quantum simulation, the background of quantum simulators, their categories, and the development in both theories and experiments. We then present a brief introduction to quantum chemistry evaluated via classical computers followed by typical procedures of quantum simulation towards quantum chemistry. Reviewed are not only theoretical proposals but also proof-of-principle experimental implementations, via a small quantum computer, which include the evaluation of the static molecular eigenenergy and the simulation of chemical reaction dynamics. Although the experimental development is still behind the theory, we give prospects and suggestions for future experiments. We anticipate that in the near future quantum simulation will become a powerful tool for quantum chemistry over classical computations.

  7. About Using Predictive Models and Tools To Assess Chemicals under TSCA

    EPA Pesticide Factsheets

    As part of EPA's effort to promote chemical safety, OPPT provides public access to predictive models and tools which can help inform the public on the hazards and risks of substances and improve chemical management decisions.

  8. Newtonian semiclassical gravity in three ontological quantum theories that solve the measurement problem: Formalisms and empirical predictions

    NASA Astrophysics Data System (ADS)

    Derakhshani, Maaneli

    In this thesis, we consider the implications of solving the quantum measurement problem for the Newtonian description of semiclassical gravity. First we review the formalism of the Newtonian description of semiclassical gravity based on standard quantum mechanics---the Schroedinger-Newton theory---and two well-established predictions that come out of it, namely, gravitational 'cat states' and gravitationally-induced wavepacket collapse. Then we review three quantum theories with 'primitive ontologies' that are well-known known to solve the measurement problem---Schroedinger's many worlds theory, the GRW collapse theory with matter density ontology, and Nelson's stochastic mechanics. We extend the formalisms of these three quantum theories to Newtonian models of semiclassical gravity and evaluate their implications for gravitational cat states and gravitational wavepacket collapse. We find that (1) Newtonian semiclassical gravity based on Schroedinger's many worlds theory is mathematically equivalent to the Schroedinger-Newton theory and makes the same predictions; (2) Newtonian semiclassical gravity based on the GRW theory differs from Schroedinger-Newton only in the use of a stochastic collapse law, but this law allows it to suppress gravitational cat states so as not to be in contradiction with experiment, while allowing for gravitational wavepacket collapse to happen as well; (3) Newtonian semiclassical gravity based on Nelson's stochastic mechanics differs significantly from Schroedinger-Newton, and does not predict gravitational cat states nor gravitational wavepacket collapse. Considering that gravitational cat states are experimentally ruled out, but gravitational wavepacket collapse is testable in the near future, this implies that only the latter two are viable theories of Newtonian semiclassical gravity and that they can be experimentally tested against each other in future molecular interferometry experiments that are anticipated to be capable of testing

  9. Measuring and Predicting the Internal Structure of Semiconductor Nanocrystals through Raman Spectroscopy.

    PubMed

    Mukherjee, Prabuddha; Lim, Sung Jun; Wrobel, Tomasz P; Bhargava, Rohit; Smith, Andrew M

    2016-08-31

    Nanocrystals composed of mixed chemical domains have diverse properties that are driving their integration in next-generation electronics, light sources, and biosensors. However, the precise spatial distribution of elements within these particles is difficult to measure and control, yet profoundly impacts their quality and performance. Here we synthesized a unique series of 42 different quantum dot nanocrystals, composed of two chemical domains (CdS:CdSe), arranged in 7 alloy and (core)shell structural classes. Chemometric analyses of far-field Raman spectra accurately classified their internal structures from their vibrational signatures. These classifications provide direct insight into the elemental arrangement of the alloy as well as an independent prediction of fluorescence quantum yield. This nondestructive, rapid approach can be broadly applied to greatly enhance our capacity to measure, predict and monitor multicomponent nanomaterials for precise tuning of their structures and properties.

  10. PREDICTING TOXICOLOGICAL ENDPOINTS OF CHEMICALS USING QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS (QSARS)

    EPA Science Inventory

    Quantitative structure-activity relationships (QSARs) are being developed to predict the toxicological endpoints for untested chemicals similar in structure to chemicals that have known experimental toxicological data. Based on a very large number of predetermined descriptors, a...

  11. Prediction of biodegradability from chemical structure: Modeling or ready biodegradation test data

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Loonen, H.; Lindgren, F.; Hansen, B.

    1999-08-01

    Biodegradation data were collected and evaluated for 894 substances with widely varying chemical structures. All data were determined according to the Japanese Ministry of International Trade and Industry (MITI) I test protocol. The MITI I test is a screening test for ready biodegradability and has been described by Organization for Economic Cooperation and Development (OECD) test guideline 301 C and European Union (EU) test guideline C4F. The chemicals were characterized by a set of 127 predefined structural fragments. This data set was used to develop a model for the prediction of the biodegradability of chemicals under standardized OECD and EUmore » ready biodegradation test conditions. Partial least squares (PLS) discriminant analysis was used for the model development. The model was evaluated by means of internal cross-validation and repeated external validation. The importance of various structural fragments and fragment interactions was investigated. The most important fragments include the presence of a long alkyl chain; hydroxy, ester, and acid groups (enhancing biodegradation); and the presence of one or more aromatic rings and halogen substituents (regarding biodegradation). More than 85% of the model predictions were correct for using the complete data set. The not readily biodegradable predictions were slightly better than the readily biodegradable predictions (86 vs 84%). The average percentage of correct predictions from four external validation studies was 83%. Model optimization by including fragment interactions improve the model predicting capabilities to 89%. It can be concluded that the PLS model provides predictions of high reliability for a diverse range of chemical structures. The predictions conform to the concept of readily biodegradable (or not readily biodegradable) as defined by OECD and EU test guidelines.« less

  12. Efficient quantum walk on a quantum processor

    PubMed Central

    Qiang, Xiaogang; Loke, Thomas; Montanaro, Ashley; Aungskunsiri, Kanin; Zhou, Xiaoqi; O'Brien, Jeremy L.; Wang, Jingbo B.; Matthews, Jonathan C. F.

    2016-01-01

    The random walk formalism is used across a wide range of applications, from modelling share prices to predicting population genetics. Likewise, quantum walks have shown much potential as a framework for developing new quantum algorithms. Here we present explicit efficient quantum circuits for implementing continuous-time quantum walks on the circulant class of graphs. These circuits allow us to sample from the output probability distributions of quantum walks on circulant graphs efficiently. We also show that solving the same sampling problem for arbitrary circulant quantum circuits is intractable for a classical computer, assuming conjectures from computational complexity theory. This is a new link between continuous-time quantum walks and computational complexity theory and it indicates a family of tasks that could ultimately demonstrate quantum supremacy over classical computers. As a proof of principle, we experimentally implement the proposed quantum circuit on an example circulant graph using a two-qubit photonics quantum processor. PMID:27146471

  13. Prediction of chemical biodegradability using support vector classifier optimized with differential evolution.

    PubMed

    Cao, Qi; Leung, K M

    2014-09-22

    Reliable computer models for the prediction of chemical biodegradability from molecular descriptors and fingerprints are very important for making health and environmental decisions. Coupling of the differential evolution (DE) algorithm with the support vector classifier (SVC) in order to optimize the main parameters of the classifier resulted in an improved classifier called the DE-SVC, which is introduced in this paper for use in chemical biodegradability studies. The DE-SVC was applied to predict the biodegradation of chemicals on the basis of extensive sample data sets and known structural features of molecules. Our optimization experiments showed that DE can efficiently find the proper parameters of the SVC. The resulting classifier possesses strong robustness and reliability compared with grid search, genetic algorithm, and particle swarm optimization methods. The classification experiments conducted here showed that the DE-SVC exhibits better classification performance than models previously used for such studies. It is a more effective and efficient prediction model for chemical biodegradability.

  14. Hybrid quantum and classical methods for computing kinetic isotope effects of chemical reactions in solutions and in enzymes.

    PubMed

    Gao, Jiali; Major, Dan T; Fan, Yao; Lin, Yen-Lin; Ma, Shuhua; Wong, Kin-Yiu

    2008-01-01

    A method for incorporating quantum mechanics into enzyme kinetics modeling is presented. Three aspects are emphasized: 1) combined quantum mechanical and molecular mechanical methods are used to represent the potential energy surface for modeling bond forming and breaking processes, 2) instantaneous normal mode analyses are used to incorporate quantum vibrational free energies to the classical potential of mean force, and 3) multidimensional tunneling methods are used to estimate quantum effects on the reaction coordinate motion. Centroid path integral simulations are described to make quantum corrections to the classical potential of mean force. In this method, the nuclear quantum vibrational and tunneling contributions are not separable. An integrated centroid path integral-free energy perturbation and umbrella sampling (PI-FEP/UM) method along with a bisection sampling procedure was summarized, which provides an accurate, easily convergent method for computing kinetic isotope effects for chemical reactions in solution and in enzymes. In the ensemble-averaged variational transition state theory with multidimensional tunneling (EA-VTST/MT), these three aspects of quantum mechanical effects can be individually treated, providing useful insights into the mechanism of enzymatic reactions. These methods are illustrated by applications to a model process in the gas phase, the decarboxylation reaction of N-methyl picolinate in water, and the proton abstraction and reprotonation process catalyzed by alanine racemase. These examples show that the incorporation of quantum mechanical effects is essential for enzyme kinetics simulations.

  15. Theoretical calculations of physico-chemical and spectroscopic properties of bioinorganic systems: current limits and perspectives.

    PubMed

    Rokob, Tibor András; Srnec, Martin; Rulíšek, Lubomír

    2012-05-21

    In the last decade, we have witnessed substantial progress in the development of quantum chemical methodologies. Simultaneously, robust solvation models and various combined quantum and molecular mechanical (QM/MM) approaches have become an integral part of quantum chemical programs. Along with the steady growth of computer power and, more importantly, the dramatic increase of the computer performance to price ratio, this has led to a situation where computational chemistry, when exercised with the proper amount of diligence and expertise, reproduces, predicts, and complements the experimental data. In this perspective, we review some of the latest achievements in the field of theoretical (quantum) bioinorganic chemistry, concentrating mostly on accurate calculations of the spectroscopic and physico-chemical properties of open-shell bioinorganic systems by wave-function (ab initio) and DFT methods. In our opinion, the one-to-one mapping between the calculated properties and individual molecular structures represents a major advantage of quantum chemical modelling since this type of information is very difficult to obtain experimentally. Once (and only once) the physico-chemical, thermodynamic and spectroscopic properties of complex bioinorganic systems are quantitatively reproduced by theoretical calculations may we consider the outcome of theoretical modelling, such as reaction profiles and the various decompositions of the calculated parameters into individual spatial or physical contributions, to be reliable. In an ideal situation, agreement between theory and experiment may imply that the practical problem at hand, such as the reaction mechanism of the studied metalloprotein, can be considered as essentially solved.

  16. Toxicity challenges in environmental chemicals: Prediction of ...

    EPA Pesticide Factsheets

    Physiologically based pharmacokinetic (PBPK) models bridge the gap between in vitro assays and in vivo effects by accounting for the adsorption, distribution, metabolism, and excretion of xenobiotics, which is especially useful in the assessment of human toxicity. Quantitative structure-activity relationships (QSAR) serve as a vital tool for the high-throughput prediction of chemical-specific PBPK parameters, such as the fraction of a chemical unbound by plasma protein (Fub). The presented work explores the merit of utilizing experimental pharmaceutical Fub data for the construction of a universal QSAR model, in order to compensate for the limited range of high-quality experimental Fub data for environmentally relevant chemicals, such as pollutants, pesticides, and consumer products. Independent QSAR models were constructed with three machine-learning algorithms, k nearest neighbors (kNN), random forest (RF), and support vector machine (SVM) regression, from a large pharmaceutical training set (~1000) and assessed with independent test sets of pharmaceuticals (~200) and environmentally relevant chemicals in the ToxCast program (~400). Small descriptor sets yielded the optimal balance of model complexity and performance, providing insight into the biochemical factors of plasma protein binding, while preventing over fitting to the training set. Overlaps in chemical space between pharmaceutical and environmental compounds were considered through applicability of do

  17. Predicting organ toxicity using in vitro bioactivity data and chemical structure

    EPA Science Inventory

    Animal testing alone cannot practically evaluate the health hazard posed by tens of thousands of environmental chemicals. Computational approaches together with high-throughput experimental data may provide more efficient means to predict chemical toxicity. Here, we use a superv...

  18. Neural network approach to quantum-chemistry data: accurate prediction of density functional theory energies.

    PubMed

    Balabin, Roman M; Lomakina, Ekaterina I

    2009-08-21

    Artificial neural network (ANN) approach has been applied to estimate the density functional theory (DFT) energy with large basis set using lower-level energy values and molecular descriptors. A total of 208 different molecules were used for the ANN training, cross validation, and testing by applying BLYP, B3LYP, and BMK density functionals. Hartree-Fock results were reported for comparison. Furthermore, constitutional molecular descriptor (CD) and quantum-chemical molecular descriptor (QD) were used for building the calibration model. The neural network structure optimization, leading to four to five hidden neurons, was also carried out. The usage of several low-level energy values was found to greatly reduce the prediction error. An expected error, mean absolute deviation, for ANN approximation to DFT energies was 0.6+/-0.2 kcal mol(-1). In addition, the comparison of the different density functionals with the basis sets and the comparison of multiple linear regression results were also provided. The CDs were found to overcome limitation of the QD. Furthermore, the effective ANN model for DFT/6-311G(3df,3pd) and DFT/6-311G(2df,2pd) energy estimation was developed, and the benchmark results were provided.

  19. Tunable Quantum Spin Liquidity in the 1 /6 th-Filled Breathing Kagome Lattice

    NASA Astrophysics Data System (ADS)

    Akbari-Sharbaf, A.; Sinclair, R.; Verrier, A.; Ziat, D.; Zhou, H. D.; Sun, X. F.; Quilliam, J. A.

    2018-06-01

    We present measurements on a series of materials, Li2 In1 -xScx Mo3 O8 , that can be described as a 1 /6 th-filled breathing kagome lattice. Substituting Sc for In generates chemical pressure which alters the breathing parameter nonmonotonically. Muon spin rotation experiments show that this chemical pressure tunes the system from antiferromagnetic long range order to a quantum spin liquid phase. A strong correlation with the breathing parameter implies that it is the dominant parameter controlling the level of magnetic frustration, with increased kagome symmetry generating the quantum spin liquid phase. Magnetic susceptibility measurements suggest that this is related to distinct types of charge order induced by changes in lattice symmetry, in line with the theory of Chen et al. [Phys. Rev. B 93, 245134 (2016), 10.1103/PhysRevB.93.245134]. The specific heat for samples at intermediate Sc concentration, which have the minimum breathing parameter, show consistency with the predicted U (1 ) quantum spin liquid.

  20. The quantum dynamics of electronically nonadiabatic chemical reactions

    NASA Technical Reports Server (NTRS)

    Truhlar, Donald G.

    1993-01-01

    Considerable progress was achieved on the quantum mechanical treatment of electronically nonadiabatic collisions involving energy transfer and chemical reaction in the collision of an electronically excited atom with a molecule. In the first step, a new diabatic representation for the coupled potential energy surfaces was created. A two-state diabatic representation was developed which was designed to realistically reproduce the two lowest adiabatic states of the valence bond model and also to have the following three desirable features: (1) it is more economical to evaluate; (2) it is more portable; and (3) all spline fits are replaced by analytic functions. The new representation consists of a set of two coupled diabatic potential energy surfaces plus a coupling surface. It is suitable for dynamics calculations on both the electronic quenching and reaction processes in collisions of Na(3p2p) with H2. The new two-state representation was obtained by a three-step process from a modified eight-state diatomics-in-molecules (DIM) representation of Blais. The second step required the development of new dynamical methods. A formalism was developed for treating reactions with very general basis functions including electronically excited states. Our formalism is based on the generalized Newton, scattered wave, and outgoing wave variational principles that were used previously for reactive collisions on a single potential energy surface, and it incorporates three new features: (1) the basis functions include electronic degrees of freedom, as required to treat reactions involving electronic excitation and two or more coupled potential energy surfaces; (2) the primitive electronic basis is assumed to be diabatic, and it is not assumed that it diagonalizes the electronic Hamiltonian even asymptotically; and (3) contracted basis functions for vibrational-rotational-orbital degrees of freedom are included in a very general way, similar to previous prescriptions for locally

  1. QSAR, DFT and quantum chemical studies on the inhibition potentials of some carbozones for the corrosion of mild steel in HCl.

    PubMed

    Eddy, Nnabuk O; Ita, Benedict I

    2011-02-01

    Experimental aspects of the inhibition of the corrosion of mild steel in HCl solutions by some carbozones were studied using gravimetric, thermometric and gasometric methods, while a theoretical study was carried out using density functional theory, a quantitative structure-activity relation, and quantum chemical principles. The results obtained indicated that the studied carbozones are good adsorption inhibitors for the corrosion of mild steel in HCl. The inhibition efficiencies of the studied carbozones were found to increase with increasing concentration of the respective inhibitor. A strong correlation was found between the average inhibition efficiency and some quantum chemical parameters, and also between the experimental and theoretical inhibition efficiencies (obtained from the quantitative structure-activity relation).

  2. Spectroscopic studies and quantum chemical investigations of (3,4-dimethoxybenzylidene) propanedinitrile

    NASA Astrophysics Data System (ADS)

    Gupta, Ujval; Kumar, Vinay; Singh, Vivek K.; Kant, Rajni; Khajuria, Yugal

    2015-04-01

    The Fourier Transform Infrared (FTIR), Ultra-Violet Visible (UV-Vis) spectroscopy and Thermogravimetric (TG) analysis of (3,4-dimethoxybenzylidene) propanedinitrile have been carried out and investigated using quantum chemical calculations. The molecular geometry, harmonic vibrational frequencies, Mulliken charges, natural atomic charges and thermodynamic properties in the ground state have been investigated by using Hartree Fock Theory (HF) and Density Functional Theory (DFT) using B3LYP functional with 6-311G(d,p) basis set. Both HF and DFT methods yield good agreement with the experimental data. Vibrational modes are assigned with the help of Vibrational Energy Distribution Analysis (VEDA) program. UV-Visible spectrum was recorded in the spectral range of 190-800 nm and the results are compared with the calculated values using TD-DFT approach. Stability of the molecule arising from hyperconjugative interactions, charge delocalization have been analyzed using natural bond orbital (NBO) analysis. The results obtained from the studies of Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) are used to calculate molecular parameters like ionization potential, electron affinity, global hardness, electron chemical potential and global electrophilicity.

  3. Leveraging Publically Available Chemical Functional Use Data in Support of Exposure Prediction

    EPA Science Inventory

    The U.S. EPA Exposure Forecasting (ExpoCast) project aims to provide rapid screening-level exposure predictions for thousands of chemicals, most of which lack detailed exposure data. Chemical functional use - the role a chemical plays in processes or products (e.g. solvent, ant...

  4. An expert system for prediction of chemical toxicity

    USGS Publications Warehouse

    Hickey, James P.; Aldridge, Andrew J.; Passino-Reader, Dora R.; Frank, Anthony M.

    1992-01-01

    The National Fisheries Research Center- Great Lakes has developed an interactive computer program that uses the structure of an organic molecule to predict its acute toxicity to four aquatic species. The expert system software, written in the muLISP language, identifies the skeletal structures and substituent groups of an organic molecule from a user-supplied standard chemical notation known as a SMILES string, and then generates values for four solvatochromic parameters. Multiple regression equations relate these parameters to the toxicities (expressed as log10LC50s and log10EC50s, along with 95% confidence intervals) for four species. The system is demonstrated by prediction of toxicity for anilide-type pesticides to the fathead minnow (Pimephales promelas). This software is designed for use on an IBM-compatible personal computer by personnel with minimal toxicology background for rapid estimation of chemical toxicity. The system has numerous applications, with much potential for use in the pharmaceutical industry

  5. Predictive performance of the Vitrigel‐eye irritancy test method using 118 chemicals

    PubMed Central

    Yamaguchi, Hiroyuki; Kojima, Hajime

    2015-01-01

    Abstract We recently developed a novel Vitrigel‐eye irritancy test (EIT) method. The Vitrigel‐EIT method is composed of two parts, i.e., the construction of a human corneal epithelium (HCE) model in a collagen vitrigel membrane chamber and the prediction of eye irritancy by analyzing the time‐dependent profile of transepithelial electrical resistance values for 3 min after exposing a chemical to the HCE model. In this study, we estimated the predictive performance of Vitrigel‐EIT method by testing a total of 118 chemicals. The category determined by the Vitrigel‐EIT method in comparison to the globally harmonized system classification revealed that the sensitivity, specificity and accuracy were 90.1%, 65.9% and 80.5%, respectively. Here, five of seven false‐negative chemicals were acidic chemicals inducing the irregular rising of transepithelial electrical resistance values. In case of eliminating the test chemical solutions showing pH 5 or lower, the sensitivity, specificity and accuracy were improved to 96.8%, 67.4% and 84.4%, respectively. Meanwhile, nine of 16 false‐positive chemicals were classified irritant by the US Environmental Protection Agency. In addition, the disappearance of ZO‐1, a tight junction‐associated protein and MUC1, a cell membrane‐spanning mucin was immunohistologically confirmed in the HCE models after exposing not only eye irritant chemicals but also false‐positive chemicals, suggesting that such false‐positive chemicals have an eye irritant potential. These data demonstrated that the Vitrigel‐EIT method could provide excellent predictive performance to judge the widespread eye irritancy, including very mild irritant chemicals. We hope that the Vitrigel‐EIT method contributes to the development of safe commodity chemicals. Copyright © 2015 The Authors. Journal of Applied Toxicology published by John Wiley & Sons Ltd. PMID:26472347

  6. Predictive performance of the Vitrigel-eye irritancy test method using 118 chemicals.

    PubMed

    Yamaguchi, Hiroyuki; Kojima, Hajime; Takezawa, Toshiaki

    2016-08-01

    We recently developed a novel Vitrigel-eye irritancy test (EIT) method. The Vitrigel-EIT method is composed of two parts, i.e., the construction of a human corneal epithelium (HCE) model in a collagen vitrigel membrane chamber and the prediction of eye irritancy by analyzing the time-dependent profile of transepithelial electrical resistance values for 3 min after exposing a chemical to the HCE model. In this study, we estimated the predictive performance of Vitrigel-EIT method by testing a total of 118 chemicals. The category determined by the Vitrigel-EIT method in comparison to the globally harmonized system classification revealed that the sensitivity, specificity and accuracy were 90.1%, 65.9% and 80.5%, respectively. Here, five of seven false-negative chemicals were acidic chemicals inducing the irregular rising of transepithelial electrical resistance values. In case of eliminating the test chemical solutions showing pH 5 or lower, the sensitivity, specificity and accuracy were improved to 96.8%, 67.4% and 84.4%, respectively. Meanwhile, nine of 16 false-positive chemicals were classified irritant by the US Environmental Protection Agency. In addition, the disappearance of ZO-1, a tight junction-associated protein and MUC1, a cell membrane-spanning mucin was immunohistologically confirmed in the HCE models after exposing not only eye irritant chemicals but also false-positive chemicals, suggesting that such false-positive chemicals have an eye irritant potential. These data demonstrated that the Vitrigel-EIT method could provide excellent predictive performance to judge the widespread eye irritancy, including very mild irritant chemicals. We hope that the Vitrigel-EIT method contributes to the development of safe commodity chemicals. Copyright © 2015 The Authors. Journal of Applied Toxicology published by John Wiley & Sons Ltd. Copyright © 2015 The Authors. Journal of Applied Toxicology published by John Wiley & Sons Ltd.

  7. Epitaxial Zn quantum dots coherently grown on Si(1 1 1): growth mechanism, nonlinear optical and chemical states analyses

    NASA Astrophysics Data System (ADS)

    Huang, Bo-Jia; Kao, Li-Chi; Brahma, Sanjaya; Jeng, Yu-En; Chiu, Shang-Jui; Ku, Ching-Shun; Lo, Kuang-Yao

    2017-05-01

    Oxide- and defect-free metal/semiconductor interface is important to improve Ohmic contact for the suppression of electron scattering and the avoidance of an extrinsic surface state in estimating the barrier of the Schottky contact at the nanodevice interface. This study reports the growth mechanism of Zn quantum dots coherently grown on Si(1 1 1) and the physical phenomena of the crystalline, nonlinear optics, and the chemical states of Zn quantum dots. Epitaxial Zn quantum dots were coherently formed on a non-oxide Si(1 1 1) surface through the liquid- to solid-phase transformation as a result of pattern matching between the Zn(0 0 2) and Si(1 1 1) surfaces. The growth mechanism of constrained Zn quantum dots grown through strategic magnetron radio frequency sputtering is complex. Some factors, such as substrate temperature, hydrogen gas flow, and negative DC bias, influence the configuration of epitaxial Zn quantum dots. In particular, hydrogen gas plays an important role in reducing the ZnO+ and native oxide that is bombarded by accelerated ions, thereby enhancing the Zn ion surface diffusion. The reduction reaction can be inspected by distinguishing the chemical states of ZnO/Zn quantum dots from natural oxidation or the states of Zn 3d through the analysis of x-ray absorption near the edge structure spectrum. The complex growth mechanism can be systematically understood by analyzing a noncancelled anisotropic 3 m dipole from reflective second harmonic generation and inspecting the evolution between the Zn(0 0 2) and Zn(1 1 1) peaks of the collective ZnO/Zn quantum dots in synchrotron XRD.

  8. Prediction of novel synthetic pathways for the production of desired chemicals.

    PubMed

    Cho, Ayoun; Yun, Hongseok; Park, Jin Hwan; Lee, Sang Yup; Park, Sunwon

    2010-03-28

    There have been several methods developed for the prediction of synthetic metabolic pathways leading to the production of desired chemicals. In these approaches, novel pathways were predicted based on chemical structure changes, enzymatic information, and/or reaction mechanisms, but the approaches generating a huge number of predicted results are difficult to be applied to real experiments. Also, some of these methods focus on specific pathways, and thus are limited to expansion to the whole metabolism. In the present study, we propose a system framework employing a retrosynthesis model with a prioritization scoring algorithm. This new strategy allows deducing the novel promising pathways for the synthesis of a desired chemical together with information on enzymes involved based on structural changes and reaction mechanisms present in the system database. The prioritization scoring algorithm employing Tanimoto coefficient and group contribution method allows examination of structurally qualified pathways to recognize which pathway is more appropriate. In addition, new concepts of binding site covalence, estimation of pathway distance and organism specificity were taken into account to identify the best synthetic pathway. Parameters of these factors can be evolutionarily optimized when a newly proven synthetic pathway is registered. As the proofs of concept, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate, and butyryl-CoA were predicted. The prediction shows a high reliability, in which experimentally verified synthetic pathways were listed within the top 0.089% of the identified pathway candidates. It is expected that the system framework developed in this study would be useful for the in silico design of novel metabolic pathways to be employed for the efficient production of chemicals, fuels and materials.

  9. Use of external cavity quantum cascade laser compliance voltage in real-time trace gas sensing of multiple chemicals

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Phillips, Mark C.; Taubman, Matthew S.; Kriesel, Jason M.

    2015-02-08

    We describe a prototype trace gas sensor designed for real-time detection of multiple chemicals. The sensor uses an external cavity quantum cascade laser (ECQCL) swept over its tuning range of 940-1075 cm-1 (9.30-10.7 µm) at a 10 Hz repetition rate.

  10. Prediction Metrics for Chemical Detection in Long-Wave Infrared Hyperspectral Imagery

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chilton, Marie C.; Walsh, Stephen J.; Daly, Don S.

    2009-01-29

    A natural or anthropogenic process often generates a signature gas plume whose chemical constituents may be identified using hyperspectral imagery. A hyperspectral image is a pixel-indexed set of spectra where each spectrum reflects the chemical constituents of the plume, the atmosphere, the bounding background surface, and instrument noise. This study explored the relationship between gas absorbance and background emissivity across the long-wave infrared (LWIR) spectrum and how they affect relative gas detection sensitivity. The physics-based model for the observed radiance shows that high gas absorbance coupled with low background emissivity at a single wavenumber results in a stronger recorded radiance.more » Two sensitivity measures were developed to predict relative probability of detection using chemical absorbance and background emissivity: one focused on a single wavenumber while another accounted for the entire spectrum. The predictive abilities of these measures were compared to synthetic image analysis. This study simulated images with 499 distinct gases at each of 6 concentrations over 6 different background surfaces with the atmosphere and level of instrument noise held constant. The Whitened Matched Filter was used to define gas detection from an image spectrum. The estimate of a chemical’s probability of detection at a given concentration over a specific background was the proportion of detections in 500 trials. Of the 499 chemicals used in the images, 276 had estimated probabilities of detection below 0.2 across all backgrounds and concentrations; these chemicals were removed from the study. For 92.8 percent of the remaining chemicals, the single channel measure correctly predicted the background over which the chemical had the largest relative probability of detection. Further, the measure which accounted for information across all wavenumbers predicted the background over which the chemical had the largest relative probability of detection for

  11. Quantum chemical characterization of zwitterionic structures: Supramolecular complexes for modifying the wettability of oil-water-limestone system.

    PubMed

    Lopez-Chavez, Ernesto; Garcia-Quiroz, Alberto; Gonzalez-Garcia, Gerardo; Orozco-Duran, Gabriela E; Zamudio-Rivera, Luis S; Martinez-Magadan, José M; Buenrostro-Gonzalez, Eduardo; Hernandez-Altamirano, Raul

    2014-06-01

    In this work, we present a quantum chemical study pertaining to some supramolecular complexes acting as wettability modifiers of oil-water-limestone system. The complexes studied are derived from zwitterionic liquids of the types N'-alkyl-bis, N-alquenil, N-cycloalkyl, N-amyl-bis-beta amino acid or salts acting as sparkling agents. We studied two molecules of zwitterionic liquids (ZL10 and ZL13), HOMO and LUMO levels, and the energy gap between them, were calculated, as well as the electron affinity (EA) and ionization potential (IP), chemical potential, chemical hardness, chemical electrophilicity index and selectivity descriptors such Fukui indices. In this work, electrochemical comparison was realized with cocamidopropyl betaine (CPB), which is a structure zwitterionic liquid type, nowadays widely applied in enhanced recovery processes. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Predicting ready biodegradability of premanufacture notice chemicals.

    PubMed

    Boethling, Robert S; Lynch, David G; Thom, Gary C

    2003-04-01

    Chemical substances other than pesticides, drugs, and food additives are regulated by the U.S. Environmental Protection Agency (U.S. EPA) under the Toxic Substances Control Act (TSCA), but the United States does not require that new substances be tested automatically for such critical properties as biodegradability. The resulting lack of submitted data has fostered the development of estimation methods, and the BioWIN models for predicting biodegradability from chemical structure have played a prominent role in premanufacture notice (PMN) review. Until now, validation efforts have used only the Japanese Ministry of International Trade and Industry (MITI) test data and have not included all models. To assess BioWIN performance with PMN substances, we assembled a database of PMNs for which ready biodegradation data had been submitted over the period 1995 through 2001. The 305 PMN structures are highly varied and pose major challenges to chemical property estimation. Despite the variability of ready biodegradation tests, the use of at least six different test methods, and widely varying quality of submitted data, accuracy of four of six BioWIN models (MITI linear, MITI nonlinear, survey ultimate, survey primary) was in the 80+% range for predicting ready biodegradability. Greater accuracy (>90%) can be achieved by using model estimates only when the four models agree (true for 3/4 of the PMNs). The BioWIN linear and nonlinear probability models did not perform as well even when classification criteria were optimized. The results suggest that the MITI and survey BioWIN models are suitable for use in screening-level applications.

  13. High-School Students' Conceptual Difficulties and Attempts at Conceptual Change: The Case of Basic Quantum Chemical Concepts

    ERIC Educational Resources Information Center

    Tsaparlis, Georgios; Papaphotis, Georgios

    2009-01-01

    This study tested for deep understanding and critical thinking about basic quantum chemical concepts taught at 12th grade (age 17-18). Our aim was to achieve conceptual change in students. A quantitative study was conducted first (n = 125), and following this 23 selected students took part in semi-structured interviews either individually or in…

  14. Chemical Potential for the Interacting Classical Gas and the Ideal Quantum Gas Obeying a Generalized Exclusion Principle

    ERIC Educational Resources Information Center

    Sevilla, F. J.; Olivares-Quiroz, L.

    2012-01-01

    In this work, we address the concept of the chemical potential [mu] in classical and quantum gases towards the calculation of the equation of state [mu] = [mu](n, T) where n is the particle density and "T" the absolute temperature using the methods of equilibrium statistical mechanics. Two cases seldom discussed in elementary textbooks are…

  15. Chemical potential and compressibility of quantum Hall bilayer excitons,.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Skinner, Brian

    2016-02-25

    I consider a system of two parallel quantum Hall layers with total filling factor 0 or 1. When the distance between the layers is small enough, electrons and holes in opposite layers can form inter-layer excitons, which have a finite effective mass and interact via a dipole-dipole potential. I present results for the chemical potential u of the resulting bosonic system as a function of the exciton concentration n and the interlayer separation d. I show that both u and the interlayer capacitance have an unusual nonmonotonic dependence on d, owing to the interplay between an increasing dipole moment andmore » an increasing effective mass with increasing d. Finally, I discuss the transition between the superfluid and Wigner crystal phases, which is shown to occur at d x n-1/10. Results are derived first via simple intuitive arguments, and then verified with more careful analytic derivations and numeric calculations.« less

  16. Foundations of Quantum Mechanics and Quantum Computation

    NASA Astrophysics Data System (ADS)

    Aspect, Alain; Leggett, Anthony; Preskill, John; Durt, Thomas; Pironio, Stefano

    2013-03-01

    I ask the question: What can we infer about the nature and structure of the physical world (a) from experiments already done to test the predictions of quantum mechanics (b) from the assumption that all future experiments will agree with those predictions? I discuss existing and projected experiments related to the two classic paradoxes of quantum mechanics, named respectively for EPR and Schrödinger's Cat, and show in particular that one natural conclusion from both types of experiment implies the abandonment of the concept of macroscopic counterfactual definiteness.

  17. Compensation effects in molecular interactions and the quantum chemical le Chatelier principle.

    PubMed

    Mezey, Paul G

    2015-05-28

    Components of molecular interactions and various changes in the components of total energy changes during molecular processes typically exhibit some degrees of compensation. This may be as prominent as the over 90% compensation of the electronic energy and nuclear repulsion energy components of the total energy in some conformational changes. Some of these compensations are enhanced by solvent effects. For various arrangements of ions in a solvent, however, not only compensation but also a formal, mutual enhancement between the electronic energy and nuclear repulsion energy components of the total energy may also occur, when the tools of nuclear charge variation are applied to establish quantum chemically rigorous energy inequalities.

  18. Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Valerio, Luis G.; Arvidson, Kirk B.; Chanderbhan, Ronald F.

    2007-07-01

    Consistent with the U.S. Food and Drug Administration (FDA) Critical Path Initiative, predictive toxicology software programs employing quantitative structure-activity relationship (QSAR) models are currently under evaluation for regulatory risk assessment and scientific decision support for highly sensitive endpoints such as carcinogenicity, mutagenicity and reproductive toxicity. At the FDA's Center for Food Safety and Applied Nutrition's Office of Food Additive Safety and the Center for Drug Evaluation and Research's Informatics and Computational Safety Analysis Staff (ICSAS), the use of computational SAR tools for both qualitative and quantitative risk assessment applications are being developed and evaluated. One tool of current interest ismore » MDL-QSAR predictive discriminant analysis modeling of rodent carcinogenicity, which has been previously evaluated for pharmaceutical applications by the FDA ICSAS. The study described in this paper aims to evaluate the utility of this software to estimate the carcinogenic potential of small, organic, naturally occurring chemicals found in the human diet. In addition, a group of 19 known synthetic dietary constituents that were positive in rodent carcinogenicity studies served as a control group. In the test group of naturally occurring chemicals, 101 were found to be suitable for predictive modeling using this software's discriminant analysis modeling approach. Predictions performed on these compounds were compared to published experimental evidence of each compound's carcinogenic potential. Experimental evidence included relevant toxicological studies such as rodent cancer bioassays, rodent anti-carcinogenicity studies, genotoxic studies, and the presence of chemical structural alerts. Statistical indices of predictive performance were calculated to assess the utility of the predictive modeling method. Results revealed good predictive performance using this software's rodent carcinogenicity module of over 1200

  19. Demonstration of a rapidly-swept external cavity quantum cascade laser for rapid and sensitive quantification of chemical mixtures

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Brumfield, Brian E.; Taubman, Matthew S.; Phillips, Mark C.

    2016-02-13

    A rapidly-swept external cavity quantum cascade laser (ECQCL) system for fast open-path quantification of multiple chemicals and mixtures is presented. The ECQCL system is swept over its entire tuning range (>100 cm-1) at frequencies up to 200 Hz. At 200 Hz the wavelength tuning rate and spectral resolution are 2x104 cm-1/sec and < 0.2 cm-1, respectively. The capability of the current system to quantify changes in chemical concentrations on millesecond timescales is demonstrated at atmospheric pressure using an open-path multi-pass cell. The detection limits for chemicals ranged from ppb to ppm levels depending on the absorption cross-section.

  20. The Nature of the Chemical Bond--1990.

    ERIC Educational Resources Information Center

    Ogilvie, J. F.

    1990-01-01

    Three aspects of quantum mechanics in modern chemistry are stressed: the fundamental structure of quantum mechanics as a basis of chemical applications, the relationship of quantum mechanics to atomic and molecular structure, and the consequent implications for chemical education. A list of 64 references is included. (CW)

  1. Can we Predict Quantum Yields Using Excited State Density Functional Theory for New Families of Fluorescent Dyes?

    NASA Astrophysics Data System (ADS)

    Kohn, Alexander W.; Lin, Zhou; Shepherd, James J.; Van Voorhis, Troy

    2016-06-01

    For a fluorescent dye, the quantum yield characterizes the efficiency of energy transfer from the absorbed light to the emitted fluorescence. In the screening among potential families of dyes, those with higher quantum yields are expected to have more advantages. From the perspective of theoreticians, an efficient prediction of the quantum yield using a universal excited state electronic structure theory is in demand but still challenging. The most representative examples for such excited state theory include time-dependent density functional theory (TDDFT) and restricted open-shell Kohn-Sham (ROKS). In the present study, we explore the possibility of predicting the quantum yields for conventional and new families of organic dyes using a combination of TDDFT and ROKS. We focus on radiative (kr) and nonradiative (knr) rates for the decay of the first singlet excited state (S_1) into the ground state (S_0) in accordance with Kasha's rule. M. Kasha, Discuss. Faraday Soc., 9, 14 (1950). For each dye compound, kr is calculated with the S_1-S_0 energy gap and transition dipole moment obtained using ROKS and TDDFT respectively at the relaxed S_1 geometry. Our predicted kr agrees well with the experimental value, so long as the order of energy levels is correctly predicted. Evaluation of knr is less straightforward as multiple processes are involved. Our study focuses on the S_1-T_1 intersystem crossing (ISC) and the S_1-S_0 internal conversion (IC): we investigate the properties that allow us to model the knr value using a Marcus-like expression, such as the Stokes shift, the reorganization energy, and the S_1-T_1 and S_1-S_0 energy gaps. Taking these factors into consideration, we compare our results with those obtained using the actual Marcus theory and provide explanation for discrepancy. T. Kowalczyk, T. Tsuchimochi, L. Top, P.-T. Chen, and T. Van Voorhis, J. Chem. Phys., 138, 164101 (2013). M. Kasha, Discuss. Faraday Soc., 9, 14 (1950).

  2. Zirconia and its allotropes; A Quantum Monte Carlo study

    NASA Astrophysics Data System (ADS)

    Jokisaari, Andrea; Benali, Anouar; Shin, Hyeondeok; Luo, Ye; Lopez Bezanilla, Alejandro; Ratcliff, Laura; Littlewood, Peter; Heinonen, Olle

    With a high strength and stability at elevated temperatures, Zirconia (zirconium dioxide) is one of the best corrosion-resistant and refractive materials used in metallurgy, and is used in structural ceramics, catalytic converters, oxygen sensors, nuclear industry, and in chemically passivating surfaces. The wide range of applications of ZrO2 has motivated a large number of electronic structures studies of its known allotropes (monoclinic, tetragonal and cubic). Density Functional Theory has been successful at reproducing some of the fundamental properties of some of the allotropes, but these results remain dependent on the specific combination of exchange-correlation functional and type of pseudopotentials, making any type of structural prediction or defect analysis uncertain. Quantum Monte Carlo (QMC) is a many-body quantum theory solving explicitly the electronic correlations, allowing reproducing and predicting materials properties with a limited number of controlled approximations. In this study, we use QMC to revisit the energetic stability of Zirconia's allotropes and compare our results with those obtained from density functional theory.

  3. AI AND SAR APPROACHES FOR PREDICTING CHEMICAL CARCINOGENICITY: SURVEY AND STATUS REPORT

    EPA Science Inventory

    A wide variety of artificial intelligence (AI) and structure-activity relationship (SAR approaches have been applied to tackling the general problem of predicting rodent chemical carcinogenicity. Given the diversity of chemical structures and mechanisms relative to this endpoin...

  4. Spectroscopic studies and quantum chemical investigations of (3,4-dimethoxybenzylidene) propanedinitrile.

    PubMed

    Gupta, Ujval; Kumar, Vinay; Singh, Vivek K; Kant, Rajni; Khajuria, Yugal

    2015-04-05

    The Fourier Transform Infrared (FTIR), Ultra-Violet Visible (UV-Vis) spectroscopy and Thermogravimetric (TG) analysis of (3,4-dimethoxybenzylidene) propanedinitrile have been carried out and investigated using quantum chemical calculations. The molecular geometry, harmonic vibrational frequencies, Mulliken charges, natural atomic charges and thermodynamic properties in the ground state have been investigated by using Hartree Fock Theory (HF) and Density Functional Theory (DFT) using B3LYP functional with 6-311G(d,p) basis set. Both HF and DFT methods yield good agreement with the experimental data. Vibrational modes are assigned with the help of Vibrational Energy Distribution Analysis (VEDA) program. UV-Visible spectrum was recorded in the spectral range of 190-800nm and the results are compared with the calculated values using TD-DFT approach. Stability of the molecule arising from hyperconjugative interactions, charge delocalization have been analyzed using natural bond orbital (NBO) analysis. The results obtained from the studies of Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) are used to calculate molecular parameters like ionization potential, electron affinity, global hardness, electron chemical potential and global electrophilicity. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Predicting the valley physics of silicon quantum dots directly from a device layout

    NASA Astrophysics Data System (ADS)

    Gamble, John King; Harvey-Collard, Patrick; Jacobson, N. Tobias; Bacewski, Andrew D.; Nielsen, Erik; Montaño, Inès; Rudolph, Martin; Carroll, Malcolm S.; Muller, Richard P.

    Qubits made from electrostatically-defined quantum dots in Si-based systems are excellent candidates for quantum information processing applications. However, the multi-valley structure of silicon's band structure provides additional challenges for the few-electron physics critical to qubit manipulation. Here, we present a theory for valley physics that is predictive, in that we take as input the real physical device geometry and experimental voltage operation schedule, and with minimal approximation compute the resulting valley physics. We present both effective mass theory and atomistic tight-binding calculations for two distinct metal-oxide-semiconductor (MOS) quantum dot systems, directly comparing them to experimental measurements of the valley splitting. We conclude by assessing these detailed simulations' utility for engineering desired valley physics in future devices. Sandia is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the US Department of Energy's National Nuclear Security Administration under Contract No. DE-AC04-94AL85000. The authors gratefully acknowledge support from the Sandia National Laboratories Truman Fellowship Program, which is funded by the Laboratory Directed Research and Development (LDRD) Program.

  6. Quantitative structure--property relationships for enhancing predictions of synthetic organic chemical removal from drinking water by granular activated carbon.

    PubMed

    Magnuson, Matthew L; Speth, Thomas F

    2005-10-01

    Granular activated carbon is a frequently explored technology for removing synthetic organic contaminants from drinking water sources. The success of this technology relies on a number of factors based not only on the adsorptive properties of the contaminant but also on properties of the water itself, notably the presence of substances in the water which compete for adsorption sites. Because it is impractical to perform field-scale evaluations for all possible contaminants, the pore surface diffusion model (PSDM) has been developed and used to predict activated carbon column performance using single-solute isotherm data as inputs. Many assumptions are built into this model to account for kinetics of adsorption and competition for adsorption sites. This work further evaluates and expands this model, through the use of quantitative structure-property relationships (QSPRs) to predict the effect of natural organic matter fouling on activated carbon adsorption of specific contaminants. The QSPRs developed are based on a combination of calculated topographical indices and quantum chemical parameters. The QSPRs were evaluated in terms of their statistical predictive ability,the physical significance of the descriptors, and by comparison with field data. The QSPR-enhanced PSDM was judged to give results better than what could previously be obtained.

  7. Prediction of Hydrolysis Products of Organic Chemicals under Environmental pH Conditions.

    PubMed

    Tebes-Stevens, Caroline; Patel, Jay M; Jones, W Jack; Weber, Eric J

    2017-05-02

    Cheminformatics-based software tools can predict the molecular structure of transformation products using a library of transformation reaction schemes. This paper presents the development of such a library for abiotic hydrolysis of organic chemicals under environmentally relevant conditions. The hydrolysis reaction schemes in the library encode the process science gathered from peer-reviewed literature and regulatory reports. Each scheme has been ranked on a scale of one to six based on the median half-life in a data set compiled from literature-reported hydrolysis rates. These ranks are used to predict the most likely transformation route when more than one structural fragment susceptible to hydrolysis is present in a molecule of interest. Separate rank assignments are established for pH 5, 7, and 9 to represent standard conditions in hydrolysis studies required for registration of pesticides in Organisation for Economic Co-operation and Development (OECD) member countries. The library is applied to predict the likely hydrolytic transformation products for two lists of chemicals, one representative of chemicals used in commerce and the other specific to pesticides, to evaluate which hydrolysis reaction pathways are most likely to be relevant for organic chemicals found in the natural environment.

  8. Chemical processing of three-dimensional graphene networks on transparent conducting electrodes for depleted-heterojunction quantum dot solar cells.

    PubMed

    Tavakoli, Mohammad Mahdi; Simchi, Abdolreza; Fan, Zhiyong; Aashuri, Hossein

    2016-01-07

    We present a novel chemical procedure to prepare three-dimensional graphene networks (3DGNs) as a transparent conductive film to enhance the photovoltaic performance of PbS quantum-dot (QD) solar cells. It is shown that 3DGN electrodes enhance electron extraction, yielding a 30% improvement in performance compared with the conventional device.

  9. Efficient prediction of terahertz quantum cascade laser dynamics from steady-state simulations

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Agnew, G.; Lim, Y. L.; Nikolić, M.

    2015-04-20

    Terahertz-frequency quantum cascade lasers (THz QCLs) based on bound-to-continuum active regions are difficult to model owing to their large number of quantum states. We present a computationally efficient reduced rate equation (RE) model that reproduces the experimentally observed variation of THz power with respect to drive current and heat-sink temperature. We also present dynamic (time-domain) simulations under a range of drive currents and predict an increase in modulation bandwidth as the current approaches the peak of the light–current curve, as observed experimentally in mid-infrared QCLs. We account for temperature and bias dependence of the carrier lifetimes, gain, and injection efficiency,more » calculated from a full rate equation model. The temperature dependence of the simulated threshold current, emitted power, and cut-off current are thus all reproduced accurately with only one fitting parameter, the interface roughness, in the full REs. We propose that the model could therefore be used for rapid dynamical simulation of QCL designs.« less

  10. Advances in Quantum Mechanochemistry: Electronic Structure Methods and Force Analysis.

    PubMed

    Stauch, Tim; Dreuw, Andreas

    2016-11-23

    In quantum mechanochemistry, quantum chemical methods are used to describe molecules under the influence of an external force. The calculation of geometries, energies, transition states, reaction rates, and spectroscopic properties of molecules on the force-modified potential energy surfaces is the key to gain an in-depth understanding of mechanochemical processes at the molecular level. In this review, we present recent advances in the field of quantum mechanochemistry and introduce the quantum chemical methods used to calculate the properties of molecules under an external force. We place special emphasis on quantum chemical force analysis tools, which can be used to identify the mechanochemically relevant degrees of freedom in a deformed molecule, and spotlight selected applications of quantum mechanochemical methods to point out their synergistic relationship with experiments.

  11. Real quantum cybernetics

    NASA Astrophysics Data System (ADS)

    Grössing, Gerhard

    1987-05-01

    It is shown on the basis of quantum cybernetics that one can obtain the usual predictions of quantum theory without ever referring to complex numbered “quantum mechanical amplitudes”. Instead, a very simple formula for transition and certain conditional probabilities is developed that involves real numbers only, thus relating intuitively understandable and in principle directly observable physical quantities.

  12. Intermediate quantum maps for quantum computation

    NASA Astrophysics Data System (ADS)

    Giraud, O.; Georgeot, B.

    2005-10-01

    We study quantum maps displaying spectral statistics intermediate between Poisson and Wigner-Dyson. It is shown that they can be simulated on a quantum computer with a small number of gates, and efficiently yield information about fidelity decay or spectral statistics. We study their matrix elements and entanglement production and show that they converge with time to distributions which differ from random matrix predictions. A randomized version of these maps can be implemented even more economically and yields pseudorandom operators with original properties, enabling, for example, one to produce fractal random vectors. These algorithms are within reach of present-day quantum computers.

  13. A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes.

    PubMed

    Chen, Lei; Lu, Jing; Zhang, Ning; Huang, Tao; Cai, Yu-Dong

    2014-04-01

    In the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), provides a global standard for classifying medical substances and serves as a tool for international drug utilization research to improve quality of drug use. In view of this, it is necessary to develop effective computational prediction methods to identify the ATC-class of a given drug, which thereby could facilitate further analysis of this system. In this study, we initiated an attempt to develop a prediction method and to gain insights from it by utilizing ontology information of drug compounds. Since only about one-fourth of drugs in the ATC classification system have ontology information, a hybrid prediction method combining the ontology information, chemical interaction information and chemical structure information of drug compounds was proposed for the prediction of drug ATC-classes. As a result, by using the Jackknife test, the 1st prediction accuracies for identifying the 14 main ATC-classes in the training dataset, the internal validation dataset and the external validation dataset were 75.90%, 75.70% and 66.36%, respectively. Analysis of some samples with false-positive predictions in the internal and external validation datasets indicated that some of them may even have a relationship with the false-positive predicted ATC-class, suggesting novel uses of these drugs. It was conceivable that the proposed method could be used as an efficient tool to identify ATC-classes of novel drugs or to discover novel uses of known drugs.

  14. Prediction of tautomer ratios by embedded-cluster integral equation theory

    NASA Astrophysics Data System (ADS)

    Kast, Stefan M.; Heil, Jochen; Güssregen, Stefan; Schmidt, K. Friedemann

    2010-04-01

    The "embedded cluster reference interaction site model" (EC-RISM) approach combines statistical-mechanical integral equation theory and quantum-chemical calculations for predicting thermodynamic data for chemical reactions in solution. The electronic structure of the solute is determined self-consistently with the structure of the solvent that is described by 3D RISM integral equation theory. The continuous solvent-site distribution is mapped onto a set of discrete background charges ("embedded cluster") that represent an additional contribution to the molecular Hamiltonian. The EC-RISM analysis of the SAMPL2 challenge set of tautomers proceeds in three stages. Firstly, the group of compounds for which quantitative experimental free energy data was provided was taken to determine appropriate levels of quantum-chemical theory for geometry optimization and free energy prediction. Secondly, the resulting workflow was applied to the full set, allowing for chemical interpretations of the results. Thirdly, disclosure of experimental data for parts of the compounds facilitated a detailed analysis of methodical issues and suggestions for future improvements of the model. Without specifically adjusting parameters, the EC-RISM model yields the smallest value of the root mean square error for the first set (0.6 kcal mol-1) as well as for the full set of quantitative reaction data (2.0 kcal mol-1) among the SAMPL2 participants.

  15. Structure activity studies of an analgesic drug tapentadol hydrochloride by spectroscopic and quantum chemical methods

    NASA Astrophysics Data System (ADS)

    Arjunan, V.; Santhanam, R.; Marchewka, M. K.; Mohan, S.; Yang, Haifeng

    2015-11-01

    Tapentadol is a novel opioid pain reliever drug with a dual mechanism of action, having potency between morphine and tramadol. Quantum chemical calculations have been carried out for tapentadol hydrochloride (TAP.Cl) to determine the properties. The geometry is optimised and the structural properties of the compound were determined from the optimised geometry by B3LYP method using 6-311++G(d,p), 6-31G(d,p) and cc-pVDZ basis sets. FT-IR and FT-Raman spectra are recorded in the solid phase in the region of 4000-400 and 4000-100 cm-1, respectively. Frontier molecular orbital energies, LUMO-HOMO energy gap, ionisation potential, electron affinity, electronegativity, hardness and chemical potential are also calculated. The stability of the molecule arising from hyperconjugative interactions and charge delocalisation has been analysed using NBO analysis. The 1H and 13C nuclear magnetic resonance chemical shifts of the molecule are analysed.

  16. The limits of predictability: Indeterminism and undecidability in classical and quantum physics

    NASA Astrophysics Data System (ADS)

    Korolev, Alexandre V.

    This thesis is a collection of three case studies, investigating various sources of indeterminism and undecidability as they bear upon in principle unpredictability of the behaviour of mechanistic systems in both classical and quantum physics. I begin by examining the sources of indeterminism and acausality in classical physics. Here I discuss the physical significance of an often overlooked and yet important Lipschitz condition, the violation of which underlies the existence of anomalous non-trivial solutions in the Norton-type indeterministic systems. I argue that the singularity arising from the violation of the Lipschitz condition in the systems considered appears to be so fragile as to be easily destroyed by slightly relaxing certain (infinite) idealizations required by these models. In particular, I show that the idealization of an absolutely nondeformable, or infinitely rigid, dome appears to be an essential assumption for anomalous motion to begin; any slightest elastic deformations of the dome due to finite rigidity of the dome destroy the shape of the dome required for indeterminism to obtain. I also consider several modifications of the original Norton's example and show that indeterminism in these cases, too, critically depends on the nature of certain idealizations pertaining to elastic properties of the bodies in these models. As a result, I argue that indeterminism of the Norton-type Lipschitz-indeterministic systems should rather be viewed as an artefact of certain (infinite) idealizations essential for the models, depriving the examples of much of their intended metaphysical import, as, for example, in Norton's antifundamentalist programme. Second, I examine the predictive computational limitations of a classical Laplace's demon. I demonstrate that in situations of self-fulfilling prognoses the class of undecidable propositions about certain future events, in general, is not empty; any Laplace's demon having all the information about the world now

  17. Interactions of ionic liquids and acetone: thermodynamic properties, quantum-chemical calculations, and NMR analysis.

    PubMed

    Ruiz, Elia; Ferro, Victor R; Palomar, Jose; Ortega, Juan; Rodriguez, Juan Jose

    2013-06-20

    The interactions between ionic liquids (ILs) and acetone have been studied to obtain a further understanding of the behavior of their mixtures, which generally give place to an exothermic process, mutual miscibility, and negative deviation of Raoult's law. COSMO-RS was used as a suitable computational method to systematically analyze the excess enthalpy of IL-acetone systems (>300), in terms of the intermolecular interactions contributing to the mixture behavior. Spectroscopic and COSMO-RS results indicated that acetone, as a polar compound with strong hydrogen bond acceptor character, in most cases, establishes favorable hydrogen bonding with ILs. This interaction is strengthened by the presence of an acidic cation and an anion with dispersed charge and non-HB acceptor character in the IL. COSMO-RS predictions indicated that gas-liquid and vapor-liquid equilibrium data for IL-acetone systems can be finely tuned by the IL selection, that is, acting on the intermolecular interactions between the molecular and ionic species in the liquid phase. NMR measurements for IL-acetone mixtures at different concentrations were also carried out. Quantum-chemical calculations by using molecular clusters of acetone and IL species were finally performed. These results provided additional evidence of the main role played by hydrogen bonding in the behavior of systems containing ILs and HB acceptor compounds, such as acetone.

  18. Bond Order and Chemical Properties of BF, CO, and N[subscript 2

    ERIC Educational Resources Information Center

    Martinie, Ryan J.; Bultema, Jarred J.; Vander Wal, Mark N.; Burkhart, Brandon J.; Vander Griend, Douglas A.; DeKock, Roger L.

    2011-01-01

    The traditional chemical approaches, Lewis electron dot structures and molecular orbital theory, predict the relative bond orders of boron monofluoride, carbon monoxide, and dinitrogen to be BF less than CO less than N[subscript 2]. This is quantified by quantum mechanical, theoretical studies that show the bond orders to be approximately 1.4,…

  19. EPA's ToxCast Program for Predicting Hazard and Prioritizing the Toxicity Testing of Environmental Chemicals

    EPA Science Inventory

    An alternative is to perform a set of relatively inexpensive and rapid high throughput screening (HTS) assays, derive signatures predictive of effects or modes of chemical toxicity from the HTS data, then use these predictions to prioritize chemicals for more detailed analysis. T...

  20. Continuous quantum measurement and the quantum to classical transition

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bhattacharya, Tanmoy; Habib, Salman; Jacobs, Kurt

    2003-04-01

    While ultimately they are described by quantum mechanics, macroscopic mechanical systems are nevertheless observed to follow the trajectories predicted by classical mechanics. Hence, in the regime defining macroscopic physics, the trajectories of the correct classical motion must emerge from quantum mechanics, a process referred to as the quantum to classical transition. Extending previous work [Bhattacharya, Habib, and Jacobs, Phys. Rev. Lett. 85, 4852 (2000)], here we elucidate this transition in some detail, showing that once the measurement processes that affect all macroscopic systems are taken into account, quantum mechanics indeed predicts the emergence of classical motion. We derive inequalities thatmore » describe the parameter regime in which classical motion is obtained, and provide numerical examples. We also demonstrate two further important properties of the classical limit: first, that multiple observers all agree on the motion of an object, and second, that classical statistical inference may be used to correctly track the classical motion.« less

  1. Thermodynamics and proton activities of protic ionic liquids with quantum cluster equilibrium theory

    NASA Astrophysics Data System (ADS)

    Ingenmey, Johannes; von Domaros, Michael; Perlt, Eva; Verevkin, Sergey P.; Kirchner, Barbara

    2018-05-01

    We applied the binary Quantum Cluster Equilibrium (bQCE) method to a number of alkylammonium-based protic ionic liquids in order to predict boiling points, vaporization enthalpies, and proton activities. The theory combines statistical thermodynamics of van-der-Waals-type clusters with ab initio quantum chemistry and yields the partition functions (and associated thermodynamic potentials) of binary mixtures over a wide range of thermodynamic phase points. Unlike conventional cluster approaches that are limited to the prediction of thermodynamic properties, dissociation reactions can be effortlessly included into the bQCE formalism, giving access to ionicities, as well. The method is open to quantum chemical methods at any level of theory, but combination with low-cost composite density functional theory methods and the proposed systematic approach to generate cluster sets provides a computationally inexpensive and mostly parameter-free way to predict such properties at good-to-excellent accuracy. Boiling points can be predicted within an accuracy of 50 K, reaching excellent accuracy for ethylammonium nitrate. Vaporization enthalpies are predicted within an accuracy of 20 kJ mol-1 and can be systematically interpreted on a molecular level. We present the first theoretical approach to predict proton activities in protic ionic liquids, with results fitting well into the experimentally observed correlation. Furthermore, enthalpies of vaporization were measured experimentally for some alkylammonium nitrates and an excellent linear correlation with vaporization enthalpies of their respective parent amines is observed.

  2. Studies on the Conformational Landscape of Tert-Butyl Acetate Using Microwave Spectroscopy and Quantum Chemical Calculations

    NASA Astrophysics Data System (ADS)

    Zhao, YueYue; Mouhib, Halima; Li, Guohua; Stahl, Wolfgang; Kleiner, Isabelle

    2014-06-01

    The tert-Butyl acetate molecule was studied using a combination of quantum chemical calculations and molecular beam Fourier transform microwave spectroscopy in the 9 to 14 GHz range. Due to its rather rigid frame, the molecule possesses only two different conformers: one of Cs and one of C1 symmetry. According to ab initio calculations, the Cs conformer is 46 kJ/mol lower in energy and is the one observed in the supersonic jet. We report on the structure and dynamics of the most abundant conformer of tert-butyl acetate, with accurate rotational and centrifugal distortion constants. Additionally, the barrier to internal rotation of the acetyl methyl group was determined. Splittings due to the internal rotation of the methyl group of up to 1.3 GHz were observed in the spectrum. Using the programs XIAM and BELGI-Cs, we determine the barrier height to be about 113 cm-1 and compare the molecular parameters obtained from these two codes. Additionally, the experimental rotational constants were used to validate numerous quantum chemical calculations. This study is part of a larger project which aims at determining the lowest energy conformers of organic esters and ketones which are of interest for flavor or perfume synthetic applications Project partly supported by the PHC PROCOPE 25059YB.

  3. Portable open-path chemical sensor using a quantum cascade laser

    NASA Astrophysics Data System (ADS)

    Corrigan, Paul; Lwin, Maung; Huntley, Reuven; Chhabra, Amandeep; Moshary, Fred; Gross, Barry; Ahmed, Samir

    2009-05-01

    Remote sensing of enemy installations or their movements by trace gas detection is a critical but challenging military objective. Open path measurements over ranges of a few meters to many kilometers with sensitivity in the parts per million or billion regime are crucial in anticipating the presence of a threat. Previous approaches to detect ground level chemical plumes, explosive constituents, or combustion have relied on low-resolution, short range Fourier transform infrared spectrometer (FTIR), or low-sensitivity near-infrared differential optical absorption spectroscopy (DOAS). As mid-infrared quantum cascade laser (QCL) sources have improved in cost and performance, systems based on QCL's that can be tailored to monitor multiple chemical species in real time are becoming a viable alternative. We present the design of a portable, high-resolution, multi-kilometer open path trace gas sensor based on QCL technology. Using a tunable (1045-1047cm-1) QCL, a modeled atmosphere and link-budget analysis with commercial component specifications, we show that with this approach, accuracy in parts per billion ozone or ammonia can be obtained in seconds at path lengths up to 10 km. We have assembled an open-path QCL sensor based on this theoretical approach at City College of New York, and we present preliminary results demonstrating the potential of QCLs in open-path sensing applications.

  4. Photodissociation of quantum state-selected diatomic molecules yields new insight into ultracold chemistry

    NASA Astrophysics Data System (ADS)

    McDonald, Mickey; McGuyer, Bart H.; Lee, Chih-Hsi; Apfelbeck, Florian; Zelevinsky, Tanya

    2016-05-01

    When a molecule is subjected to a sufficiently energetic photon it can break apart into fragments through a process called ``photodissociation''. For over 70 years this simple chemical reaction has served as a vital experimental tool for acquiring information about molecular structure, since the character of the photodissociative transition can be inferred by measuring the 3D photofragment angular distribution (PAD). While theoretical understanding of this process has gradually evolved from classical considerations to a fully quantum approach, experiments to date have not yet revealed the full quantum nature of this process. In my talk I will describe recent experiments involving the photodissociation of ultracold, optical lattice-trapped, and fully quantum state-resolved 88Sr2 molecules. Optical absorption images of the PADs produced in these experiments reveal features which are inherently quantum mechanical in nature, such as matter-wave interference between output channels, and are sensitive to the quantum statistics of the molecular wavefunctions. The results of these experiments cannot be predicted using quasiclassical methods. Instead, we describe our results with a fully quantum mechanical model yielding new intuition about ultracold chemistry.

  5. Computer-Aided Construction of Chemical Kinetic Models

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Green, William H.

    2014-12-31

    The combustion chemistry of even simple fuels can be extremely complex, involving hundreds or thousands of kinetically significant species. The most reasonable way to deal with this complexity is to use a computer not only to numerically solve the kinetic model, but also to construct the kinetic model in the first place. Because these large models contain so many numerical parameters (e.g. rate coefficients, thermochemistry) one never has sufficient data to uniquely determine them all experimentally. Instead one must work in “predictive” mode, using theoretical rather than experimental values for many of the numbers in the model, and as appropriatemore » refining the most sensitive numbers through experiments. Predictive chemical kinetics is exactly what is needed for computer-aided design of combustion systems based on proposed alternative fuels, particularly for early assessment of the value and viability of proposed new fuels before those fuels are commercially available. This project was aimed at making accurate predictive chemical kinetics practical; this is a challenging goal which requires a range of science advances. The project spanned a wide range from quantum chemical calculations on individual molecules and elementary-step reactions, through the development of improved rate/thermo calculation procedures, the creation of algorithms and software for constructing and solving kinetic simulations, the invention of methods for model-reduction while maintaining error control, and finally comparisons with experiment. Many of the parameters in the models were derived from quantum chemistry calculations, and the models were compared with experimental data measured in our lab or in collaboration with others.« less

  6. The role of NH3 and hydrocarbon mixtures in GaN pseudo-halide CVD: a quantum chemical study.

    PubMed

    Gadzhiev, Oleg B; Sennikov, Peter G; Petrov, Alexander I; Kachel, Krzysztof; Golka, Sebastian; Gogova, Daniela; Siche, Dietmar

    2014-11-01

    The prospects of a control for a novel gallium nitride pseudo-halide vapor phase epitaxy (PHVPE) with HCN were thoroughly analyzed for hydrocarbons-NH3-Ga gas phase on the basis of quantum chemical investigation with DFT (B3LYP, B3LYP with D3 empirical correction on dispersion interaction) and ab-initio (CASSCF, coupled clusters, and multireference configuration interaction including MRCI+Q) methods. The computational screening of reactions for different hydrocarbons (CH4, C2H6, C3H8, C2H4, and C2H2) as readily available carbon precursors for HCN formation, potential chemical transport agents, and for controlled carbon doping of deposited GaN was carried out with the B3LYP method in conjunction with basis sets up to aug-cc-pVTZ. The gas phase intermediates for the reactions in the Ga-hydrocarbon systems were predicted at different theory levels. The located π-complexes Ga…C2H2 and Ga…C2H4 were studied to determine a probable catalytic activity in reactions with NH3. A limited influence of the carbon-containing atmosphere was exhibited for the carbon doping of GaN crystal in the conventional GaN chemical vapor deposition (CVD) process with hydrocarbons injected in the gas phase. Our results provide a basis for experimental studies of GaN crystal growth with C2H4 and C2H2 as auxiliary carbon reagents for the Ga-NH3 and Ga-C-NH3 CVD systems and prerequisites for reactor design to enhance and control the PHVPE process through the HCN synthesis.

  7. POSSIBLE NATURE OF THE RADIATION-INDUCED SIGNAL IN NAILS: HIGH-FIELD EPR, CONFIRMING CHEMICAL SYNTHESIS, AND QUANTUM CHEMICAL CALCULATIONS

    PubMed Central

    Tipikin, Dmitriy S.; Swarts, Steven G.; Sidabras, Jason W.; Trompier, François; Swartz, Harold M.

    2016-01-01

    Exposure of finger- and toe-nails to ionizing radiation generates an Electron Paramagnetic Resonance (EPR) signal whose intensity is dose dependent and stable at room temperature for several days. The dependency of the radiation-induced signal (RIS) on the received dose may be used as the basis for retrospective dosimetry of an individual's fortuitous exposure to ionizing radiation. Two radiation-induced signals, a quasi-stable (RIS2) and stable signal (RIS5), have been identified in nails irradiated up to a dose of 50 Gy. Using X-band EPR, both RIS signals exhibit a singlet line shape with a line width around 1.0 mT and an apparent g-value of 2.0044. In this work, we seek information on the exact chemical nature of the radiation-induced free radicals underlying the signal. This knowledge may provide insights into the reason for the discrepancy in the stabilities of the two RIS signals and help develop strategies for stabilizing the radicals in nails or devising methods for restoring the radicals after decay. In this work an analysis of high field (94 GHz and 240 GHz) EPR spectra of the RIS using quantum chemical calculations, the oxidation–reduction properties and the pH dependence of the signal intensities are used to show that spectroscopic and chemical properties of the RIS are consistent with a semiquinone-type radical underlying the RIS. It has been suggested that semiquinone radicals formed on trace amounts of melanin in nails are the basis for the RIS signals. However, based on the quantum chemical calculations and chemical properties of the RIS, it is likely that the radicals underlying this signal are generated from the radiolysis of L-3,4-dihydroxyphenylalanine (DOPA) amino acids in the keratin proteins. These DOPA amino acids are likely formed from the exogenous oxidation of tyrosine in keratin by the oxygen from the air prior to irradiation. We show that these DOPA amino acids can work as radical traps, capturing the highly reactive and unstable

  8. ToxCast: Developing Predictive Signatures of Chemically Induced Toxicity (S)

    EPA Science Inventory

    ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry, bioactivity profiling and toxicogenomic data to predict potential for toxicity and prioritize limited testing resour...

  9. Ab Initio-Based Predictions of Hydrocarbon Combustion Chemistry

    DTIC Science & Technology

    2015-07-15

    There are two prime objectives of the research. One is to develop and apply efficient methods for using ab initio potential energy surfaces (PESs...31-Mar-2015 Approved for Public Release; Distribution Unlimited Final Report: Ab Initio -Based Predictions of Hydrocarbon Combustion Chemistry The...Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 hydrocarbon combustion, ab initio quantum chemistry, potential energy surfaces, chemical

  10. Enhanced NMR Discrimination of Pharmaceutically Relevant Molecular Crystal Forms through Fragment-Based Ab Initio Chemical Shift Predictions.

    PubMed

    Hartman, Joshua D; Day, Graeme M; Beran, Gregory J O

    2016-11-02

    Chemical shift prediction plays an important role in the determination or validation of crystal structures with solid-state nuclear magnetic resonance (NMR) spectroscopy. One of the fundamental theoretical challenges lies in discriminating variations in chemical shifts resulting from different crystallographic environments. Fragment-based electronic structure methods provide an alternative to the widely used plane wave gauge-including projector augmented wave (GIPAW) density functional technique for chemical shift prediction. Fragment methods allow hybrid density functionals to be employed routinely in chemical shift prediction, and we have recently demonstrated appreciable improvements in the accuracy of the predicted shifts when using the hybrid PBE0 functional instead of generalized gradient approximation (GGA) functionals like PBE. Here, we investigate the solid-state 13 C and 15 N NMR spectra for multiple crystal forms of acetaminophen, phenobarbital, and testosterone. We demonstrate that the use of the hybrid density functional instead of a GGA provides both higher accuracy in the chemical shifts and increased discrimination among the different crystallographic environments. Finally, these results also provide compelling evidence for the transferability of the linear regression parameters mapping predicted chemical shieldings to chemical shifts that were derived in an earlier study.

  11. Enhanced NMR Discrimination of Pharmaceutically Relevant Molecular Crystal Forms through Fragment-Based Ab Initio Chemical Shift Predictions

    PubMed Central

    2016-01-01

    Chemical shift prediction plays an important role in the determination or validation of crystal structures with solid-state nuclear magnetic resonance (NMR) spectroscopy. One of the fundamental theoretical challenges lies in discriminating variations in chemical shifts resulting from different crystallographic environments. Fragment-based electronic structure methods provide an alternative to the widely used plane wave gauge-including projector augmented wave (GIPAW) density functional technique for chemical shift prediction. Fragment methods allow hybrid density functionals to be employed routinely in chemical shift prediction, and we have recently demonstrated appreciable improvements in the accuracy of the predicted shifts when using the hybrid PBE0 functional instead of generalized gradient approximation (GGA) functionals like PBE. Here, we investigate the solid-state 13C and 15N NMR spectra for multiple crystal forms of acetaminophen, phenobarbital, and testosterone. We demonstrate that the use of the hybrid density functional instead of a GGA provides both higher accuracy in the chemical shifts and increased discrimination among the different crystallographic environments. Finally, these results also provide compelling evidence for the transferability of the linear regression parameters mapping predicted chemical shieldings to chemical shifts that were derived in an earlier study. PMID:27829821

  12. Wavy carbon: A new series of carbon structures explored by quantum chemical calculations

    NASA Astrophysics Data System (ADS)

    Ohno, Koichi; Satoh, Hiroko; Iwamoto, Takeaki; Tokoyama, Hiroaki; Yamakado, Hideo

    2015-10-01

    A new carbon family adopting wavy structures has been found by quantum chemical calculations. The key motif of this family is a condensed four-membered ring. Periodically wavy-carbon sheets (wavy-Cn sheets, n = 2, 6, and 8) as well as wavy-C36 tube were found to be very similar to the previously reported prism-Cn carbon tubes (n = 5, 6, and 8) in several respects, including the relative energies per one carbon atom with respect to graphene, CC bond lengths, and CCC bond angles. Because of very high relative energies with respect to graphene (206-253 kJ mol-1), the wavy-carbons may behave as energy reserving materials.

  13. Chemical combination effects predict connectivity in biological systems

    PubMed Central

    Lehár, Joseph; Zimmermann, Grant R; Krueger, Andrew S; Molnar, Raymond A; Ledell, Jebediah T; Heilbut, Adrian M; Short, Glenn F; Giusti, Leanne C; Nolan, Garry P; Magid, Omar A; Lee, Margaret S; Borisy, Alexis A; Stockwell, Brent R; Keith, Curtis T

    2007-01-01

    Efforts to construct therapeutically useful models of biological systems require large and diverse sets of data on functional connections between their components. Here we show that cellular responses to combinations of chemicals reveal how their biological targets are connected. Simulations of pathways with pairs of inhibitors at varying doses predict distinct response surface shapes that are reproduced in a yeast experiment, with further support from a larger screen using human tumour cells. The response morphology yields detailed connectivity constraints between nearby targets, and synergy profiles across many combinations show relatedness between targets in the whole network. Constraints from chemical combinations complement genetic studies, because they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. After extending this initial study to cover a wider range of combination effects and pathway topologies, chemical combinations may be used to refine network models or to identify novel targets. This response surface methodology may even apply to non-biological systems where responses to targeted perturbations can be measured. PMID:17332758

  14. Comparative study of biodegradability prediction of chemicals using decision trees, functional trees, and logistic regression.

    PubMed

    Chen, Guangchao; Li, Xuehua; Chen, Jingwen; Zhang, Ya-Nan; Peijnenburg, Willie J G M

    2014-12-01

    Biodegradation is the principal environmental dissipation process of chemicals. As such, it is a dominant factor determining the persistence and fate of organic chemicals in the environment, and is therefore of critical importance to chemical management and regulation. In the present study, the authors developed in silico methods assessing biodegradability based on a large heterogeneous set of 825 organic compounds, using the techniques of the C4.5 decision tree, the functional inner regression tree, and logistic regression. External validation was subsequently carried out by 2 independent test sets of 777 and 27 chemicals. As a result, the functional inner regression tree exhibited the best predictability with predictive accuracies of 81.5% and 81.0%, respectively, on the training set (825 chemicals) and test set I (777 chemicals). Performance of the developed models on the 2 test sets was subsequently compared with that of the Estimation Program Interface (EPI) Suite Biowin 5 and Biowin 6 models, which also showed a better predictability of the functional inner regression tree model. The model built in the present study exhibits a reasonable predictability compared with existing models while possessing a transparent algorithm. Interpretation of the mechanisms of biodegradation was also carried out based on the models developed. © 2014 SETAC.

  15. Quantum chemical calculations to determine partitioning coefficients for HgCl2 on iron-oxide aerosols.

    PubMed

    Tacey, Sean A; Xu, Lang; Szilvási, Tibor; Schauer, James J; Mavrikakis, Manos

    2018-04-30

    Gas-to-particle phase partitioning controls the pathways for oxidized mercury deposition from the atmosphere to the Earth's surface. The propensity of oxidized mercury species to transition between these two phases is described by the partitioning coefficient (K p ). Experimental measurements of K p values for HgCl 2 in the presence of atmospheric aerosols are difficult and time-consuming. Quantum chemical calculations, therefore, offer a promising opportunity to efficiently estimate partitioning coefficients for HgCl 2 on relevant aerosols. In this study, density functional theory (DFT) calculations are used to predict K p values for HgCl 2 on relevant iron-oxide surfaces. The model is first verified using a NaCl(100) surface, showing good agreement between the calculated (2.8) and experimental (29-43) dimensionless partitioning coefficients at room temperature. Then, the methodology is applied to six atmospherically relevant terminations of α-Fe 2 O 3 (0001): OH-Fe-R, (OH) 3 -Fe-R, (OH) 3 -R, O-Fe-R, Fe-O 3 -R, and O 3 -R (where R denotes bulk ordering). The OH-Fe-R termination is predicted to be the most stable under typical atmospheric conditions, and on this surface termination, a dimensionless HgCl 2 K p value of 5.2 × 10 3 at 295 K indicates a strong preference for the particle phase. This work demonstrates DFT as a promising approach to obtain partitioning coefficients, which can lead to improved models for the transport of mercury, as well as for other atmospheric pollutant species, through and between the anthroposphere and troposphere. Copyright © 2018 Elsevier B.V. All rights reserved.

  16. Toward prethreshold gate-based quantum simulation of chemical dynamics: using potential energy surfaces to simulate few-channel molecular collisions

    DOE PAGES

    Sornborger, Andrew Tyler; Stancil, Phillip; Geller, Michael R.

    2018-03-22

    Here, one of the most promising applications of an error-corrected universal quantum computer is the efficient simulation of complex quantum systems such as large molecular systems. In this application, one is interested in both the electronic structure such as the ground state energy and dynamical properties such as the scattering cross section and chemical reaction rates. However, most theoretical work and experimental demonstrations have focused on the quantum computation of energies and energy surfaces. In this work, we attempt to make the prethreshold (not error-corrected) quantum simulation of dynamical properties practical as well. We show that the use of precomputedmore » potential energy surfaces and couplings enables the gate-based simulation of few-channel but otherwise realistic molecular collisions. Our approach is based on the widely used Born–Oppenheimer approximation for the structure problem coupled with a semiclassical method for the dynamics. In the latter the electrons are treated quantum mechanically but the nuclei are classical, which restricts the collisions to high energy or temperature (typically above ≈10 eV). By using operator splitting techniques optimized for the resulting time-dependent Hamiltonian simulation problem, we give several physically realistic collision examples, with 3–8 channels and circuit depths < 1000.« less

  17. Toward prethreshold gate-based quantum simulation of chemical dynamics: using potential energy surfaces to simulate few-channel molecular collisions

    NASA Astrophysics Data System (ADS)

    Sornborger, Andrew T.; Stancil, Phillip; Geller, Michael R.

    2018-05-01

    One of the most promising applications of an error-corrected universal quantum computer is the efficient simulation of complex quantum systems such as large molecular systems. In this application, one is interested in both the electronic structure such as the ground state energy and dynamical properties such as the scattering cross section and chemical reaction rates. However, most theoretical work and experimental demonstrations have focused on the quantum computation of energies and energy surfaces. In this work, we attempt to make the prethreshold (not error-corrected) quantum simulation of dynamical properties practical as well. We show that the use of precomputed potential energy surfaces and couplings enables the gate-based simulation of few-channel but otherwise realistic molecular collisions. Our approach is based on the widely used Born-Oppenheimer approximation for the structure problem coupled with a semiclassical method for the dynamics. In the latter the electrons are treated quantum mechanically but the nuclei are classical, which restricts the collisions to high energy or temperature (typically above ≈ 10 eV). By using operator splitting techniques optimized for the resulting time-dependent Hamiltonian simulation problem, we give several physically realistic collision examples, with 3-8 channels and circuit depths < 1000.

  18. Toward prethreshold gate-based quantum simulation of chemical dynamics: using potential energy surfaces to simulate few-channel molecular collisions

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sornborger, Andrew Tyler; Stancil, Phillip; Geller, Michael R.

    Here, one of the most promising applications of an error-corrected universal quantum computer is the efficient simulation of complex quantum systems such as large molecular systems. In this application, one is interested in both the electronic structure such as the ground state energy and dynamical properties such as the scattering cross section and chemical reaction rates. However, most theoretical work and experimental demonstrations have focused on the quantum computation of energies and energy surfaces. In this work, we attempt to make the prethreshold (not error-corrected) quantum simulation of dynamical properties practical as well. We show that the use of precomputedmore » potential energy surfaces and couplings enables the gate-based simulation of few-channel but otherwise realistic molecular collisions. Our approach is based on the widely used Born–Oppenheimer approximation for the structure problem coupled with a semiclassical method for the dynamics. In the latter the electrons are treated quantum mechanically but the nuclei are classical, which restricts the collisions to high energy or temperature (typically above ≈10 eV). By using operator splitting techniques optimized for the resulting time-dependent Hamiltonian simulation problem, we give several physically realistic collision examples, with 3–8 channels and circuit depths < 1000.« less

  19. Materials Frontiers to Empower Quantum Computing

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Taylor, Antoinette Jane; Sarrao, John Louis; Richardson, Christopher

    This is an exciting time at the nexus of quantum computing and materials research. The materials frontiers described in this report represent a significant advance in electronic materials and our understanding of the interactions between the local material and a manufactured quantum state. Simultaneously, directed efforts to solve materials issues related to quantum computing provide an opportunity to control and probe the fundamental arrangement of matter that will impact all electronic materials. An opportunity exists to extend our understanding of materials functionality from electronic-grade to quantum-grade by achieving a predictive understanding of noise and decoherence in qubits and their originsmore » in materials defects and environmental coupling. Realizing this vision systematically and predictively will be transformative for quantum computing and will represent a qualitative step forward in materials prediction and control.« less

  20. Quantum Hall resistance standards from graphene grown by chemical vapour deposition on silicon carbide

    NASA Astrophysics Data System (ADS)

    Lafont, F.; Ribeiro-Palau, R.; Kazazis, D.; Michon, A.; Couturaud, O.; Consejo, C.; Chassagne, T.; Zielinski, M.; Portail, M.; Jouault, B.; Schopfer, F.; Poirier, W.

    2015-04-01

    Replacing GaAs by graphene to realize more practical quantum Hall resistance standards (QHRS), accurate to within 10-9 in relative value, but operating at lower magnetic fields than 10 T, is an ongoing goal in metrology. To date, the required accuracy has been reported, only few times, in graphene grown on SiC by Si sublimation, under higher magnetic fields. Here, we report on a graphene device grown by chemical vapour deposition on SiC, which demonstrates such accuracies of the Hall resistance from 10 T up to 19 T at 1.4 K. This is explained by a quantum Hall effect with low dissipation, resulting from strongly localized bulk states at the magnetic length scale, over a wide magnetic field range. Our results show that graphene-based QHRS can replace their GaAs counterparts by operating in as-convenient cryomagnetic conditions, but over an extended magnetic field range. They rely on a promising hybrid and scalable growth method and a fabrication process achieving low-electron-density devices.

  1. Quantum Hall resistance standards from graphene grown by chemical vapour deposition on silicon carbide

    PubMed Central

    Lafont, F.; Ribeiro-Palau, R.; Kazazis, D.; Michon, A.; Couturaud, O.; Consejo, C.; Chassagne, T.; Zielinski, M.; Portail, M.; Jouault, B.; Schopfer, F.; Poirier, W.

    2015-01-01

    Replacing GaAs by graphene to realize more practical quantum Hall resistance standards (QHRS), accurate to within 10−9 in relative value, but operating at lower magnetic fields than 10 T, is an ongoing goal in metrology. To date, the required accuracy has been reported, only few times, in graphene grown on SiC by Si sublimation, under higher magnetic fields. Here, we report on a graphene device grown by chemical vapour deposition on SiC, which demonstrates such accuracies of the Hall resistance from 10 T up to 19 T at 1.4 K. This is explained by a quantum Hall effect with low dissipation, resulting from strongly localized bulk states at the magnetic length scale, over a wide magnetic field range. Our results show that graphene-based QHRS can replace their GaAs counterparts by operating in as-convenient cryomagnetic conditions, but over an extended magnetic field range. They rely on a promising hybrid and scalable growth method and a fabrication process achieving low-electron-density devices. PMID:25891533

  2. New approach to predict photoallergic potentials of chemicals based on murine local lymph node assay.

    PubMed

    Maeda, Yosuke; Hirosaki, Haruka; Yamanaka, Hidenori; Takeyoshi, Masahiro

    2018-05-23

    Photoallergic dermatitis, caused by pharmaceuticals and other consumer products, is a very important issue in human health. However, S10 guidelines of the International Conference on Harmonization do not recommend the existing prediction methods for photoallergy because of their low predictability in human cases. We applied local lymph node assay (LLNA), a reliable, quantitative skin sensitization prediction test, to develop a new photoallergy prediction method. This method involves a three-step approach: (1) ultraviolet (UV) absorption analysis; (2) determination of no observed adverse effect level for skin phototoxicity based on LLNA; and (3) photoallergy evaluation based on LLNA. Photoallergic potential of chemicals was evaluated by comparing lymph node cell proliferation among groups treated with chemicals with minimal effect levels of skin sensitization and skin phototoxicity under UV irradiation (UV+) or non-UV irradiation (UV-). A case showing significant difference (P < .05) in lymph node cell proliferation rates between UV- and UV+ groups was considered positive for photoallergic reaction. After testing 13 chemicals, seven human photoallergens tested positive and the other six, with no evidence of causing photoallergic dermatitis or UV absorption, tested negative. Among these chemicals, both doxycycline hydrochloride and minocycline hydrochloride were tetracycline antibiotics with different photoallergic properties, and the new method clearly distinguished between the photoallergic properties of these chemicals. These findings suggested high predictability of our method; therefore, it is promising and effective in predicting human photoallergens. Copyright © 2018 John Wiley & Sons, Ltd.

  3. STRUCTURE-ACTIVITY RELATIONSHIP STUIDES AND THEIR ROLE IN PREDICTING AND INVESTIGATING CHEMICAL TOXICITY

    EPA Science Inventory

    Structure-Activity Relationship Studies and their Role in Predicting and Investigating Chemical Toxicity

    Structure-activity relationships (SAR) represent attempts to generalize chemical information relative to biological activity for the twin purposes of generating insigh...

  4. Solubility prediction, solvate and cocrystal screening as tools for rational crystal engineering.

    PubMed

    Loschen, Christoph; Klamt, Andreas

    2015-06-01

    The fact that novel drug candidates are becoming increasingly insoluble is a major problem of current drug development. Computational tools may address this issue by screening for suitable solvents or by identifying potential novel cocrystal formers that increase bioavailability. In contrast to other more specialized methods, the fluid phase thermodynamics approach COSMO-RS (conductor-like screening model for real solvents) allows for a comprehensive treatment of drug solubility, solvate and cocrystal formation and many other thermodynamics properties in liquids. This article gives an overview of recent COSMO-RS developments that are of interest for drug development and contains several new application examples for solubility prediction and solvate/cocrystal screening. For all property predictions COSMO-RS has been used. The basic concept of COSMO-RS consists of using the screening charge density as computed from first principles calculations in combination with fast statistical thermodynamics to compute the chemical potential of a compound in solution. The fast and accurate assessment of drug solubility and the identification of suitable solvents, solvate or cocrystal formers is nowadays possible and may be used to complement modern drug development. Efficiency is increased by avoiding costly quantum-chemical computations using a database of previously computed molecular fragments. COSMO-RS theory can be applied to a range of physico-chemical properties, which are of interest in rational crystal engineering. Most notably, in combination with experimental reference data, accurate quantitative solubility predictions in any solvent or solvent mixture are possible. Additionally, COSMO-RS can be extended to the prediction of cocrystal formation, which results in considerable predictive accuracy concerning coformer screening. In a recent variant costly quantum chemical calculations are avoided resulting in a significant speed-up and ease-of-use. © 2015 Royal

  5. Quantum Chemical Molecular Dynamics Simulations of 1,3-Dichloropropene Combustion.

    PubMed

    Ahubelem, Nwakamma; Shah, Kalpit; Moghtaderi, Behdad; Page, Alister J

    2015-09-03

    Oxidative decomposition of 1,3-dichloropropene was investigated using quantum chemical molecular dynamics (QM/MD) at 1500 and 3000 K. Thermal oxidation of 1,3-dichloropropene was initiated by (1) abstraction of allylic H/Cl by O2 and (2) intra-annular C-Cl bond scission and elimination of allylic Cl. A kinetic analysis shows that (2) is the more dominant initiation pathway, in agreement with QM/MD results. These QM/MD simulations reveal new routes to the formation of major products (H2O, CO, HCl, CO2), which are propagated primarily by the chloroperoxy (ClO2), OH, and 1,3-dichloropropene derived radicals. In particular, intra-annular C-C/C-H bond dissociation reactions of intermediate aldehydes/ketones are shown to play a dominant role in the formation of CO and CO2. Our simulations demonstrate that both combustion temperature and radical concentration can influence the product yield, however not the combustion mechanism.

  6. CADASTER QSPR Models for Predictions of Melting and Boiling Points of Perfluorinated Chemicals.

    PubMed

    Bhhatarai, Barun; Teetz, Wolfram; Liu, Tao; Öberg, Tomas; Jeliazkova, Nina; Kochev, Nikolay; Pukalov, Ognyan; Tetko, Igor V; Kovarich, Simona; Papa, Ester; Gramatica, Paola

    2011-03-14

    Quantitative structure property relationship (QSPR) studies on per- and polyfluorinated chemicals (PFCs) on melting point (MP) and boiling point (BP) are presented. The training and prediction chemicals used for developing and validating the models were selected from Syracuse PhysProp database and literatures. The available experimental data sets were split in two different ways: a) random selection on response value, and b) structural similarity verified by self-organizing-map (SOM), in order to propose reliable predictive models, developed only on the training sets and externally verified on the prediction sets. Individual linear and non-linear approaches based models developed by different CADASTER partners on 0D-2D Dragon descriptors, E-state descriptors and fragment based descriptors as well as consensus model and their predictions are presented. In addition, the predictive performance of the developed models was verified on a blind external validation set (EV-set) prepared using PERFORCE database on 15 MP and 25 BP data respectively. This database contains only long chain perfluoro-alkylated chemicals, particularly monitored by regulatory agencies like US-EPA and EU-REACH. QSPR models with internal and external validation on two different external prediction/validation sets and study of applicability-domain highlighting the robustness and high accuracy of the models are discussed. Finally, MPs for additional 303 PFCs and BPs for 271 PFCs were predicted for which experimental measurements are unknown. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Beable-guided quantum theories: Generalizing quantum probability laws

    NASA Astrophysics Data System (ADS)

    Kent, Adrian

    2013-02-01

    Beable-guided quantum theories (BGQT) are generalizations of quantum theory, inspired by Bell's concept of beables. They modify the quantum probabilities for some specified set of fundamental events, histories, or other elements of quasiclassical reality by probability laws that depend on the realized configuration of beables. For example, they may define an additional probability weight factor for a beable configuration, independent of the quantum dynamics. Beable-guided quantum theories can be fitted to observational data to provide foils against which to compare explanations based on standard quantum theory. For example, a BGQT could, in principle, characterize the effects attributed to dark energy or dark matter, or any other deviation from the predictions of standard quantum dynamics, without introducing extra fields or a cosmological constant. The complexity of the beable-guided theory would then parametrize how far we are from a standard quantum explanation. Less conservatively, we give reasons for taking suitably simple beable-guided quantum theories as serious phenomenological theories in their own right. Among these are the possibility that cosmological models defined by BGQT might in fact fit the empirical data better than any standard quantum explanation, and the fact that BGQT suggest potentially interesting nonstandard ways of coupling quantum matter to gravity.

  8. Benchmarking of density functionals for a soft but accurate prediction and assignment of (1) H and (13)C NMR chemical shifts in organic and biological molecules.

    PubMed

    Benassi, Enrico

    2017-01-15

    A number of programs and tools that simulate 1 H and 13 C nuclear magnetic resonance (NMR) chemical shifts using empirical approaches are available. These tools are user-friendly, but they provide a very rough (and sometimes misleading) estimation of the NMR properties, especially for complex systems. Rigorous and reliable ways to predict and interpret NMR properties of simple and complex systems are available in many popular computational program packages. Nevertheless, experimentalists keep relying on these "unreliable" tools in their daily work because, to have a sufficiently high accuracy, these rigorous quantum mechanical methods need high levels of theory. An alternative, efficient, semi-empirical approach has been proposed by Bally, Rablen, Tantillo, and coworkers. This idea consists of creating linear calibrations models, on the basis of the application of different combinations of functionals and basis sets. Following this approach, the predictive capability of a wider range of popular functionals was systematically investigated and tested. The NMR chemical shifts were computed in solvated phase at density functional theory level, using 30 different functionals coupled with three different triple-ζ basis sets. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  9. Mid-Infrared Quantum-Dot Quantum Cascade Laser: A Theoretical Feasibility Study

    DOE PAGES

    Michael, Stephan; Chow, Weng; Schneider, Hans

    2016-05-01

    In the framework of a microscopic model for intersubband gain from electrically pumped quantum-dot structures we investigate electrically pumped quantum-dots as active material for a mid-infrared quantum cascade laser. Our previous calculations have indicated that these structures could operate with reduced threshold current densities while also achieving a modal gain comparable to that of quantum well active materials. We study the influence of two important quantum-dot material parameters, here, namely inhomogeneous broadening and quantum-dot sheet density, on the performance of a proposed quantum cascade laser design. In terms of achieving a positive modal net gain, a high quantum-dot density canmore » compensate for moderately high inhomogeneous broadening, but at a cost of increased threshold current density. By minimizing quantum-dot density with presently achievable inhomogeneous broadening and total losses, significantly lower threshold densities than those reported in quantum-well quantum-cascade lasers are predicted by our theory.« less

  10. Algorithms Bridging Quantum Computation and Chemistry

    NASA Astrophysics Data System (ADS)

    McClean, Jarrod Ryan

    The design of new materials and chemicals derived entirely from computation has long been a goal of computational chemistry, and the governing equation whose solution would permit this dream is known. Unfortunately, the exact solution to this equation has been far too expensive and clever approximations fail in critical situations. Quantum computers offer a novel solution to this problem. In this work, we develop not only new algorithms to use quantum computers to study hard problems in chemistry, but also explore how such algorithms can help us to better understand and improve our traditional approaches. In particular, we first introduce a new method, the variational quantum eigensolver, which is designed to maximally utilize the quantum resources available in a device to solve chemical problems. We apply this method in a real quantum photonic device in the lab to study the dissociation of the helium hydride (HeH+) molecule. We also enhance this methodology with architecture specific optimizations on ion trap computers and show how linear-scaling techniques from traditional quantum chemistry can be used to improve the outlook of similar algorithms on quantum computers. We then show how studying quantum algorithms such as these can be used to understand and enhance the development of classical algorithms. In particular we use a tool from adiabatic quantum computation, Feynman's Clock, to develop a new discrete time variational principle and further establish a connection between real-time quantum dynamics and ground state eigenvalue problems. We use these tools to develop two novel parallel-in-time quantum algorithms that outperform competitive algorithms as well as offer new insights into the connection between the fermion sign problem of ground states and the dynamical sign problem of quantum dynamics. Finally we use insights gained in the study of quantum circuits to explore a general notion of sparsity in many-body quantum systems. In particular we use

  11. Predictive Structure-Based Toxicology Approaches To Assess the Androgenic Potential of Chemicals.

    PubMed

    Trisciuzzi, Daniela; Alberga, Domenico; Mansouri, Kamel; Judson, Richard; Novellino, Ettore; Mangiatordi, Giuseppe Felice; Nicolotti, Orazio

    2017-11-27

    We present a practical and easy-to-run in silico workflow exploiting a structure-based strategy making use of docking simulations to derive highly predictive classification models of the androgenic potential of chemicals. Models were trained on a high-quality chemical collection comprising 1689 curated compounds made available within the CoMPARA consortium from the US Environmental Protection Agency and were integrated with a two-step applicability domain whose implementation had the effect of improving both the confidence in prediction and statistics by reducing the number of false negatives. Among the nine androgen receptor X-ray solved structures, the crystal 2PNU (entry code from the Protein Data Bank) was associated with the best performing structure-based classification model. Three validation sets comprising each 2590 compounds extracted by the DUD-E collection were used to challenge model performance and the effectiveness of Applicability Domain implementation. Next, the 2PNU model was applied to screen and prioritize two collections of chemicals. The first is a small pool of 12 representative androgenic compounds that were accurately classified based on outstanding rationale at the molecular level. The second is a large external blind set of 55450 chemicals with potential for human exposure. We show how the use of molecular docking provides highly interpretable models and can represent a real-life option as an alternative nontesting method for predictive toxicology.

  12. A general intermolecular force field based on tight-binding quantum chemical calculations

    NASA Astrophysics Data System (ADS)

    Grimme, Stefan; Bannwarth, Christoph; Caldeweyher, Eike; Pisarek, Jana; Hansen, Andreas

    2017-10-01

    A black-box type procedure is presented for the generation of a molecule-specific, intermolecular potential energy function. The method uses quantum chemical (QC) information from our recently published extended tight-binding semi-empirical scheme (GFN-xTB) and can treat non-covalently bound complexes and aggregates with almost arbitrary chemical structure. The necessary QC information consists of the equilibrium structure, Mulliken atomic charges, charge centers of localized molecular orbitals, and also of frontier orbitals and orbital energies. The molecular pair potential includes model density dependent Pauli repulsion, penetration, as well as point charge electrostatics, the newly developed D4 dispersion energy model, Drude oscillators for polarization, and a charge-transfer term. Only one element-specific and about 20 global empirical parameters are needed to cover systems with nuclear charges up to radon (Z = 86). The method is tested for standard small molecule interaction energy benchmark sets where it provides accurate intermolecular energies and equilibrium distances. Examples for structures with a few hundred atoms including charged systems demonstrate the versatility of the approach. The method is implemented in a stand-alone computer code which enables rigid-body, global minimum energy searches for molecular aggregation or alignment.

  13. Learning to Predict Chemical Reactions

    PubMed Central

    Kayala, Matthew A.; Azencott, Chloé-Agathe; Chen, Jonathan H.

    2011-01-01

    Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles respectively are not high-throughput, are not generalizable or scalable, or lack sufficient data and structure to be implemented. We propose a new approach to reaction prediction utilizing elements from each pole. Using a physically inspired conceptualization, we describe single mechanistic reactions as interactions between coarse approximations of molecular orbitals (MOs) and use topological and physicochemical attributes as descriptors. Using an existing rule-based system (Reaction Explorer), we derive a restricted chemistry dataset consisting of 1630 full multi-step reactions with 2358 distinct starting materials and intermediates, associated with 2989 productive mechanistic steps and 6.14 million unproductive mechanistic steps. And from machine learning, we pose identifying productive mechanistic steps as a statistical ranking, information retrieval, problem: given a set of reactants and a description of conditions, learn a ranking model over potential filled-to-unfilled MO interactions such that the top ranked mechanistic steps yield the major products. The machine learning implementation follows a two-stage approach, in which we first train atom level reactivity filters to prune 94.00% of non-productive reactions with a 0.01% error rate. Then, we train an ensemble of ranking models on pairs of interacting MOs to learn a relative productivity function over mechanistic steps in a given system. Without the use of explicit transformation patterns, the ensemble perfectly ranks the productive mechanism at the top 89.05% of the time, rising to 99.86% of the time when the top four are considered. Furthermore, the system

  14. Learning to predict chemical reactions.

    PubMed

    Kayala, Matthew A; Azencott, Chloé-Agathe; Chen, Jonathan H; Baldi, Pierre

    2011-09-26

    Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles, respectively, are not high throughput, are not generalizable or scalable, and lack sufficient data and structure to be implemented. We propose a new approach to reaction prediction utilizing elements from each pole. Using a physically inspired conceptualization, we describe single mechanistic reactions as interactions between coarse approximations of molecular orbitals (MOs) and use topological and physicochemical attributes as descriptors. Using an existing rule-based system (Reaction Explorer), we derive a restricted chemistry data set consisting of 1630 full multistep reactions with 2358 distinct starting materials and intermediates, associated with 2989 productive mechanistic steps and 6.14 million unproductive mechanistic steps. And from machine learning, we pose identifying productive mechanistic steps as a statistical ranking, information retrieval problem: given a set of reactants and a description of conditions, learn a ranking model over potential filled-to-unfilled MO interactions such that the top-ranked mechanistic steps yield the major products. The machine learning implementation follows a two-stage approach, in which we first train atom level reactivity filters to prune 94.00% of nonproductive reactions with a 0.01% error rate. Then, we train an ensemble of ranking models on pairs of interacting MOs to learn a relative productivity function over mechanistic steps in a given system. Without the use of explicit transformation patterns, the ensemble perfectly ranks the productive mechanism at the top 89.05% of the time, rising to 99.86% of the time when the top four are considered. Furthermore, the system

  15. Significance of vapor phase chemical reactions on CVD rates predicted by chemically frozen and local thermochemical equilibrium boundary layer theories

    NASA Technical Reports Server (NTRS)

    Gokoglu, Suleyman A.

    1988-01-01

    This paper investigates the role played by vapor-phase chemical reactions on CVD rates by comparing the results of two extreme theories developed to predict CVD mass transport rates in the absence of interfacial kinetic barrier: one based on chemically frozen boundary layer and the other based on local thermochemical equilibrium. Both theories consider laminar convective-diffusion boundary layers at high Reynolds numbers and include thermal (Soret) diffusion and variable property effects. As an example, Na2SO4 deposition was studied. It was found that gas phase reactions have no important role on Na2SO4 deposition rates and on the predictions of the theories. The implications of the predictions of the two theories to other CVD systems are discussed.

  16. Compressed quantum computation using a remote five-qubit quantum computer

    NASA Astrophysics Data System (ADS)

    Hebenstreit, M.; Alsina, D.; Latorre, J. I.; Kraus, B.

    2017-05-01

    The notion of compressed quantum computation is employed to simulate the Ising interaction of a one-dimensional chain consisting of n qubits using the universal IBM cloud quantum computer running on log2(n ) qubits. The external field parameter that controls the quantum phase transition of this model translates into particular settings of the quantum gates that generate the circuit. We measure the magnetization, which displays the quantum phase transition, on a two-qubit system, which simulates a four-qubit Ising chain, and show its agreement with the theoretical prediction within a certain error. We also discuss the relevant point of how to assess errors when using a cloud quantum computer with a limited amount of runs. As a solution, we propose to use validating circuits, that is, to run independent controlled quantum circuits of similar complexity to the circuit of interest.

  17. The SOA formation model combined with semiempirical quantum chemistry for predicting UV-Vis absorption of secondary organic aerosols.

    PubMed

    Zhong, Min; Jang, Myoseon; Oliferenko, Alexander; Pillai, Girinath G; Katritzky, Alan R

    2012-07-07

    A new model for predicting the UV-visible absorption spectra of secondary organic aerosols (SOA) has been developed. The model consists of two primary parts: a SOA formation model and a semiempirical quantum chemistry method. The mass of SOA is predicted using the PHRCSOA (Partitioning Heterogeneous Reaction Consortium Secondary Organic Aerosol) model developed by Cao and Jang [Environ. Sci. Technol., 2010, 44, 727]. The chemical composition is estimated using a combination of the kinetic model (MCM) and the PHRCSOA model. The absorption spectrum is obtained by taking the sum of the spectrum of each SOA product calculated using a semiempirical NDDO (Neglect of Diatomic Differential Overlap)-based method. SOA was generated from the photochemical reaction of toluene or α-pinene at different NO(x) levels (low NO(x): 24-26 ppm, middle NO(x): 49 ppb, high NO(x): 104-105 ppb) using a 2 m(3) indoor Teflon film chamber. The model simulation reasonably agrees with the measured absorption spectra of α-pinene SOA but underestimates toluene SOA under high and middle NO(x) conditions. The absorption spectrum of toluene SOA is moderately enhanced with increasing NO(x) concentrations, while that of α-pinene SOA is not affected. Both measured and calculated UV-visible spectra show that the light absorption of toluene SOA is much stronger than that of α-pinene SOA.

  18. Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.

    PubMed

    Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

    2013-09-01

    The research aims to develop global modeling tools capable of categorizing structurally diverse chemicals in various toxicity classes according to the EEC and European Community directives, and to predict their acute toxicity in fathead minnow using set of selected molecular descriptors. Accordingly, artificial intelligence approach based classification and regression models, such as probabilistic neural networks (PNN), generalized regression neural networks (GRNN), multilayer perceptron neural network (MLPN), radial basis function neural network (RBFN), support vector machines (SVM), gene expression programming (GEP), and decision tree (DT) were constructed using the experimental toxicity data. Diversity and non-linearity in the chemicals' data were tested using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Predictive and generalization abilities of various models constructed here were compared using several statistical parameters. PNN and GRNN models performed relatively better than MLPN, RBFN, SVM, GEP, and DT. Both in two and four category classifications, PNN yielded a considerably high accuracy of classification in training (95.85 percent and 90.07 percent) and validation data (91.30 percent and 86.96 percent), respectively. GRNN rendered a high correlation between the measured and model predicted -log LC50 values both for the training (0.929) and validation (0.910) data and low prediction errors (RMSE) of 0.52 and 0.49 for two sets. Efficiency of the selected PNN and GRNN models in predicting acute toxicity of new chemicals was adequately validated using external datasets of different fish species (fathead minnow, bluegill, trout, and guppy). The PNN and GRNN models showed good predictive and generalization abilities and can be used as tools for predicting toxicities of structurally diverse chemical compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

  19. Standoff detection of turbulent chemical mixture plumes using a swept external cavity quantum cascade laser

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Phillips, Mark C.; Brumfield, Brian E.

    We demonstrate standoff detection of turbulent mixed-chemical plumes using a broadly-tunable external cavity quantum cascade laser (ECQCL). The ECQCL was directed through plumes of mixed methanol/ethanol vapor to a partially-reflective surface located 10 m away. The reflected power was measured as the ECQCL was swept over its tuning range of 930-1065 cm-1 (9.4-10.8 µm) at rates up to 200 Hz. Analysis of the transmission spectra though the plume was performed to determine chemical concentrations with time resolution of 0.005 s. Comparison of multiple spectral sweep rates of 2 Hz, 20 Hz, and 200 Hz shows that higher sweep rates reducemore » effects of atmospheric and source turbulence, resulting in lower detection noise and more accurate measurement of the rapidly-changing chemical concentrations. Detection sensitivities of 0.13 ppm*m for MeOH and 1.2 ppm*m for EtOH are demonstrated for a 200 Hz spectral sweep rate, normalized to 1 s detection time.« less

  20. On the origin of the gauche effect. A quantum chemical study of 1,2-difluoroethane

    NASA Astrophysics Data System (ADS)

    Engkvist, O.; Karlström, G.; Widmark, P.-O.

    1997-01-01

    The conformational equilibrium of 1,2-difluoroethane has been investigated using ab initio quantum chemical calculations at the SCF, MP2 and CCSD(T) levels, with ANO basis sets. The relative stability of the gauche-conformation of 1,2-difluoroethane is found to be a consequence of the nodal structure of the singly occupied orbital in the CFH 2 radical. It is also shown that the nodal structure of the singly occupied orbitals in the CFH biradical can explain the stability of the cis conformation of 1,2-difluoroethene.

  1. Chemical bonding in TiSb(2) and VSb(2): a quantum chemical and experimental study.

    PubMed

    Armbrüster, Marc; Schnelle, Walter; Schwarz, Ulrich; Grin, Yuri

    2007-08-06

    The chemical bonding in the isostructural intermetallic compounds TiSb2 and VSb2, crystallizing in the CuAl2 type, was investigated by means of quantum chemical calculations, particularly the electron localization function (ELF), as well as by Raman spectroscopy, Hall effect and conductivity measurements on oriented single crystals, and high-pressure X-ray powder diffraction. The homogeneity ranges of the compounds were determined by powder X-ray diffraction, WDXS, and DSC measurements. TiSb2 exhibits no significant homogeneity range, while VSb2 shows a small homogeneity range of approximately 0.3 at. %. According to the ELF calculations, the Sb atoms form dumbbells via a two-center two-electron bond, while the T atoms (T = Ti, V) build up chains along the crystallographic c-axis. Both building units are connected by covalent T-Sb-T three-center bonds, thus forming a three-dimensional network. The strength of the bonds involving Sb was determined by fitting a force constant model to the vibrational mode frequencies observed by polarized Raman measurements on oriented single crystals. The resulting bond order of the Sb2 dumbbells is 1, while the strength of the three-center bonds resembles a bond order of 1.5. The weak pressure dependence of the c/a ratio confirms the slightly different bonding picture in TiSb2 compared to that in CuAl2. Electrical transport measurements show the presence of free charge carriers, as well as a metal-like temperature dependence of the electrical resistivity.

  2. Time-Resolved Quantum Cascade Laser Absorption Spectroscopy of Pulsed Plasma Assisted Chemical Vapor Deposition Processes Containing BCl3

    NASA Astrophysics Data System (ADS)

    Lang, Norbert; Hempel, Frank; Strämke, Siegfried; Röpcke, Jürgen

    2011-08-01

    In situ measurements are reported giving insight into the plasma chemical conversion of the precursor BCl3 in industrial applications of boriding plasmas. For the online monitoring of its ground state concentration, quantum cascade laser absorption spectroscopy (QCLAS) in the mid-infrared spectral range was applied in a plasma assisted chemical vapor deposition (PACVD) reactor. A compact quantum cascade laser measurement and control system (Q-MACS) was developed to allow a flexible and completely dust-sealed optical coupling to the reactor chamber of an industrial plasma surface modification system. The process under the study was a pulsed DC plasma with periodically injected BCl3 at 200 Pa. A synchronization of the Q-MACS with the process control unit enabled an insight into individual process cycles with a sensitivity of 10-6 cm-1·Hz-1/2. Different fragmentation rates of the precursor were found during an individual process cycle. The detected BCl3 concentrations were in the order of 1014 molecules·cm-3. The reported results of in situ monitoring with QCLAS demonstrate the potential for effective optimization procedures in industrial PACVD processes.

  3. Adsorption, Thermodynamic and Quantum Chemical Studies of 1-hexyl-3-methylimidazolium Based Ionic Liquids as Corrosion Inhibitors for Mild Steel in HCl

    PubMed Central

    Mashuga, Motsie E.; Olasunkanmi, Lukman O.; Adekunle, Abolanle S.; Yesudass, Sasikumar; Kabanda, Mwadham M.; Ebenso, Eno E.

    2015-01-01

    The inhibition of mild steel corrosion in 1 M HCl solution by some ionic liquids (ILs) namely, 1-hexyl-3-methylimidazolium trifluoromethanesulfonate [HMIM][TfO], 1-hexyl-3-methylimidazolium tetrafluoroborate [HMIM][BF4], 1-hexyl-3-methylimidazolium hexafluorophosphate [HMIM][PF6], and 1-hexyl-3-methylimidazolium iodide [HMIM][I] was investigated using electrochemical measurements, spectroscopic analyses and quantum chemical calculations. All the ILs showed appreciably high inhibition efficiency. At 303 K, the results of electrochemical measurements indicated that the studied ILs are mixed-type inhibitors. The adsorption studies showed that all the four ILs adsorb spontaneously on steel surface with [HMIM][TfO], [HMIM][BF4] and [HMIM][I] obeying Langmuir adsorption isotherm, while [HMIM][PF6] conformed better with Temkin adsorption isotherm. Spectroscopic analyses suggested the formation of Fe/ILs complexes. Some quantum chemical parameters were calculated to corroborate experimental results.

  4. Advancing alternatives analysis: The role of predictive toxicology in selecting safer chemical products and processes.

    PubMed

    Malloy, Timothy; Zaunbrecher, Virginia; Beryt, Elizabeth; Judson, Richard; Tice, Raymond; Allard, Patrick; Blake, Ann; Cote, Ila; Godwin, Hilary; Heine, Lauren; Kerzic, Patrick; Kostal, Jakub; Marchant, Gary; McPartland, Jennifer; Moran, Kelly; Nel, Andre; Ogunseitan, Oladele; Rossi, Mark; Thayer, Kristina; Tickner, Joel; Whittaker, Margaret; Zarker, Ken

    2017-09-01

    Alternatives analysis (AA) is a method used in regulation and product design to identify, assess, and evaluate the safety and viability of potential substitutes for hazardous chemicals. It requires toxicological data for the existing chemical and potential alternatives. Predictive toxicology uses in silico and in vitro approaches, computational models, and other tools to expedite toxicological data generation in a more cost-effective manner than traditional approaches. The present article briefly reviews the challenges associated with using predictive toxicology in regulatory AA, then presents 4 recommendations for its advancement. It recommends using case studies to advance the integration of predictive toxicology into AA, adopting a stepwise process to employing predictive toxicology in AA beginning with prioritization of chemicals of concern, leveraging existing resources to advance the integration of predictive toxicology into the practice of AA, and supporting transdisciplinary efforts. The further incorporation of predictive toxicology into AA would advance the ability of companies and regulators to select alternatives to harmful ingredients, and potentially increase the use of predictive toxicology in regulation more broadly. Integr Environ Assess Manag 2017;13:915-925. © 2017 SETAC. © 2017 SETAC.

  5. Quantum-mechanics-derived 13Cα chemical shift server (CheShift) for protein structure validation

    PubMed Central

    Vila, Jorge A.; Arnautova, Yelena A.; Martin, Osvaldo A.; Scheraga, Harold A.

    2009-01-01

    A server (CheShift) has been developed to predict 13Cα chemical shifts of protein structures. It is based on the generation of 696,916 conformations as a function of the φ, ψ, ω, χ1 and χ2 torsional angles for all 20 naturally occurring amino acids. Their 13Cα chemical shifts were computed at the DFT level of theory with a small basis set and extrapolated, with an empirically-determined linear regression formula, to reproduce the values obtained with a larger basis set. Analysis of the accuracy and sensitivity of the CheShift predictions, in terms of both the correlation coefficient R and the conformational-averaged rmsd between the observed and predicted 13Cα chemical shifts, was carried out for 3 sets of conformations: (i) 36 x-ray-derived protein structures solved at 2.3 Å or better resolution, for which sets of 13Cα chemical shifts were available; (ii) 15 pairs of x-ray and NMR-derived sets of protein conformations; and (iii) a set of decoys for 3 proteins showing an rmsd with respect to the x-ray structure from which they were derived of up to 3 Å. Comparative analysis carried out with 4 popular servers, namely SHIFTS, SHIFTX, SPARTA, and PROSHIFT, for these 3 sets of conformations demonstrated that CheShift is the most sensitive server with which to detect subtle differences between protein models and, hence, to validate protein structures determined by either x-ray or NMR methods, if the observed 13Cα chemical shifts are available. CheShift is available as a web server. PMID:19805131

  6. Vibrational, electronic and quantum chemical studies of 1,2,4-benzenetricarboxylic-1,2-anhydride.

    PubMed

    Arjunan, V; Raj, Arushma; Subramanian, S; Mohan, S

    2013-06-01

    The FTIR and FT-Raman spectra of 1,2,4-benzenetricarboxylic-1,2-anhydride (BTCA) have been recorded in the range 4000-400 and 4000-100 cm(-1), respectively. The complete vibrational assignments and analysis of BTCA have been performed. More support on the experimental findings was added from the quantum chemical studies performed with DFT (B3LYP, MP2, B3PW91) method using 6-311++G(**), 6-31G(**) and cc-pVTZ basis sets. The structural parameters, energies, thermodynamic parameters, vibrational frequencies and the NBO charges of BTCA were determined by the DFT method. The (1)H and (13)C isotropic chemical shifts (δ ppm) of BTCA with respect to TMS were also calculated using the gauge independent atomic orbital (GIAO) method and compared with the experimental data. The delocalization energies of different types of interactions were determined. Copyright © 2013 Elsevier B.V. All rights reserved.

  7. Development and Validation of Decision Forest Model for Estrogen Receptor Binding Prediction of Chemicals Using Large Data Sets.

    PubMed

    Ng, Hui Wen; Doughty, Stephen W; Luo, Heng; Ye, Hao; Ge, Weigong; Tong, Weida; Hong, Huixiao

    2015-12-21

    Some chemicals in the environment possess the potential to interact with the endocrine system in the human body. Multiple receptors are involved in the endocrine system; estrogen receptor α (ERα) plays very important roles in endocrine activity and is the most studied receptor. Understanding and predicting estrogenic activity of chemicals facilitates the evaluation of their endocrine activity. Hence, we have developed a decision forest classification model to predict chemical binding to ERα using a large training data set of 3308 chemicals obtained from the U.S. Food and Drug Administration's Estrogenic Activity Database. We tested the model using cross validations and external data sets of 1641 chemicals obtained from the U.S. Environmental Protection Agency's ToxCast project. The model showed good performance in both internal (92% accuracy) and external validations (∼ 70-89% relative balanced accuracies), where the latter involved the validations of the model across different ER pathway-related assays in ToxCast. The important features that contribute to the prediction ability of the model were identified through informative descriptor analysis and were related to current knowledge of ER binding. Prediction confidence analysis revealed that the model had both high prediction confidence and accuracy for most predicted chemicals. The results demonstrated that the model constructed based on the large training data set is more accurate and robust for predicting ER binding of chemicals than the published models that have been developed using much smaller data sets. The model could be useful for the evaluation of ERα-mediated endocrine activity potential of environmental chemicals.

  8. PREDICTION METRICS FOR CHEMICAL DETECTION IN LONG-WAVE INFRARED HYPERSPECTRAL IMAGERY

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chilton, M.; Walsh, S.J.; Daly, D.S.

    2009-01-01

    Natural and man-made chemical processes generate gaseous plumes that may be detected by hyperspectral imaging, which produces a matrix of spectra affected by the chemical constituents of the plume, the atmosphere, the bounding background surface and instrument noise. A physics-based model of observed radiance shows that high chemical absorbance and low background emissivity result in a larger chemical signature. Using simulated hyperspectral imagery, this study investigated two metrics which exploited this relationship. The objective was to explore how well the chosen metrics predicted when a chemical would be more easily detected when comparing one background type to another. The twomore » predictor metrics correctly rank ordered the backgrounds for about 94% of the chemicals tested as compared to the background rank orders from Whitened Matched Filtering (a detection algorithm) of the simulated spectra. These results suggest that the metrics provide a reasonable summary of how the background emissivity and chemical absorbance interact to produce the at-sensor chemical signal. This study suggests that similarly effective predictors that account for more general physical conditions may be derived.« less

  9. Molecular mechanism of NDMA formation from N,N-dimethylsulfamide during ozonation: quantum chemical insights into a bromide-catalyzed pathway.

    PubMed

    Trogolo, Daniela; Mishra, Brijesh Kumar; Heeb, Michèle B; von Gunten, Urs; Arey, J Samuel

    2015-04-07

    During ozonation of drinking water, the fungicide metabolite N,N-dimethylsulfamide (DMS) can be transformed into a highly toxic product, N-nitrosodimethylamine (NDMA). We used quantum chemical computations and stopped-flow experiments to evaluate a chemical mechanism proposed previously to describe this transformation. Stopped-flow experiments indicate a pK(a) = 10.4 for DMS. Experiments show that hypobromous acid (HOBr), generated by ozone oxidation of naturally occurring bromide, brominates the deprotonated DMS(-) anion with a near-diffusion controlled rate constant (7.1 ± 0.6 × 10(8) M(-1) s(-1)), forming Br-DMS(-) anion. According to quantum chemical calculations, Br-DMS has a pK(a) ∼ 9.0 and thus remains partially deprotonated at neutral pH. The anionic Br-DMS(-) bromamine can react with ozone with a high rate constant (10(5 ± 2.5) M(-1) s(-1)), forming the reaction intermediate (BrNO)(SO2)N(CH3)2(-). This intermediate resembles a loosely bound complex between an electrophilic nitrosyl bromide (BrNO) molecule and an electron-rich dimethylaminosulfinate ((SO2)N(CH3)2(-)) fragment, based on inspection of computed natural charges and geometric parameters. This fragile complex undergoes immediate (10(10 ± 2.5) s(-1)) reaction by two branches: an exothermic channel that produces NDMA, and an entropy-driven channel giving non-NDMA products. Computational results bring new insights into the electronic nature, chemical equilibria, and kinetics of the elementary reactions of this pathway, enabled by computed energies of structures that are not possible to access experimentally.

  10. Chemically functionalized ZnS quantum dots as new optical nanosensor of herbicides

    NASA Astrophysics Data System (ADS)

    Masteri-Farahani, M.; Mahdavi, S.; Khanmohammadi, H.

    2018-03-01

    Surface chemical functionalization of ZnS quantum dots (ZnS-QDs) with cysteamine hydrochloride resulted in the preparation of an optical nanosensor for detection of herbicides. Characterization of the functionalized ZnS-QDs was performed with physicochemical methods such as x-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier transform infrared (FT-IR) spectroscopy, energy dispersive x-ray (EDX) analysis, ultraviolet-visible (UV–vis) and photoluminescence (PL) spectroscopies. The optical band gap of the functionalized ZnS-QDs was determined by using Tauc plot as 4.1 eV. Addition of various herbicides resulted in the linearly fluorescence quenching of the functionalized ZnS-QDs according to the Stern-Volmer equation. The functionalized ZnS-QDs can be used as simple, rapid, and inexpensive nanosensor for practical detection and measurement of various herbicides.

  11. Quantum sequencing: opportunities and challenges

    NASA Astrophysics Data System (ADS)

    di Ventra, Massimiliano

    Personalized or precision medicine refers to the ability of tailoring drugs to the specific genome and transcriptome of each individual. It is however not yet feasible due the high costs and slow speed of present DNA sequencing methods. I will discuss a sequencing protocol that requires the measurement of the distributions of transverse tunneling currents during the translocation of single-stranded DNA into nanochannels. I will show that such a quantum sequencing approach can reach unprecedented speeds, without requiring any chemical preparation, amplification or labeling. I will discuss recent experiments that support these theoretical predictions, the advantages of this approach over other sequencing methods, and stress the challenges that need to be overcome to render it commercially viable.

  12. Similarity-based prediction for Anatomical Therapeutic Chemical classification of drugs by integrating multiple data sources.

    PubMed

    Liu, Zhongyang; Guo, Feifei; Gu, Jiangyong; Wang, Yong; Li, Yang; Wang, Dan; Lu, Liang; Li, Dong; He, Fuchu

    2015-06-01

    Anatomical Therapeutic Chemical (ATC) classification system, widely applied in almost all drug utilization studies, is currently the most widely recognized classification system for drugs. Currently, new drug entries are added into the system only on users' requests, which leads to seriously incomplete drug coverage of the system, and bioinformatics prediction is helpful during this process. Here we propose a novel prediction model of drug-ATC code associations, using logistic regression to integrate multiple heterogeneous data sources including chemical structures, target proteins, gene expression, side-effects and chemical-chemical associations. The model obtains good performance for the prediction not only on ATC codes of unclassified drugs but also on new ATC codes of classified drugs assessed by cross-validation and independent test sets, and its efficacy exceeds previous methods. Further to facilitate the use, the model is developed into a user-friendly web service SPACE ( S: imilarity-based P: redictor of A: TC C: od E: ), which for each submitted compound, will give candidate ATC codes (ranked according to the decreasing probability_score predicted by the model) together with corresponding supporting evidence. This work not only contributes to knowing drugs' therapeutic, pharmacological and chemical properties, but also provides clues for drug repositioning and side-effect discovery. In addition, the construction of the prediction model also provides a general framework for similarity-based data integration which is suitable for other drug-related studies such as target, side-effect prediction etc. The web service SPACE is available at http://www.bprc.ac.cn/space. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Microscopic origin of the fast blue-green luminescence of chemically synthesized non-oxidized silicon quantum dots.

    PubMed

    Dohnalová, Kateřina; Fučíková, Anna; Umesh, Chinnaswamy P; Humpolíčková, Jana; Paulusse, Jos M J; Valenta, Jan; Zuilhof, Han; Hof, Martin; Gregorkiewicz, Tom

    2012-10-22

    The microscopic origin of the bright nanosecond blue-green photoluminescence (PL), frequently reported for synthesized organically terminated Si quantum dots (Si-QDs), has not been fully resolved, hampering potential applications of this interesting material. Here a comprehensive study of the PL from alkyl-terminated Si-QDs of 2-3 nm size, prepared by wet chemical synthesis is reported. Results obtained on the ensemble and those from the single nano-object level are compared, and they provide conclusive evidence that efficient and tunable emission arises due to radiative recombination of electron-hole pairs confined in the Si-QDs. This understanding paves the way towards applications of chemical synthesis for the development of Si-QDs with tunable sizes and bandgaps. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Stabilization of the Simplest Criegee Intermediate from the Reaction between Ozone and Ethylene: A High-Level Quantum Chemical and Kinetic Analysis of Ozonolysis.

    PubMed

    Nguyen, Thanh Lam; Lee, Hyunwoo; Matthews, Devin A; McCarthy, Michael C; Stanton, John F

    2015-06-04

    The fraction of the collisionally stabilized Criegee species CH2OO produced from the ozonolysis of ethylene is calculated using a two-dimensional (E, J)-grained master equation technique and semiclassical transition-state theory based on the potential energy surface obtained from high-accuracy quantum chemical calculations. Our calculated yield of 42 ± 6% for the stabilized CH2OO agrees well, within experimental error, with available (indirect) experimental results. Inclusion of angular momentum in the master equation is found to play an essential role in bringing the theoretical results into agreement with the experiment. Additionally, yields of HO and HO2 radical products are predicted to be 13 ± 6% and 17 ± 6%, respectively. In the kinetic simulation, the HO radical product is produced mostly from the stepwise decomposition mechanism of primary ozonide rather than from dissociation of hot CH2OO.

  15. Molecular Structure-Based Large-Scale Prediction of Chemical-Induced Gene Expression Changes.

    PubMed

    Liu, Ruifeng; AbdulHameed, Mohamed Diwan M; Wallqvist, Anders

    2017-09-25

    The quantitative structure-activity relationship (QSAR) approach has been used to model a wide range of chemical-induced biological responses. However, it had not been utilized to model chemical-induced genomewide gene expression changes until very recently, owing to the complexity of training and evaluating a very large number of models. To address this issue, we examined the performance of a variable nearest neighbor (v-NN) method that uses information on near neighbors conforming to the principle that similar structures have similar activities. Using a data set of gene expression signatures of 13 150 compounds derived from cell-based measurements in the NIH Library of Integrated Network-based Cellular Signatures program, we were able to make predictions for 62% of the compounds in a 10-fold cross validation test, with a correlation coefficient of 0.61 between the predicted and experimentally derived signatures-a reproducibility rivaling that of high-throughput gene expression measurements. To evaluate the utility of the predicted gene expression signatures, we compared the predicted and experimentally derived signatures in their ability to identify drugs known to cause specific liver, kidney, and heart injuries. Overall, the predicted and experimentally derived signatures had similar receiver operating characteristics, whose areas under the curve ranged from 0.71 to 0.77 and 0.70 to 0.73, respectively, across the three organ injury models. However, detailed analyses of enrichment curves indicate that signatures predicted from multiple near neighbors outperformed those derived from experiments, suggesting that averaging information from near neighbors may help improve the signal from gene expression measurements. Our results demonstrate that the v-NN method can serve as a practical approach for modeling large-scale, genomewide, chemical-induced, gene expression changes.

  16. Prediction of quantum interference in molecular junctions using a parabolic diagram: Understanding the origin of Fano and anti- resonances

    NASA Astrophysics Data System (ADS)

    Nozaki, Daijiro; Avdoshenko, Stanislav M.; Sevinçli, Hâldun; Gutierrez, Rafael; Cuniberti, Gianaurelio

    2013-03-01

    Recently the interest in quantum interference (QI) phenomena in molecular devices (molecular junctions) has been growing due to the unique features observed in the transmission spectra. In order to design single molecular devices exploiting QI effects as desired, it is necessary to provide simple rules for predicting the appearance of QI effects such as anti-resonances or Fano line shapes and for controlling them. In this study, we derive a transmission function of a generic molecular junction with a side group (T-shaped molecular junction) using a minimal toy model. We developed a simple method to predict the appearance of quantum interference, Fano resonances or anti- resonances, and its position in the conductance spectrum by introducing a simple graphical representation (parabolic model). Using it we can easily visualize the relation between the key electronic parameters and the positions of normal resonant peaks and anti-resonant peaks induced by quantum interference in the conductance spectrum. We also demonstrate Fano and anti-resonance in T-shaped molecular junctions using a simple tight-binding model. This parabolic model enables one to infer on-site energies of T-shaped molecules and the coupling between side group and main conduction channel from transmission spectra.

  17. Efficient first-principles prediction of solid stability: Towards chemical accuracy

    NASA Astrophysics Data System (ADS)

    Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia; Chen, Tina; Dacek, Stephen T.; Sarmiento-Pérez, Rafael A.; Marques, Maguel A. L.; Peng, Haowei; Ceder, Gerbrand; Perdew, John P.; Sun, Jianwei

    2018-03-01

    The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. Here, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for main group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.

  18. Efficient first-principles prediction of solid stability: Towards chemical accuracy

    DOE PAGES

    Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia; ...

    2018-03-09

    The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. In this paper, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for mainmore » group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.« less

  19. Efficient first-principles prediction of solid stability: Towards chemical accuracy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia

    The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. In this paper, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for mainmore » group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.« less

  20. Quantum junction solar cells.

    PubMed

    Tang, Jiang; Liu, Huan; Zhitomirsky, David; Hoogland, Sjoerd; Wang, Xihua; Furukawa, Melissa; Levina, Larissa; Sargent, Edward H

    2012-09-12

    Colloidal quantum dot solids combine convenient solution-processing with quantum size effect tuning, offering avenues to high-efficiency multijunction cells based on a single materials synthesis and processing platform. The highest-performing colloidal quantum dot rectifying devices reported to date have relied on a junction between a quantum-tuned absorber and a bulk material (e.g., TiO(2)); however, quantum tuning of the absorber then requires complete redesign of the bulk acceptor, compromising the benefits of facile quantum tuning. Here we report rectifying junctions constructed entirely using inherently band-aligned quantum-tuned materials. Realizing these quantum junction diodes relied upon the creation of an n-type quantum dot solid having a clean bandgap. We combine stable, chemically compatible, high-performance n-type and p-type materials to create the first quantum junction solar cells. We present a family of photovoltaic devices having widely tuned bandgaps of 0.6-1.6 eV that excel where conventional quantum-to-bulk devices fail to perform. Devices having optimal single-junction bandgaps exhibit certified AM1.5 solar power conversion efficiencies of 5.4%. Control over doping in quantum solids, and the successful integration of these materials to form stable quantum junctions, offers a powerful new degree of freedom to colloidal quantum dot optoelectronics.

  1. The molecular structure of 4-methylpyridine-N-oxide: Gas-phase electron diffraction and quantum chemical calculations

    NASA Astrophysics Data System (ADS)

    Belova, Natalya V.; Girichev, Georgiy V.; Kotova, Vitaliya E.; Korolkova, Kseniya A.; Trang, Nguyen Hoang

    2018-03-01

    The molecular structure of 4-methylpiridine-N-oxide, 4-MePyO, has been studied by gas-phase electron diffraction monitored by mass spectrometry (GED/MS) and quantum chemical (DFT) calculations. Both, quantum chemistry and GED analyses resulted in CS molecular symmetry with the planar pyridine ring. Obtained molecular parameters confirm the hyperconjugation in the pyridine ring and the sp2 hybridization concept of the nitrogen and carbon atoms in the ring. The experimental geometric parameters are in a good agreement with the parameters for non-substituted N-oxide and reproduced very closely by DFT calculations. The presence of the electron-donating CH3 substituent in 4-MePyO leads to a decrease of the ipso-angle and to an increase of r(N→O) in comparison with the non-substituted PyO. Electron density distribution analysis has been performed in terms of natural bond orbitals (NBO) scheme. The nature of the semipolar N→O bond is discussed.

  2. The IINS/quantum chemical studies of 17α- and 21-hydroxy-derivatives of progesterone

    NASA Astrophysics Data System (ADS)

    Szyczewski, A.; Hołderna-Natkaniec, K.; Natkaniec, I.

    2003-05-01

    The inelastic incoherent neutron scattering and quantum chemical studies have been performed on 17 and 21 hydroxy progesterone and the assignment of internal modes have been proposed in the range up to 700 cm -1. The lattice branch of PDS reveals modes which could be attributed to torsions of rings A and D (cyclohexane and cyclopentane) of the pregnane skeleton. An assignment of the torsional vibrations of methyl groups in the range 150-300 cm -1 and the deformation and out-of plane vibrations of CCOH groups has been proposed. An analysis of the effect of hydrogen bonds on PDS spectra has been performed.

  3. Predicting bioconcentration of chemicals into vegetation from soil or air using the molecular connectivity index

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Dowdy, D.L.; McKone, T.E.; Hsieh, D.P.H.

    1995-12-31

    Bioconcentration factors (BCFs) are the ratio of chemical concentration found in an exposed organism (in this case a plant) to the concentration in an air or soil exposure medium. The authors examine here the use of molecular connectivity indices (MCIs) as quantitative structure-activity relationships (QSARS) for predicting BCFs for organic chemicals between plants and air or soil. The authors compare the reliability of the octanol-air partition coefficient (K{sub oa}) to the MC based prediction method for predicting plant/air partition coefficients. The authors also compare the reliability of the octanol/water partition coefficient (K{sub ow}) to the MC based prediction method formore » predicting plant/soil partition coefficients. The results here indicate that, relative to the use of K{sub ow} or K{sub oa} as predictors of BCFs the MC can substantially increase the reliability with which BCFs can be estimated. The authors find that the MC provides a relatively precise and accurate method for predicting the potential biotransfer of a chemical from environmental media into plants. In addition, the MC is much faster and more cost effective than direct measurements.« less

  4. Novel naïve Bayes classification models for predicting the carcinogenicity of chemicals.

    PubMed

    Zhang, Hui; Cao, Zhi-Xing; Li, Meng; Li, Yu-Zhi; Peng, Cheng

    2016-11-01

    The carcinogenicity prediction has become a significant issue for the pharmaceutical industry. The purpose of this investigation was to develop a novel prediction model of carcinogenicity of chemicals by using a naïve Bayes classifier. The established model was validated by the internal 5-fold cross validation and external test set. The naïve Bayes classifier gave an average overall prediction accuracy of 90 ± 0.8% for the training set and 68 ± 1.9% for the external test set. Moreover, five simple molecular descriptors (e.g., AlogP, Molecular weight (M W ), No. of H donors, Apol and Wiener) considered as important for the carcinogenicity of chemicals were identified, and some substructures related to the carcinogenicity were achieved. Thus, we hope the established naïve Bayes prediction model could be applied to filter early-stage molecules for this potential carcinogenicity adverse effect; and the identified five simple molecular descriptors and substructures of carcinogens would give a better understanding of the carcinogenicity of chemicals, and further provide guidance for medicinal chemists in the design of new candidate drugs and lead optimization, ultimately reducing the attrition rate in later stages of drug development. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Quantum Metropolis sampling.

    PubMed

    Temme, K; Osborne, T J; Vollbrecht, K G; Poulin, D; Verstraete, F

    2011-03-03

    The original motivation to build a quantum computer came from Feynman, who imagined a machine capable of simulating generic quantum mechanical systems--a task that is believed to be intractable for classical computers. Such a machine could have far-reaching applications in the simulation of many-body quantum physics in condensed-matter, chemical and high-energy systems. Part of Feynman's challenge was met by Lloyd, who showed how to approximately decompose the time evolution operator of interacting quantum particles into a short sequence of elementary gates, suitable for operation on a quantum computer. However, this left open the problem of how to simulate the equilibrium and static properties of quantum systems. This requires the preparation of ground and Gibbs states on a quantum computer. For classical systems, this problem is solved by the ubiquitous Metropolis algorithm, a method that has basically acquired a monopoly on the simulation of interacting particles. Here we demonstrate how to implement a quantum version of the Metropolis algorithm. This algorithm permits sampling directly from the eigenstates of the Hamiltonian, and thus evades the sign problem present in classical simulations. A small-scale implementation of this algorithm should be achievable with today's technology.

  6. Improved Electrostatic Embedding for Fragment-Based Chemical Shift Calculations in Molecular Crystals.

    PubMed

    Hartman, Joshua D; Balaji, Ashwin; Beran, Gregory J O

    2017-12-12

    Fragment-based methods predict nuclear magnetic resonance (NMR) chemical shielding tensors in molecular crystals with high accuracy and computational efficiency. Such methods typically employ electrostatic embedding to mimic the crystalline environment, and the quality of the results can be sensitive to the embedding treatment. To improve the quality of this embedding environment for fragment-based molecular crystal property calculations, we borrow ideas from the embedded ion method to incorporate self-consistently polarized Madelung field effects. The self-consistent reproduction of the Madelung potential (SCRMP) model developed here constructs an array of point charges that incorporates self-consistent lattice polarization and which reproduces the Madelung potential at all atomic sites involved in the quantum mechanical region of the system. The performance of fragment- and cluster-based 1 H, 13 C, 14 N, and 17 O chemical shift predictions using SCRMP and density functionals like PBE and PBE0 are assessed. The improved embedding model results in substantial improvements in the predicted 17 O chemical shifts and modest improvements in the 15 N ones. Finally, the performance of the model is demonstrated by examining the assignment of the two oxygen chemical shifts in the challenging γ-polymorph of glycine. Overall, the SCRMP-embedded NMR chemical shift predictions are on par with or more accurate than those obtained with the widely used gauge-including projector augmented wave (GIPAW) model.

  7. NMRDSP: an accurate prediction of protein shape strings from NMR chemical shifts and sequence data.

    PubMed

    Mao, Wusong; Cong, Peisheng; Wang, Zhiheng; Lu, Longjian; Zhu, Zhongliang; Li, Tonghua

    2013-01-01

    Shape string is structural sequence and is an extremely important structure representation of protein backbone conformations. Nuclear magnetic resonance chemical shifts give a strong correlation with the local protein structure, and are exploited to predict protein structures in conjunction with computational approaches. Here we demonstrate a novel approach, NMRDSP, which can accurately predict the protein shape string based on nuclear magnetic resonance chemical shifts and structural profiles obtained from sequence data. The NMRDSP uses six chemical shifts (HA, H, N, CA, CB and C) and eight elements of structure profiles as features, a non-redundant set (1,003 entries) as the training set, and a conditional random field as a classification algorithm. For an independent testing set (203 entries), we achieved an accuracy of 75.8% for S8 (the eight states accuracy) and 87.8% for S3 (the three states accuracy). This is higher than only using chemical shifts or sequence data, and confirms that the chemical shift and the structure profile are significant features for shape string prediction and their combination prominently improves the accuracy of the predictor. We have constructed the NMRDSP web server and believe it could be employed to provide a solid platform to predict other protein structures and functions. The NMRDSP web server is freely available at http://cal.tongji.edu.cn/NMRDSP/index.jsp.

  8. Incorporating High-Throughput Exposure Predictions With Dosimetry-Adjusted In Vitro Bioactivity to Inform Chemical Toxicity Testing

    PubMed Central

    Wetmore, Barbara A.; Wambaugh, John F.; Allen, Brittany; Ferguson, Stephen S.; Sochaski, Mark A.; Setzer, R. Woodrow; Houck, Keith A.; Strope, Cory L.; Cantwell, Katherine; Judson, Richard S.; LeCluyse, Edward; Clewell, Harvey J.; Thomas, Russell S.; Andersen, Melvin E.

    2015-01-01

    We previously integrated dosimetry and exposure with high-throughput screening (HTS) to enhance the utility of ToxCast HTS data by translating in vitro bioactivity concentrations to oral equivalent doses (OEDs) required to achieve these levels internally. These OEDs were compared against regulatory exposure estimates, providing an activity-to-exposure ratio (AER) useful for a risk-based ranking strategy. As ToxCast efforts expand (ie, Phase II) beyond food-use pesticides toward a wider chemical domain that lacks exposure and toxicity information, prediction tools become increasingly important. In this study, in vitro hepatic clearance and plasma protein binding were measured to estimate OEDs for a subset of Phase II chemicals. OEDs were compared against high-throughput (HT) exposure predictions generated using probabilistic modeling and Bayesian approaches generated by the U.S. Environmental Protection Agency (EPA) ExpoCast program. This approach incorporated chemical-specific use and national production volume data with biomonitoring data to inform the exposure predictions. This HT exposure modeling approach provided predictions for all Phase II chemicals assessed in this study whereas estimates from regulatory sources were available for only 7% of chemicals. Of the 163 chemicals assessed in this study, 3 or 13 chemicals possessed AERs < 1 or < 100, respectively. Diverse bioactivities across a range of assays and concentrations were also noted across the wider chemical space surveyed. The availability of HT exposure estimation and bioactivity screening tools provides an opportunity to incorporate a risk-based strategy for use in testing prioritization. PMID:26251325

  9. CADRE-SS, an in Silico Tool for Predicting Skin Sensitization Potential Based on Modeling of Molecular Interactions.

    PubMed

    Kostal, Jakub; Voutchkova-Kostal, Adelina

    2016-01-19

    Using computer models to accurately predict toxicity outcomes is considered to be a major challenge. However, state-of-the-art computational chemistry techniques can now be incorporated in predictive models, supported by advances in mechanistic toxicology and the exponential growth of computing resources witnessed over the past decade. The CADRE (Computer-Aided Discovery and REdesign) platform relies on quantum-mechanical modeling of molecular interactions that represent key biochemical triggers in toxicity pathways. Here, we present an external validation exercise for CADRE-SS, a variant developed to predict the skin sensitization potential of commercial chemicals. CADRE-SS is a hybrid model that evaluates skin permeability using Monte Carlo simulations, assigns reactive centers in a molecule and possible biotransformations via expert rules, and determines reactivity with skin proteins via quantum-mechanical modeling. The results were promising with an overall very good concordance of 93% between experimental and predicted values. Comparison to performance metrics yielded by other tools available for this endpoint suggests that CADRE-SS offers distinct advantages for first-round screenings of chemicals and could be used as an in silico alternative to animal tests where permissible by legislative programs.

  10. Toward the realization of a compact chemical sensor platform using quantum cascade lasers

    NASA Astrophysics Data System (ADS)

    Holthoff, Ellen L.; Marcus, Logan S.; Pellegrino, Paul M.

    2015-05-01

    The Army is investigating several spectroscopic techniques (e.g., infrared spectroscopy) that could allow for an adaptable sensor platform. Traditionally, chemical sensing platforms have been hampered by the opposing concerns of increasing sensor capability while maintaining a minimal package size. Current sensors, although reasonably sized, are geared to more classical chemical threats, and the ability to expand their capabilities to a broader range of emerging threats is uncertain. Recently, photoacoustic spectroscopy, employed in a sensor format, has shown enormous potential to address these ever-changing threats, while maintaining a compact sensor design. In order to realize the advantage of photoacoustic sensor miniaturization, light sources of comparable size are required. Recent research has employed quantum cascade lasers (QCLs) in combination with MEMS-scale photoacoustic cell designs. The continuous tuning capability of QCLs over a broad wavelength range in the mid-infrared spectral region greatly expands the number of compounds that can be identified. Results have demonstrated that utilizing a tunable QCL with a MEMS-scale photoacoustic cell produces favorable detection limits (ppb levels) for chemical targets (e.g., dimethyl methyl phosphonate (DMMP), vinyl acetate, 1,4-dioxane). Although our chemical sensing research has benefitted from the broad tuning capabilities of QCLs, the limitations of these sources must be considered. Current commercially available tunable systems are still expensive and obviously geared more toward laboratory operation, not fielding. Although the laser element itself is quite small, the packaging, power supply, and controller remain logistical burdens. Additionally, operational features such as continuous wave (CW) modulation and laser output powers while maintaining wide tunability are not yet ideal for a variety of sensing applications. In this paper, we will discuss our continuing evaluation of QCL technology as it matures

  11. Generalized Causal Quantum Theories

    NASA Astrophysics Data System (ADS)

    Parmeggiani, Claudio

    2007-12-01

    We shall show that is always possible to construct causal Quantum Theories fully equivalent (as predictive tools) to acausal, standard Quantum Theory, relativistic or not relativistic; we re-obtain, as a particular case, the usual Quantum Bohmian Theory. Then we consider the measurement process, in causal theories, and we conclude that the state of affairs is not really improved, with respect to standard theories.

  12. Quantum interpolation for high-resolution sensing.

    PubMed

    Ajoy, Ashok; Liu, Yi-Xiang; Saha, Kasturi; Marseglia, Luca; Jaskula, Jean-Christophe; Bissbort, Ulf; Cappellaro, Paola

    2017-02-28

    Recent advances in engineering and control of nanoscale quantum sensors have opened new paradigms in precision metrology. Unfortunately, hardware restrictions often limit the sensor performance. In nanoscale magnetic resonance probes, for instance, finite sampling times greatly limit the achievable sensitivity and spectral resolution. Here we introduce a technique for coherent quantum interpolation that can overcome these problems. Using a quantum sensor associated with the nitrogen vacancy center in diamond, we experimentally demonstrate that quantum interpolation can achieve spectroscopy of classical magnetic fields and individual quantum spins with orders of magnitude finer frequency resolution than conventionally possible. Not only is quantum interpolation an enabling technique to extract structural and chemical information from single biomolecules, but it can be directly applied to other quantum systems for superresolution quantum spectroscopy.

  13. Use of QSARs in international decision-making frameworks to predict ecologic effects and environmental fate of chemical substances.

    PubMed Central

    Cronin, Mark T D; Walker, John D; Jaworska, Joanna S; Comber, Michael H I; Watts, Christopher D; Worth, Andrew P

    2003-01-01

    This article is a review of the use, by regulatory agencies and authorities, of quantitative structure-activity relationships (QSARs) to predict ecologic effects and environmental fate of chemicals. For many years, the U.S. Environmental Protection Agency has been the most prominent regulatory agency using QSARs to predict the ecologic effects and environmental fate of chemicals. However, as increasing numbers of standard QSAR methods are developed and validated to predict ecologic effects and environmental fate of chemicals, it is anticipated that more regulatory agencies and authorities will find them to be acceptable alternatives to chemical testing. PMID:12896861

  14. Predicting ion specific capacitances of supercapacitors due to quantum ionic interactions.

    PubMed

    Parsons, Drew F

    2014-08-01

    A new theoretical framework is now available to help explain ion specific (Hofmeister) effects. All measurements in physical chemistry show ion specificity, inexplicable by classical electrostatic theories. These ignore ionic dispersion forces that change ionic adsorption. We explored ion specificity in supercapacitors using a modified Poisson-Boltzmann approach that includes ionic dispersion energies. We have applied ab initio quantum chemical methods to determine required ion sizes and ion polarisabilities. Our model represents graphite electrodes through their optical dielectric spectra. The electrolyte was 1.2 M Li salt in propylene carbonate, using the common battery anions, PF6(-), BF4(-) and ClO4(-). We also investigated the perhalate series with BrO4(-) and IO4(-). The capacitance C=dσ/dψ was calculated from the predicted electrode surface charge σ of each electrode with potential ψ between electrodes. Compared to the purely electrostatic calculation, the capacitance of a positively charged graphite electrode was enhanced by more than 15%, with PF6(-) showing >50% increase in capacitance. IO4(-) provided minimal enhancement. The enhancement is due to adsorption of both anions and cations, driven by ionic dispersion forces. The Hofmeister series in the single-electrode capacitance was PF6(-)>BF4(-)>ClO4(-)>BrO4(-)>IO4(-) . When the graphite electrode was negatively charged, the perhalates provided almost no enhancement of capacitance, while PF6(-) and BF4(-) decreased capacitance by about 15%. Due to the asymmetric impact of nonelectrostatic ion interactions, the capacitances of positive and negative electrodes are not equal. The capacitance of a supercapacitor should therefore be reported as two values rather than one, similar to the matrix of mutual capacitances used in multielectrode devices. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. Students' Predictions about the Sensory Properties of Chemical Compounds: Additive versus Emergent Frameworks

    ERIC Educational Resources Information Center

    Talanquer, Vicente

    2008-01-01

    We investigated general chemistry students' intuitive ideas about the expected properties of the products of a chemical reaction. In particular, we analyzed college chemistry students' predictions about the color, smell, and taste of the products of chemical reactions represented at the molecular level. The study was designed to explore the extent…

  16. In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle.

    PubMed

    Castilhos, A M; Francisco, C L; Branco, R H; Bonilha, S F M; Mercadante, M E Z; Meirelles, P R L; Pariz, C M; Jorge, A M

    2018-05-04

    Evaluation of the body chemical composition of beef cattle can only be measured postmortem and those data cannot be used in real production scenarios to adjust nutritional plans. The objective of this study was to develop multiple linear regression equations from in vivo measurements, such as ultrasound parameters [backfat thickness (uBFT, mm), rump fat thickness (uRF, mm), and ribeye area (uLMA, cm2)], shrunk body weight (SBW, kg), age (AG, d), hip height (HH, m), as well as from postmortem measurements (composition of the 9th to 11th rib section) to predict the empty body and carcass chemical composition for Nellore cattle. Thirty-three young bulls were used (339 ± 36.15 kg and 448 ± 17.78 d for initial weight and age, respectively). Empty body chemical composition (protein, fat, water, and ash in kg) was obtained by combining noncarcass and carcass components. Data were analyzed using the PROC REG procedure of SAS software. Mallows' Cp values were close to the ideal value of number of independent variables in the prediction equations plus one. Equations to predict chemical components of both empty body and carcass using in vivo measurements presented higher R2 values than those determined by postmortem measurements. Chemical composition of the empty body using in vivo measurements was predicted with R2 > 0.73. Equations to predict chemical composition of the carcass from in vivo measurements showed R2 lower (R2< 0.68) than observed for empty body, except for the water (R2 = 0.84). The independent variables SBW, uRF, and AG were sufficient to predict the fat, water, energy components of the empty body, whereas for estimation of protein content the uRF, HH, and SBW were satisfactory. For the calculation of the ash, the SBW variable in the equation was sufficient. Chemical compounds from components of the empty body of Nellore cattle can be calculated by the following equations: protein (kg) = 47.92 + 0.18 × SBW - 1.46 × uRF - 30.72 × HH (R2 = 0.94, RMSPE = 1

  17. Developing a predictive model for the chemical composition of soot nanoparticles

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Violi, Angela; Michelsen, Hope; Hansen, Nils

    In order to provide the scientific foundation to enable technology breakthroughs in transportation fuel, it is important to develop a combustion modeling capability to optimize the operation and design of evolving fuels in advanced engines for transportation applications. The goal of this proposal is to develop a validated predictive model to describe the chemical composition of soot nanoparticles in premixed and diffusion flames. Atomistic studies in conjunction with state-of-the-art experiments are the distinguishing characteristics of this unique interdisciplinary effort. The modeling effort has been conducted at the University of Michigan by Prof. A. Violi. The experimental work has entailed amore » series of studies using different techniques to analyze gas-phase soot precursor chemistry and soot particle production in premixed and diffusion flames. Measurements have provided spatial distributions of polycyclic aromatic hydrocarbons and other gas-phase species and size and composition of incipient soot nanoparticles for comparison with model results. The experimental team includes Dr. N. Hansen and H. Michelsen at Sandia National Labs' Combustion Research Facility, and Dr. K. Wilson as collaborator at Lawrence Berkeley National Lab's Advanced Light Source. Our results show that the chemical and physical properties of nanoparticles affect the coagulation behavior in soot formation, and our results on an experimentally validated, predictive model for the chemical composition of soot nanoparticles will not only enhance our understanding of soot formation since but will also allow the prediction of particle size distributions under combustion conditions. These results provide a novel description of soot formation based on physical and chemical properties of the particles for use in the next generation of soot models and an enhanced capability for facilitating the design of alternative fuels and the engines they will power.« less

  18. Predicting in vivo effect levels for repeat-dose systemic toxicity using chemical, biological, kinetic and study covariates.

    PubMed

    Truong, Lisa; Ouedraogo, Gladys; Pham, LyLy; Clouzeau, Jacques; Loisel-Joubert, Sophie; Blanchet, Delphine; Noçairi, Hicham; Setzer, Woodrow; Judson, Richard; Grulke, Chris; Mansouri, Kamel; Martin, Matthew

    2018-02-01

    In an effort to address a major challenge in chemical safety assessment, alternative approaches for characterizing systemic effect levels, a predictive model was developed. Systemic effect levels were curated from ToxRefDB, HESS-DB and COSMOS-DB from numerous study types totaling 4379 in vivo studies for 1247 chemicals. Observed systemic effects in mammalian models are a complex function of chemical dynamics, kinetics, and inter- and intra-individual variability. To address this complex problem, systemic effect levels were modeled at the study-level by leveraging study covariates (e.g., study type, strain, administration route) in addition to multiple descriptor sets, including chemical (ToxPrint, PaDEL, and Physchem), biological (ToxCast), and kinetic descriptors. Using random forest modeling with cross-validation and external validation procedures, study-level covariates alone accounted for approximately 15% of the variance reducing the root mean squared error (RMSE) from 0.96 log 10 to 0.85 log 10  mg/kg/day, providing a baseline performance metric (lower expectation of model performance). A consensus model developed using a combination of study-level covariates, chemical, biological, and kinetic descriptors explained a total of 43% of the variance with an RMSE of 0.69 log 10  mg/kg/day. A benchmark model (upper expectation of model performance) was also developed with an RMSE of 0.5 log 10  mg/kg/day by incorporating study-level covariates and the mean effect level per chemical. To achieve a representative chemical-level prediction, the minimum study-level predicted and observed effect level per chemical were compared reducing the RMSE from 1.0 to 0.73 log 10  mg/kg/day, equivalent to 87% of predictions falling within an order-of-magnitude of the observed value. Although biological descriptors did not improve model performance, the final model was enriched for biological descriptors that indicated xenobiotic metabolism gene expression, oxidative stress, and

  19. Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.

    PubMed

    Liu, Mei; Wu, Yonghui; Chen, Yukun; Sun, Jingchun; Zhao, Zhongming; Chen, Xue-wen; Matheny, Michael Edwin; Xu, Hua

    2012-06-01

    Adverse drug reaction (ADR) is one of the major causes of failure in drug development. Severe ADRs that go undetected until the post-marketing phase of a drug often lead to patient morbidity. Accurate prediction of potential ADRs is required in the entire life cycle of a drug, including early stages of drug design, different phases of clinical trials, and post-marketing surveillance. Many studies have utilized either chemical structures or molecular pathways of the drugs to predict ADRs. Here, the authors propose a machine-learning-based approach for ADR prediction by integrating the phenotypic characteristics of a drug, including indications and other known ADRs, with the drug's chemical structures and biological properties, including protein targets and pathway information. A large-scale study was conducted to predict 1385 known ADRs of 832 approved drugs, and five machine-learning algorithms for this task were compared. This evaluation, based on a fivefold cross-validation, showed that the support vector machine algorithm outperformed the others. Of the three types of information, phenotypic data were the most informative for ADR prediction. When biological and phenotypic features were added to the baseline chemical information, the ADR prediction model achieved significant improvements in area under the curve (from 0.9054 to 0.9524), precision (from 43.37% to 66.17%), and recall (from 49.25% to 63.06%). Most importantly, the proposed model successfully predicted the ADRs associated with withdrawal of rofecoxib and cerivastatin. The results suggest that phenotypic information on drugs is valuable for ADR prediction. Moreover, they demonstrate that different models that combine chemical, biological, or phenotypic information can be built from approved drugs, and they have the potential to detect clinically important ADRs in both preclinical and post-marketing phases.

  20. Efficient universal quantum channel simulation in IBM's cloud quantum computer

    NASA Astrophysics Data System (ADS)

    Wei, Shi-Jie; Xin, Tao; Long, Gui-Lu

    2018-07-01

    The study of quantum channels is an important field and promises a wide range of applications, because any physical process can be represented as a quantum channel that transforms an initial state into a final state. Inspired by the method of performing non-unitary operators by the linear combination of unitary operations, we proposed a quantum algorithm for the simulation of the universal single-qubit channel, described by a convex combination of "quasi-extreme" channels corresponding to four Kraus operators, and is scalable to arbitrary higher dimension. We demonstrated the whole algorithm experimentally using the universal IBM cloud-based quantum computer and studied the properties of different qubit quantum channels. We illustrated the quantum capacity of the general qubit quantum channels, which quantifies the amount of quantum information that can be protected. The behavior of quantum capacity in different channels revealed which types of noise processes can support information transmission, and which types are too destructive to protect information. There was a general agreement between the theoretical predictions and the experiments, which strongly supports our method. By realizing the arbitrary qubit channel, this work provides a universally- accepted way to explore various properties of quantum channels and novel prospect for quantum communication.

  1. Defect states in hexagonal boron nitride: Assignments of observed properties and prediction of properties relevant to quantum computation

    NASA Astrophysics Data System (ADS)

    Sajid, A.; Reimers, Jeffrey R.; Ford, Michael J.

    2018-02-01

    Key properties of nine possible defect sites in hexagonal boron nitride (h-BN), VN,VN -1,CN,VNO2 B,VNNB,VNCB,VBCN,VBCNS iN , and VNCBS iB , are predicted using density-functional theory and are corrected by applying results from high-level ab initio calculations. Observed h-BN electron-paramagnetic resonance signals at 22.4, 20.83, and 352.70 MHz are assigned to VN,CN, and VNO2 B , respectively, while the observed photoemission at 1.95 eV is assigned to VNCB . Detailed consideration of the available excited states, allowed spin-orbit couplings, zero-field splitting, and optical transitions is made for the two related defects VNCB and VBCN . VNCB is proposed for realizing long-lived quantum memory in h-BN. VBCN is predicted to have a triplet ground state, implying that spin initialization by optical means is feasible and suitable optical excitations are identified, making this defect of interest for possible quantum-qubit operations.

  2. PRISM 3: expanded prediction of natural product chemical structures from microbial genomes

    PubMed Central

    Skinnider, Michael A.; Merwin, Nishanth J.; Johnston, Chad W.

    2017-01-01

    Abstract Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/. PMID:28460067

  3. Quantum chemical approach for condensed-phase thermochemistry (V): Development of rigid-body type harmonic solvation model

    NASA Astrophysics Data System (ADS)

    Tarumi, Moto; Nakai, Hiromi

    2018-05-01

    This letter proposes an approximate treatment of the harmonic solvation model (HSM) assuming the solute to be a rigid body (RB-HSM). The HSM method can appropriately estimate the Gibbs free energy for condensed phases even where an ideal gas model used by standard quantum chemical programs fails. The RB-HSM method eliminates calculations for intra-molecular vibrations in order to reduce the computational costs. Numerical assessments indicated that the RB-HSM method can evaluate entropies and internal energies with the same accuracy as the HSM method but with lower calculation costs.

  4. Prediction of Quantum Anomalous Hall Insulator in half-fluorinated GaBi Honeycomb

    PubMed Central

    Chen, Sung-Ping; Huang, Zhi-Quan; Crisostomo, Christian P.; Hsu, Chia-Hsiu; Chuang, Feng-Chuan; Lin, Hsin; Bansil, Arun

    2016-01-01

    Using first-principles electronic structure calculations, we predict half-fluorinated GaBi honeycomb under tensile strain to harbor a quantum anomalous Hall (QAH) insulator phase. We show that this QAH phase is driven by a single inversion in the band structure at the Γ point. Moreover, we have computed the electronic spectrum of a half-fluorinated GaBi nanoribbon with zigzag edges, which shows that only one edge band crosses the Fermi level within the band gap. Our results suggest that half-fluorination of the GaBi honeycomb under tensile strain could provide a new platform for developing novel spintronics devices based on the QAH effect. PMID:27507248

  5. Chemical Modeling for Predicting the Abundances of Certain Aldimines and Amines in Hot Cores

    NASA Astrophysics Data System (ADS)

    Sil, Milan; Gorai, Prasanta; Das, Ankan; Bhat, Bratati; Etim, Emmanuel E.; Chakrabarti, Sandip K.

    2018-02-01

    We consider six isomeric groups ({{CH}}3{{N}}, {{CH}}5{{N}}, {{{C}}}2{{{H}}}5{{N}}, {{{C}}}2{{{H}}}7{{N}}, {{{C}}}3{{{H}}}7{{N}}, and {{{C}}}3{{{H}}}9{{N}}) to review the presence of amines and aldimines within the interstellar medium (ISM). Each of these groups contains at least one aldimine or amine. Methanimine ({{CH}}2{NH}) from {{CH}}3{{N}} and methylamine ({{CH}}3{{NH}}2) from {{CH}}5{{N}} isomeric group were detected a few decades ago. Recently, the presence of ethanimine ({{CH}}3{CHNH}) from {{{C}}}2{{{H}}}5{{N}} isomeric group has been discovered in the ISM. This prompted us to investigate the possibility of detecting any aldimine or amine from the very next three isomeric groups in this sequence: {{{C}}}2{{{H}}}7{{N}}, {{{C}}}3{{{H}}}7{{N}}, and {{{C}}}3{{{H}}}9{{N}}. We employ high-level quantum chemical calculations to estimate accurate energies of all the species. According to enthalpies of formation, optimized energies, and expected intensity ratio, we found that ethylamine (precursor of glycine) from {{{C}}}2{{{H}}}7{{N}} isomeric group, (1Z)-1-propanimine from {{{C}}}3{{{H}}}7{{N}} isomeric group, and trimethylamine from {{{C}}}3{{{H}}}9{{N}} isomeric group are the most viable candidates for the future astronomical detection. Based on our quantum chemical calculations and from other approximations (from prevailing similar types of reactions), a complete set of reaction pathways to the synthesis of ethylamine and (1Z)-1-propanimine is prepared. Moreover, a large gas-grain chemical model is employed to study the presence of these species in the ISM. Our modeling results suggest that ethylamine and (1Z)-1-propanimine could efficiently be formed in hot-core regions and could be observed with present astronomical facilities. Radiative transfer modeling is also implemented to additionally aid their discovery in interstellar space.

  6. Simulation of quantum dynamics based on the quantum stochastic differential equation.

    PubMed

    Li, Ming

    2013-01-01

    The quantum stochastic differential equation derived from the Lindblad form quantum master equation is investigated. The general formulation in terms of environment operators representing the quantum state diffusion is given. The numerical simulation algorithm of stochastic process of direct photodetection of a driven two-level system for the predictions of the dynamical behavior is proposed. The effectiveness and superiority of the algorithm are verified by the performance analysis of the accuracy and the computational cost in comparison with the classical Runge-Kutta algorithm.

  7. Quantum chemical study on the stability of honeybee queen pheromone against atmospheric factors.

    PubMed

    Shi, Rongwei; Liu, Fanglin

    2016-06-01

    The managed honeybee, Apis mellifera, has been experienced a puzzling event, termed as colony collapse disorder (CCD), in which worker bees abruptly disappear from their hives. Potential factors include parasites, pesticides, malnutrition, and environmental stresses. However, so far, no definitive relationship has been established between specific causal factors and CCD events. Here we theoretically test whether atmospheric environment could disturb the chemical communication between the queen and their workers in a colony. A quantum chemistry method has been used to investigate for the stability of the component of A. mellifera queen mandibular pheromone (QMP), (E)-9-keto-2-decenoic acid (9-ODA), against atmospheric water and free radicals. The results show that 9-ODA is less likely to react with water due to the high barrier heights (~36.5 kcal · mol(-1)) and very low reaction rates. However, it can easily react with triplet oxygen and hydroxyl radicals because of low or negative energy barriers. Thus, the atmospheric free radicals may disturb the chemical communication between the queen and their daughters in a colony. Our pilot study provides new insight for the cause of CCD, which has been reported throughout the world.

  8. ToxCast: Developing Predictive Signatures of Chemically Induced Toxicity (Developing Predictive Bioactivity Signatures from ToxCasts HTS Data)

    EPA Science Inventory

    ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry, bioactivity profiling and toxicogenomic data to predict potential for toxicity and prioritize limited testing resour...

  9. Quantum Foam

    ScienceCinema

    Lincoln, Don

    2018-01-16

    The laws of quantum mechanics and relativity are quite perplexing however it is when the two theories are merged that things get really confusing. This combined theory predicts that empty space isn’t empty at all – it’s a seething and bubbling cauldron of matter and antimatter particles springing into existence before disappearing back into nothingness. Scientists call this complicated state of affairs “quantum foam.” In this video, Fermilab’s Dr. Don Lincoln discusses this mind-bending idea and sketches some of the experiments that have convinced scientists that this crazy prediction is actually true.

  10. A unified algorithm for predicting partition coefficients for PBPK modeling of drugs and environmental chemicals

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Peyret, Thomas; Poulin, Patrick; Krishnan, Kannan, E-mail: kannan.krishnan@umontreal.ca

    The algorithms in the literature focusing to predict tissue:blood PC (P{sub tb}) for environmental chemicals and tissue:plasma PC based on total (K{sub p}) or unbound concentration (K{sub pu}) for drugs differ in their consideration of binding to hemoglobin, plasma proteins and charged phospholipids. The objective of the present study was to develop a unified algorithm such that P{sub tb}, K{sub p} and K{sub pu} for both drugs and environmental chemicals could be predicted. The development of the unified algorithm was accomplished by integrating all mechanistic algorithms previously published to compute the PCs. Furthermore, the algorithm was structured in such amore » way as to facilitate predictions of the distribution of organic compounds at the macro (i.e. whole tissue) and micro (i.e. cells and fluids) levels. The resulting unified algorithm was applied to compute the rat P{sub tb}, K{sub p} or K{sub pu} of muscle (n = 174), liver (n = 139) and adipose tissue (n = 141) for acidic, neutral, zwitterionic and basic drugs as well as ketones, acetate esters, alcohols, aliphatic hydrocarbons, aromatic hydrocarbons and ethers. The unified algorithm reproduced adequately the values predicted previously by the published algorithms for a total of 142 drugs and chemicals. The sensitivity analysis demonstrated the relative importance of the various compound properties reflective of specific mechanistic determinants relevant to prediction of PC values of drugs and environmental chemicals. Overall, the present unified algorithm uniquely facilitates the computation of macro and micro level PCs for developing organ and cellular-level PBPK models for both chemicals and drugs.« less

  11. Integrative Approaches for Predicting in vivo Effects of Chemicals from their Structural Descriptors and the Results of Short-term Biological Assays

    PubMed Central

    Low, Yen S.; Sedykh, Alexander; Rusyn, Ivan; Tropsha, Alexander

    2017-01-01

    Cheminformatics approaches such as Quantitative Structure Activity Relationship (QSAR) modeling have been used traditionally for predicting chemical toxicity. In recent years, high throughput biological assays have been increasingly employed to elucidate mechanisms of chemical toxicity and predict toxic effects of chemicals in vivo. The data generated in such assays can be considered as biological descriptors of chemicals that can be combined with molecular descriptors and employed in QSAR modeling to improve the accuracy of toxicity prediction. In this review, we discuss several approaches for integrating chemical and biological data for predicting biological effects of chemicals in vivo and compare their performance across several data sets. We conclude that while no method consistently shows superior performance, the integrative approaches rank consistently among the best yet offer enriched interpretation of models over those built with either chemical or biological data alone. We discuss the outlook for such interdisciplinary methods and offer recommendations to further improve the accuracy and interpretability of computational models that predict chemical toxicity. PMID:24805064

  12. Accurate prediction of acute fish toxicity of fragrance chemicals with the RTgill-W1 cell assay.

    PubMed

    Natsch, Andreas; Laue, Heike; Haupt, Tina; von Niederhäusern, Valentin; Sanders, Gordon

    2018-03-01

    Testing for acute fish toxicity is an integral part of the environmental safety assessment of chemicals. A true replacement of primary fish tissue was recently proposed using cell viability in a fish gill cell line (RTgill-W1) as a means of predicting acute toxicity, showing good predictivity on 35 chemicals. To promote regulatory acceptance, the predictivity and applicability domain of novel tests need to be carefully evaluated on chemicals with existing high-quality in vivo data. We applied the RTgill-W1 cell assay to 38 fragrance chemicals with a wide range of both physicochemical properties and median lethal concentration (LC50) values and representing a diverse range of chemistries. A strong correlation (R 2  = 0.90-0.94) between the logarithmic in vivo LC50 values, based on fish mortality, and the logarithmic in vitro median effect concentration (EC50) values based on cell viability was observed. A leave-one-out analysis illustrates a median under-/overprediction from in vitro EC50 values to in vivo LC50 values by a factor of 1.5. This assay offers a simple, accurate, and reliable alternative to in vivo acute fish toxicity testing for chemicals, presumably acting mainly by a narcotic mode of action. Furthermore, the present study provides validation of the predictivity of the RTgill-W1 assay on a completely independent set of chemicals that had not been previously tested and indicates that fragrance chemicals are clearly within the applicability domain. Environ Toxicol Chem 2018;37:931-941. © 2017 SETAC. © 2017 SETAC.

  13. Quantum interpolation for high-resolution sensing

    PubMed Central

    Ajoy, Ashok; Liu, Yi-Xiang; Saha, Kasturi; Marseglia, Luca; Jaskula, Jean-Christophe; Bissbort, Ulf; Cappellaro, Paola

    2017-01-01

    Recent advances in engineering and control of nanoscale quantum sensors have opened new paradigms in precision metrology. Unfortunately, hardware restrictions often limit the sensor performance. In nanoscale magnetic resonance probes, for instance, finite sampling times greatly limit the achievable sensitivity and spectral resolution. Here we introduce a technique for coherent quantum interpolation that can overcome these problems. Using a quantum sensor associated with the nitrogen vacancy center in diamond, we experimentally demonstrate that quantum interpolation can achieve spectroscopy of classical magnetic fields and individual quantum spins with orders of magnitude finer frequency resolution than conventionally possible. Not only is quantum interpolation an enabling technique to extract structural and chemical information from single biomolecules, but it can be directly applied to other quantum systems for superresolution quantum spectroscopy. PMID:28196889

  14. Experimental and Quantum-Chemical Study of Electronically Excited States of Protolytic Isovanillin Species

    NASA Astrophysics Data System (ADS)

    Vusovich, O. V.; Tchaikovskaya, O. N.; Sokolova, I. V.; Vasil'eva, N. Yu.

    2014-05-01

    Methods of electronic spectroscopy and quantum chemistry are used to compare protolytic vanillin and isovanillin species. Three protolytic species: anion, cation, and neutral are distinguished in the ground state of the examined molecules. Vanillin and isovanillin in the ground state in water possess identical spectral characteristics: line positions and intensities in the absorption spectra coincide. Minima of the electrostatic potential demonstrate that the deepest isomer minimum is observed on the carbonyl oxygen atom. However, investigations of the fluorescence spectra show that the radiative properties of isomers differ. An analysis of results of quantum-chemical calculations demonstrate that the long-wavelength ππ* transition in the vanillin absorption spectra is formed due to electron charge transfer from the phenol part of the molecule to oxygen atoms of the methoxy and carbonyl groups, and in the isovanillin absorption spectra, it is formed only on the oxygen atom of the methoxy group. The presence of hydroxyl and carbonyl groups in the structure of the examined molecules leads to the fact that isovanillin in the ground S0 state, the same as vanillin, possesses acidic properties, whereas in the excited S1 state, they possess basic properties. A comparison of the рKа values of aqueous solutions demonstrates that vanillin possesses stronger acidic and basic properties in comparison with isovanillin.

  15. Quantum probability ranking principle for ligand-based virtual screening.

    PubMed

    Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

    2017-04-01

    Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

  16. Quantum probability ranking principle for ligand-based virtual screening

    NASA Astrophysics Data System (ADS)

    Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

    2017-04-01

    Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

  17. Characterization and prediction of chemical functions and weight fractions in consumer products.

    PubMed

    Isaacs, Kristin K; Goldsmith, Michael-Rock; Egeghy, Peter; Phillips, Katherine; Brooks, Raina; Hong, Tao; Wambaugh, John F

    2016-01-01

    Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents). We combined these functions with weight fraction data for 4115 personal care products (PCPs) to characterize the composition of 66 different product categories (e.g., shampoos). We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR) classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties). We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-based chemical prioritization.

  18. Conductance in inhomogeneous quantum wires: Luttinger liquid predictions and quantum Monte Carlo results

    NASA Astrophysics Data System (ADS)

    Morath, D.; Sedlmayr, N.; Sirker, J.; Eggert, S.

    2016-09-01

    We study electron and spin transport in interacting quantum wires contacted by noninteracting leads. We theoretically model the wire and junctions as an inhomogeneous chain where the parameters at the junction change on the scale of the lattice spacing. We study such systems analytically in the appropriate limits based on Luttinger liquid theory and compare the results to quantum Monte Carlo calculations of the conductances and local densities near the junction. We first consider an inhomogeneous spinless fermion model with a nearest-neighbor interaction and then generalize our results to a spinful model with an on-site Hubbard interaction.

  19. Isolation, characterization, spectroscopic properties and quantum chemical computations of an important phytoalexin resveratrol as antioxidant component from Vitis labrusca L. and their chemical compositions

    NASA Astrophysics Data System (ADS)

    Güder, Aytaç; Korkmaz, Halil; Gökce, Halil; Alpaslan, Yelda Bingöl; Alpaslan, Gökhan

    2014-12-01

    In this study, isolation and characterization of trans-resveratrol (RES) as an antioxidant compound were carried out from VLE, VLG and VLS. Furthermore, antioxidant activities were evaluated by using six different methods. Finally, total phenolic, flavonoid, ascorbic acid, anthocyanin, lycopene, β-carotene and vitamin E contents were carried out. In addition, the FT-IR, 13C and 1H NMR chemical shifts and UV-vis. spectra of trans-resveratrol were experimentally recorded. Quantum chemical computations such as the molecular geometry, vibrational frequencies, UV-vis. spectroscopic parameters, HOMOs-LUMOs energies, molecular electrostatic potential (MEP), natural bond orbitals (NBO) and nonlinear optics (NLO) properties of title molecule have been calculated by using DFT/B3PW91 method with 6-311++G(d,p) basis set in ground state for the first time. The obtained results show that the calculated spectroscopic data are in a good agreement with experimental data.

  20. Predictive performance of the human Cell Line Activation Test (h-CLAT) for lipophilic chemicals with high octanol-water partition coefficients.

    PubMed

    Takenouchi, Osamu; Miyazawa, Masaaki; Saito, Kazutoshi; Ashikaga, Takao; Sakaguchi, Hitoshi

    2013-01-01

    To meet the urgent need for a reliable alternative test for predicting skin sensitizing potential of many chemicals, we have developed a cell-based in vitro test, human Cell Line Activation Test (h-CLAT). However, the predictive performance for lipophilic chemicals in the h-CLAT still remains relatively unknown. Moreover, it's suggested that low water solubility of chemicals might induce false negative outcomes. Thus, in this study, we tested relatively low water soluble 37 chemicals with log Kow values above and below 3.5 in the h-CLAT. The small-scale assessment resulted in nine false negative outcomes for chemicals with log Kow values greater than 3.5. We then created a dataset of 143 chemicals by combining the existing dataset of 106 chemicals and examined the predictive performance of the h-CLAT for chemicals with a log Kow of less than 3.5; a total of 112 chemicals from the 143 chemicals in the dataset. The sensitivity and overall accuracy for the 143 chemicals were 83% and 80%, respectively. In contrast, sensitivity and overall accuracy for the 112 chemicals with log Kow values below 3.5 improved to 94% and 88%, respectively. These data suggested that the h-CLAT could successfully detect sensitizers with log Kow values up to 3.5. When chemicals with log Kow values greater than 3.5 that were deemed positive by h-CLAT were included with the 112 chemicals, the sensitivity and accuracy in terms of the resulting applicable 128 chemicals out of the 143 chemicals became 95% and 88%, respectively. The use of log Kow values gave the h-CLAT a higher predictive performance. Our results demonstrated that the h-CLAT could predict sensitizing potential of various chemicals, which contain lipophilic chemicals using a large-scale chemical dataset.

  1. A cascaded QSAR model for efficient prediction of overall power conversion efficiency of all-organic dye-sensitized solar cells.

    PubMed

    Li, Hongzhi; Zhong, Ziyan; Li, Lin; Gao, Rui; Cui, Jingxia; Gao, Ting; Hu, Li Hong; Lu, Yinghua; Su, Zhong-Min; Li, Hui

    2015-05-30

    A cascaded model is proposed to establish the quantitative structure-activity relationship (QSAR) between the overall power conversion efficiency (PCE) and quantum chemical molecular descriptors of all-organic dye sensitizers. The cascaded model is a two-level network in which the outputs of the first level (JSC, VOC, and FF) are the inputs of the second level, and the ultimate end-point is the overall PCE of dye-sensitized solar cells (DSSCs). The model combines quantum chemical methods and machine learning methods, further including quantum chemical calculations, data division, feature selection, regression, and validation steps. To improve the efficiency of the model and reduce the redundancy and noise of the molecular descriptors, six feature selection methods (multiple linear regression, genetic algorithms, mean impact value, forward selection, backward elimination, and +n-m algorithm) are used with the support vector machine. The best established cascaded model predicts the PCE values of DSSCs with a MAE of 0.57 (%), which is about 10% of the mean value PCE (5.62%). The validation parameters according to the OECD principles are R(2) (0.75), Q(2) (0.77), and Qcv2 (0.76), which demonstrate the great goodness-of-fit, predictivity, and robustness of the model. Additionally, the applicability domain of the cascaded QSAR model is defined for further application. This study demonstrates that the established cascaded model is able to effectively predict the PCE for organic dye sensitizers with very low cost and relatively high accuracy, providing a useful tool for the design of dye sensitizers with high PCE. © 2015 Wiley Periodicals, Inc.

  2. Quantum chemistry in environmental pesticide risk assessment.

    PubMed

    Villaverde, Juan J; López-Goti, Carmen; Alcamí, Manuel; Lamsabhi, Al Mokhtar; Alonso-Prados, José L; Sandín-España, Pilar

    2017-11-01

    The scientific community and regulatory bodies worldwide, currently promote the development of non-experimental tests that produce reliable data for pesticide risk assessment. The use of standard quantum chemistry methods could allow the development of tools to perform a first screening of compounds to be considered for the experimental studies, improving the risk assessment. This fact results in a better distribution of resources and in better planning, allowing a more exhaustive study of the pesticides and their metabolic products. The current paper explores the potential of quantum chemistry in modelling toxicity and environmental behaviour of pesticides and their by-products by using electronic descriptors obtained computationally. Quantum chemistry has potential to estimate the physico-chemical properties of pesticides, including certain chemical reaction mechanisms and their degradation pathways, allowing modelling of the environmental behaviour of both pesticides and their by-products. In this sense, theoretical methods can contribute to performing a more focused risk assessment of pesticides used in the market, and may lead to higher quality and safer agricultural products. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  3. Observation of the Quantum Anomalous Hall Insulator to Anderson Insulator Quantum Phase Transition and its Scaling Behavior.

    PubMed

    Chang, Cui-Zu; Zhao, Weiwei; Li, Jian; Jain, J K; Liu, Chaoxing; Moodera, Jagadeesh S; Chan, Moses H W

    2016-09-16

    Fundamental insight into the nature of the quantum phase transition from a superconductor to an insulator in two dimensions, or from one plateau to the next or to an insulator in the quantum Hall effect, has been revealed through the study of its scaling behavior. Here, we report on the experimental observation of a quantum phase transition from a quantum-anomalous-Hall insulator to an Anderson insulator in a magnetic topological insulator by tuning the chemical potential. Our experiment demonstrates the existence of scaling behavior from which we extract the critical exponent for this quantum phase transition. We expect that our work will motivate much further investigation of many properties of quantum phase transition in this new context.

  4. New chemical-DSMC method in numerical simulation of axisymmetric rarefied reactive flow

    NASA Astrophysics Data System (ADS)

    Zakeri, Ramin; Kamali Moghadam, Ramin; Mani, Mahmoud

    2017-04-01

    The modified quantum kinetic (MQK) chemical reaction model introduced by Zakeri et al. is developed for applicable cases in axisymmetric reactive rarefied gas flows using the direct simulation Monte Carlo (DSMC) method. Although, the MQK chemical model uses some modifications in the quantum kinetic (QK) method, it also employs the general soft sphere collision model and Stockmayer potential function to properly select the collision pairs in the DSMC algorithm and capture both the attraction and repulsion intermolecular forces in rarefied gas flows. For assessment of the presented model in the simulation of more complex and applicable reacting flows, first, the air dissociation is studied in a single cell for equilibrium and non-equilibrium conditions. The MQK results agree well with the analytical and experimental data and they accurately predict the characteristics of the rarefied flowfield with chemical reaction. To investigate accuracy of the MQK chemical model in the simulation of the axisymmetric flow, air dissociation is also assessed in an axial hypersonic flow around two geometries, the sphere as a benchmark case and the blunt body (STS-2) as an applicable test case. The computed results including the transient, rotational and vibrational temperatures, species concentration in the stagnation line, and also the heat flux and pressure coefficient on the surface are compared with those of the other chemical methods like the QK and total collision energy (TCE) models and available analytical and experimental data. Generally, the MQK chemical model properly simulates the chemical reactions and predicts flowfield characteristics more accurate rather than the typical QK model. Although in some cases, results of the MQK approaches match with those of the TCE method, the main point is that the MQK does not need any experimental data or unrealistic assumption of specular boundary condition as used in the TCE method. Another advantage of the MQK model is the

  5. Nuclear quantum effects and kinetic isotope effects in enzyme reactions.

    PubMed

    Vardi-Kilshtain, Alexandra; Nitoker, Neta; Major, Dan Thomas

    2015-09-15

    Enzymes are extraordinarily effective catalysts evolved to perform well-defined and highly specific chemical transformations. Studying the nature of rate enhancements and the mechanistic strategies in enzymes is very important, both from a basic scientific point of view, as well as in order to improve rational design of biomimetics. Kinetic isotope effect (KIE) is a very important tool in the study of chemical reactions and has been used extensively in the field of enzymology. Theoretically, the prediction of KIEs in condensed phase environments such as enzymes is challenging due to the need to include nuclear quantum effects (NQEs). Herein we describe recent progress in our group in the development of multi-scale simulation methods for the calculation of NQEs and accurate computation of KIEs. We also describe their application to several enzyme systems. In particular we describe the use of combined quantum mechanics/molecular mechanics (QM/MM) methods in classical and quantum simulations. The development of various novel path-integral methods is reviewed. These methods are tailor suited to enzyme systems, where only a few degrees of freedom involved in the chemistry need to be quantized. The application of the hybrid QM/MM quantum-classical simulation approach to three case studies is presented. The first case involves the proton transfer in alanine racemase. The second case presented involves orotidine 5'-monophosphate decarboxylase where multidimensional free energy simulations together with kinetic isotope effects are combined in the study of the reaction mechanism. Finally, we discuss the proton transfer in nitroalkane oxidase, where the enzyme employs tunneling as a catalytic fine-tuning tool. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. PRISM 3: expanded prediction of natural product chemical structures from microbial genomes.

    PubMed

    Skinnider, Michael A; Merwin, Nishanth J; Johnston, Chad W; Magarvey, Nathan A

    2017-07-03

    Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. Visualizing Chemical Bonds in Synthetic Molecules

    NASA Astrophysics Data System (ADS)

    Collins, Laura C.; Ruth, Anthony; Green, David B.; Janko, Boldizsar; Gomes, Kenjiro K.

    The use of synthetic quantum systems makes it possible to study phenomena that cannot be probed by conventional experiments. We created synthetic molecules using atomic manipulation and directly imaged the chemical bonds using tunneling spectroscopy. These synthetic systems allow us to probe the structure and electronic properties of chemical bonds in molecules, including those that would be unstable in nature, with unprecedented detail. The experimental images of electronic states in our synthetic molecules show a remarkable match to the charge distribution predicted by density functional theory calculations. The statistical analysis of the spectroscopy of these molecules can be adapted in the future to quantify aromaticity, which has been difficult to quantify universally thus far due to vague definitions. We can also study anti-aromatic molecules which are unstable naturally, to illuminate the electronic consequences of antiaromaticity.

  8. Karl Popper's Quantum Ghost

    NASA Astrophysics Data System (ADS)

    Shields, William

    2004-05-01

    Karl Popper, though not trained as a physicist and embarrassed early in his career by a physics error pointed out by Einstein and Bohr, ultimately made substantial contributions to the interpretation of quantum mechanics. As was often the case, Popper initially formulated his position by criticizing the views of others - in this case Niels Bohr and Werner Heisenberg. Underlying Popper's criticism was his belief that, first, the "standard interpretation" of quantum mechanics, sometimes called the Copenhagen interpretation, abandoned scientific realism and second, the assertion that quantum theory was "complete" (an assertion rejected by Einstein among others) amounted to an unfalsifiable claim. Popper insisted that the most basic predictions of quantum mechanics should continue to be tested, with an eye towards falsification rather than mere adding of decimal places to confirmatory experiments. His persistent attacks on the Copenhagen interpretation were aimed not at the uncertainty principle itself and the formalism from which it was derived, but at the acceptance by physicists of an unclear epistemology and ontology that left critical questions unanswered. In 1999, physicists at the University of Maryland conducted a version of Popper's Experiment, re-igniting the debate over quantum predictions and the role of locality in physics.

  9. Predictive spectroscopy and chemical imaging based on novel optical systems

    NASA Astrophysics Data System (ADS)

    Nelson, Matthew Paul

    1998-10-01

    This thesis describes two futuristic optical systems designed to surpass contemporary spectroscopic methods for predictive spectroscopy and chemical imaging. These systems are advantageous to current techniques in a number of ways including lower cost, enhanced portability, shorter analysis time, and improved S/N. First, a novel optical approach to predicting chemical and physical properties based on principal component analysis (PCA) is proposed and evaluated. A regression vector produced by PCA is designed into the structure of a set of paired optical filters. Light passing through the paired filters produces an analog detector signal directly proportional to the chemical/physical property for which the regression vector was designed. Second, a novel optical system is described which takes a single-shot approach to chemical imaging with high spectroscopic resolution using a dimension-reduction fiber-optic array. Images are focused onto a two- dimensional matrix of optical fibers which are drawn into a linear distal array with specific ordering. The distal end is imaged with a spectrograph equipped with an ICCD camera for spectral analysis. Software is used to extract the spatial/spectral information contained in the ICCD images and deconvolute them into wave length-specific reconstructed images or position-specific spectra which span a multi-wavelength space. This thesis includes a description of the fabrication of two dimension-reduction arrays as well as an evaluation of the system for spatial and spectral resolution, throughput, image brightness, resolving power, depth of focus, and channel cross-talk. PCA is performed on the images by treating rows of the ICCD images as spectra and plotting the scores of each PC as a function of reconstruction position. In addition, iterative target transformation factor analysis (ITTFA) is performed on the spectroscopic images to generate ``true'' chemical maps of samples. Univariate zero-order images, univariate first

  10. CURRENT STATE OF PREDICTING THE RESPIRATORY ALLERGY POTENTIAL OF CHEMICALS: WHAT ARE THE ISSUES?

    EPA Science Inventory

    Current State of Predicting the Respiratory Allergy Potential of Chemicals: What Are the Issues? M I. Gilmour1 and S. E. Loveless2, 1USEPA, Research Triangle Park, NC and 2DuPont Haskell Laboratory, Newark, DE.

    Many chemicals are clearly capable of eliciting immune respon...

  11. A quantum–quantum Metropolis algorithm

    PubMed Central

    Yung, Man-Hong; Aspuru-Guzik, Alán

    2012-01-01

    The classical Metropolis sampling method is a cornerstone of many statistical modeling applications that range from physics, chemistry, and biology to economics. This method is particularly suitable for sampling the thermal distributions of classical systems. The challenge of extending this method to the simulation of arbitrary quantum systems is that, in general, eigenstates of quantum Hamiltonians cannot be obtained efficiently with a classical computer. However, this challenge can be overcome by quantum computers. Here, we present a quantum algorithm which fully generalizes the classical Metropolis algorithm to the quantum domain. The meaning of quantum generalization is twofold: The proposed algorithm is not only applicable to both classical and quantum systems, but also offers a quantum speedup relative to the classical counterpart. Furthermore, unlike the classical method of quantum Monte Carlo, this quantum algorithm does not suffer from the negative-sign problem associated with fermionic systems. Applications of this algorithm include the study of low-temperature properties of quantum systems, such as the Hubbard model, and preparing the thermal states of sizable molecules to simulate, for example, chemical reactions at an arbitrary temperature. PMID:22215584

  12. Prediction of Quantum Anomalous Hall Insulator in half-fluorinated GaBi Honeycomb

    DOE PAGES

    Chen, Sung-Ping; Huang, Zhi-Quan; Crisostomo, Christian P.; ...

    2016-08-10

    Using first-principles electronic structure calculations, we predict half-fluorinated GaBi honeycomb under tensile strain to harbor a quantum anomalous Hall (QAH) insulator phase. We show that this QAH phase is driven by a single inversion in the band structure at the Γ point. Moreover, we have computed the electronic spectrum of a half-fluorinated GaBi nanoribbon with zigzag edges, which shows that only one edge band crosses the Fermi level within the band gap. In conclusion, our results suggest that half-fluorination of the GaBi honeycomb under tensile strain could provide a new platform for developing novel spintronics devices based on the QAHmore » effect.« less

  13. An Energy Balance Model to Predict Chemical Partitioning in a Photosynthetic Microbial Mat

    NASA Technical Reports Server (NTRS)

    Hoehler, Tori M.; Albert, Daniel B.; DesMarais, David J.

    2006-01-01

    Studies of biosignature formation in photosynthetic microbial mat communities offer potentially useful insights with regards to both solar and extrasolar astrobiology. Biosignature formation in such systems results from the chemical transformation of photosynthetically fixed carbon by accessory microorganisms. This fixed carbon represents a source not only of reducing power, but also energy, to these organisms, so that chemical and energy budgets should be coupled. We tested this hypothesis by applying an energy balance model to predict the fate of photosynthetic productivity under dark, anoxic conditions. Fermentation of photosynthetically fixed carbon is taken to be the only source of energy available to cyanobacteria in the absence of light and oxygen, and nitrogen fixation is the principal energy demand. The alternate fate for fixed carbon is to build cyanobacterial biomass with Redfield C:N ratio. The model predicts that, under completely nitrogen-limited conditions, growth is optimized when 78% of fixed carbon stores are directed into fermentative energy generation, with the remainder allocated to growth. These predictions were compared to measurements made on microbial mats that are known to be both nitrogen-limited and populated by actively nitrogen-fixing cyanobacteria. In these mats, under dark, anoxic conditions, 82% of fixed carbon stores were diverted into fermentation. The close agreement between these independent approaches suggests that energy balance models may provide a quantitative means of predicting chemical partitioning within such systems - an important step towards understanding how biological productivity is ultimately partitioned into biosignature compounds.

  14. Toward structural dynamics: protein motions viewed by chemical shift modulations and direct detection of C'N multiple-quantum relaxation.

    PubMed

    Mori, Mirko; Kateb, Fatiha; Bodenhausen, Geoffrey; Piccioli, Mario; Abergel, Daniel

    2010-03-17

    Multiple quantum relaxation in proteins reveals unexpected relationships between correlated or anti-correlated conformational backbone dynamics in alpha-helices or beta-sheets. The contributions of conformational exchange to the relaxation rates of C'N coherences (i.e., double- and zero-quantum coherences involving backbone carbonyl (13)C' and neighboring amide (15)N nuclei) depend on the kinetics of slow exchange processes, as well as on the populations of the conformations and chemical shift differences of (13)C' and (15)N nuclei. The relaxation rates of C'N coherences, which reflect concerted fluctuations due to slow chemical shift modulations (CSMs), were determined by direct (13)C detection in diamagnetic and paramagnetic proteins. In well-folded proteins such as lanthanide-substituted calbindin (CaLnCb), copper,zinc superoxide dismutase (Cu,Zn SOD), and matrix metalloproteinase (MMP12), slow conformational exchange occurs along the entire backbone. Our observations demonstrate that relaxation rates of C'N coherences arising from slow backbone dynamics have positive signs (characteristic of correlated fluctuations) in beta-sheets and negative signs (characteristic of anti-correlated fluctuations) in alpha-helices. This extends the prospects of structure-dynamics relationships to slow time scales that are relevant for protein function and enzymatic activity.

  15. Quantum chemical calculations of Cr2O3/SnO2 using density functional theory method

    NASA Astrophysics Data System (ADS)

    Jawaher, K. Rackesh; Indirajith, R.; Krishnan, S.; Robert, R.; Das, S. Jerome

    2018-03-01

    Quantum chemical calculations have been employed to study the molecular effects produced by Cr2O3/SnO2 optimised structure. The theoretical parameters of the transparent conducting metal oxides were calculated using DFT / B3LYP / LANL2DZ method. The optimised bond parameters such as bond lengths, bond angles and dihedral angles were calculated using the same theory. The non-linear optical property of the title compound was calculated using first-order hyperpolarisability calculation. The calculated HOMO-LUMO analysis explains the charge transfer interaction between the molecule. In addition, MEP and Mulliken atomic charges were also calculated and analysed.

  16. A Rat α-Fetoprotein Binding Activity Prediction Model to Facilitate Assessment of the Endocrine Disruption Potential of Environmental Chemicals.

    PubMed

    Hong, Huixiao; Shen, Jie; Ng, Hui Wen; Sakkiah, Sugunadevi; Ye, Hao; Ge, Weigong; Gong, Ping; Xiao, Wenming; Tong, Weida

    2016-03-25

    Endocrine disruptors such as polychlorinated biphenyls (PCBs), diethylstilbestrol (DES) and dichlorodiphenyltrichloroethane (DDT) are agents that interfere with the endocrine system and cause adverse health effects. Huge public health concern about endocrine disruptors has arisen. One of the mechanisms of endocrine disruption is through binding of endocrine disruptors with the hormone receptors in the target cells. Entrance of endocrine disruptors into target cells is the precondition of endocrine disruption. The binding capability of a chemical with proteins in the blood affects its entrance into the target cells and, thus, is very informative for the assessment of potential endocrine disruption of chemicals. α-fetoprotein is one of the major serum proteins that binds to a variety of chemicals such as estrogens. To better facilitate assessment of endocrine disruption of environmental chemicals, we developed a model for α-fetoprotein binding activity prediction using the novel pattern recognition method (Decision Forest) and the molecular descriptors calculated from two-dimensional structures by Mold² software. The predictive capability of the model has been evaluated through internal validation using 125 training chemicals (average balanced accuracy of 69%) and external validations using 22 chemicals (balanced accuracy of 71%). Prediction confidence analysis revealed the model performed much better at high prediction confidence. Our results indicate that the model is useful (when predictions are in high confidence) in endocrine disruption risk assessment of environmental chemicals though improvement by increasing number of training chemicals is needed.

  17. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    DOE PAGES

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; ...

    2015-06-04

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstratemore » prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.« less

  18. Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

    PubMed Central

    2015-01-01

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies. PMID:26113956

  19. Isolation, characterization, spectroscopic properties and quantum chemical computations of an important phytoalexin resveratrol as antioxidant component from Vitis labrusca L. and their chemical compositions.

    PubMed

    Güder, Aytaç; Korkmaz, Halil; Gökce, Halil; Alpaslan, Yelda Bingöl; Alpaslan, Gökhan

    2014-12-10

    In this study, isolation and characterization of trans-resveratrol (RES) as an antioxidant compound were carried out from VLE, VLG and VLS. Furthermore, antioxidant activities were evaluated by using six different methods. Finally, total phenolic, flavonoid, ascorbic acid, anthocyanin, lycopene, β-carotene and vitamin E contents were carried out. In addition, the FT-IR, (13)C and (1)H NMR chemical shifts and UV-vis. spectra of trans-resveratrol were experimentally recorded. Quantum chemical computations such as the molecular geometry, vibrational frequencies, UV-vis. spectroscopic parameters, HOMOs-LUMOs energies, molecular electrostatic potential (MEP), natural bond orbitals (NBO) and nonlinear optics (NLO) properties of title molecule have been calculated by using DFT/B3PW91 method with 6-311++G(d,p) basis set in ground state for the first time. The obtained results show that the calculated spectroscopic data are in a good agreement with experimental data. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. Prediction of the true digestible amino acid contents from the chemical composition of sorghum grain for poultry.

    PubMed

    Ebadi, M R; Sedghi, M; Golian, A; Ahmadi, H

    2011-10-01

    Accurate knowledge of true digestible amino acid (TDAA) contents of feedstuffs is necessary to accurately formulate poultry diets for profitable production. Several experimental approaches that are highly expensive and time consuming have been used to determine available amino acids. Prediction of the nutritive value of a feed ingredient from its chemical composition via regression methodology has been attempted for many years. The artificial neural network (ANN) model is a powerful method that may describe the relationship between digestible amino acid contents and chemical composition. Therefore, multiple linear regressions (MLR) and ANN models were developed for predicting the TDAA contents of sorghum grain based on chemical composition. A precision-fed assay trial using cecectomized roosters was performed to determine the TDAA contents in 48 sorghum samples from 12 sorghum varieties differing in chemical composition. The input variables for both MLR and ANN models were CP, ash, crude fiber, ether extract, and total phenols whereas the output variable was each individual TDAA for every sample. The results of this study revealed that it is possible to satisfactorily estimate the TDAA of sorghum grain through its chemical composition. The chemical composition of sorghum grain seems to highly influence the TDAA contents when considering components such as CP, crude fiber, ether extract, ash and total phenols. It is also possible to estimate the TDAA contents through multiple regression equations with reasonable accuracy depending on composition. However, a more satisfactory prediction may be achieved via ANN for all amino acids. The R(2) values for the ANN model corresponding to testing and training parameters showed a higher accuracy of prediction than equations established by the MLR method. In addition, the current data confirmed that chemical composition, often considered in total amino acid prediction, could be also a useful predictor of true digestible values

  1. 2D quantum gravity from quantum entanglement.

    PubMed

    Gliozzi, F

    2011-01-21

    In quantum systems with many degrees of freedom the replica method is a useful tool to study the entanglement of arbitrary spatial regions. We apply it in a way that allows them to backreact. As a consequence, they become dynamical subsystems whose position, form, and extension are determined by their interaction with the whole system. We analyze, in particular, quantum spin chains described at criticality by a conformal field theory. Its coupling to the Gibbs' ensemble of all possible subsystems is relevant and drives the system into a new fixed point which is argued to be that of the 2D quantum gravity coupled to this system. Numerical experiments on the critical Ising model show that the new critical exponents agree with those predicted by the formula of Knizhnik, Polyakov, and Zamolodchikov.

  2. Prediction of Hydrolysis Products of Organic Chemicals under Environmental pH Conditions

    EPA Science Inventory

    Cheminformatics-based software tools can predict the molecular structure of transformation products using a library of transformation reaction schemes. This paper presents the development of such a library for abiotic hydrolysis of organic chemicals under environmentally relevant...

  3. Predictive In Vitro Screening of Environmental Chemicals – The ToxCast Project

    EPA Science Inventory

    ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry and bioactivity profiling to predict potential for toxicity and prioritize limited testing resources (www.epa.gov/toc...

  4. Reliability of analog quantum simulation

    DOE PAGES

    Sarovar, Mohan; Zhang, Jun; Zeng, Lishan

    2017-01-03

    Analog quantum simulators (AQS) will likely be the first nontrivial application of quantum technology for predictive simulation. However, there remain questions regarding the degree of confidence that can be placed in the results of AQS since they do not naturally incorporate error correction. Specifically, how do we know whether an analog simulation of a quantum model will produce predictions that agree with the ideal model in the presence of inevitable imperfections? At the same time there is a widely held expectation that certain quantum simulation questions will be robust to errors and perturbations in the underlying hardware. Resolving these twomore » points of view is a critical step in making the most of this promising technology. In this paper we formalize the notion of AQS reliability by determining sensitivity of AQS outputs to underlying parameters, and formulate conditions for robust simulation. Our approach naturally reveals the importance of model symmetries in dictating the robust properties. Finally, to demonstrate the approach, we characterize the robust features of a variety of quantum many-body models.« less

  5. From Einstein-Podolsky-Rosen paradox to quantum nonlocality: experimental investigation of quantum correlations

    NASA Astrophysics Data System (ADS)

    Xu, Jin-Shi; Li, Chuan-Feng; Guo, Guang-Can

    2016-11-01

    In 1935, Einstein, Podolsky and Rosen published their influential paper proposing a now famous paradox (the EPR paradox) that threw doubt on the completeness of quantum mechanics. Two fundamental concepts: entanglement and steering, were given in the response to the EPR paper by Schrodinger, which both reflect the nonlocal nature of quantum mechanics. In 1964, John Bell obtained an experimentally testable inequality, in which its violation contradicts the prediction of local hidden variable models and agrees with that of quantum mechanics. Since then, great efforts have been made to experimentally investigate the nonlocal feature of quantum mechanics and many distinguished quantum properties were observed. In this work, along with the discussion of the development of quantum nonlocality, we would focus on our recent experimental efforts in investigating quantum correlations and their applications with optical systems, including the study of entanglement-assisted entropic uncertainty principle, Einstein-Podolsky-Rosen steering and the dynamics of quantum correlations.

  6. Photoisomerization in bacteriorhodopsin studied by FTIR, linear dichroism and photoselection experiments combined with quantum chemical theoretical analysis

    NASA Astrophysics Data System (ADS)

    Fahmy, K.; Siebert, F.; Großjean, M. F.; Tavan, P.

    1989-12-01

    Orientations of IR transition moments of the retinal chromophore of bacteriorhodopsin (BR) and of the apo-protein are investigated by FTIR linear dichroism and photoselection measurements. Low temperature difference spectra for the photoinduced transitions of BR to its photocycle intermediates K and L are evaluated using improved methods. Quantum chemical calculations of directions of IR and electronic transition moments of model chromophores are employed to analyze corresponding observations. The chromophore of light-adapted BR 568 is shown to exhibit small (15-30°) twists around the CC single bonds of retinals polyene chain but no large overall helicity (⩽15°). The average retinal plane is demonstrated to form an angle of 90±20° with the plane of the purple membrane. The C 9C 10 double bond of retinal is found approximately parallel to the plane of the membrane. Upon photoisomerization the orientation of the chromophore moiety from C 1 to C 13 is estimated to be largely conserved. The single bond twists of the chromophore in L are shown to be larger than those in BR 568. This result is in agreement with the previous prediction of increased single bond twists in L, which can cause a p K decrease of the chromophore and, thereby, enforce its deprotonation in the L→M transition [Schulten and Tavan, Nature, 272 (1978) 85].

  7. Quantum chemical modeling of new derivatives of (E,E)-azomethines: Synthesis, spectroscopic (FT-IR, UV/Vis, polarization) and thermophysical investigations

    NASA Astrophysics Data System (ADS)

    Shahab, Siyamak; Sheikhi, Masoome; Filippovich, Liudmila; Anatol'evich, Dikusar Evgenij; Yahyaei, Hooriye

    2017-06-01

    In the present work, the molecular structures of three new azomethine dyes: N-benzylidene-4-((E)-phenyldiazenyl)aniline (PAZB-1), 2-methoxy-4-(((4-((E)- phenyldiazenyl)phenyl)imino)methyl)phenol (PAZB-2) and 2-methoxy-5-((E)-((4-((E)- phenyldiazenyl)phenyl)imino)methyl)phenol (PAZB-8) have been predicted and investigated using Density Functional Theory (DFT) in dimethylformamide (DMF). The geometries of the azomethine dyes were optimized by PBE0/6-31 + G* level of theory. The electronic spectra of these azomethine dyes in a DMF solution was carried out by TDPBE0/6-31 + G* method. After quantum-chemical calculations three new azomethine dyes for optoelectronic applications were synthesized. FT-IR spectra of the title compounds are recorded and discussed. The computed absorption spectral data of the azomethine dyes are in good agreement with the experimental data, thus allowing an assignment of the UV/Vis spectra. On the basis of polyvinyl alcohol (PVA) and the new synthesized azomethine dyes polarizing films for Visible region of spectrum were developed. The main optical parameters of polarizing PVA-films (Transmittance, Polarization Efficiency and Dichroic Ratio) have been measured and discussed. Anisotropy of thermal conductivity of the PVA-films has been studied.

  8. Spectroscopic and quantum chemical perspectives on 2-amino 5-methylpyridinium 4-nitrobenzoate - An organic single crystals for optoelectronics device applications

    NASA Astrophysics Data System (ADS)

    Gandhimathi, A.; Karunakaran, R. T.; Kumaran, A. Elakkina; Prabahar, S.

    2018-07-01

    In this work, an optical quality single crystals of 2-amino 5-methylpyridinium 4-nitrobenzoate (2A5MPNB) were grown by slow evaporation solution growth technique using methanol as a solvent. The phases and functional groups of 2A5MPNB have been confirmed through powder X-ray diffraction and Fourier transform infrared (FTIR) studies, respectively. The optical transmittance window and the lower cut-off wavelength of the 2A5MPNB have been identified by UV-Vis-NIR studies. Dielectric and photoconductivity studies were also performed for the grown crystals. In order to analyze the mechanical strength Vickers hardness studies were taken for the grown crystal. The thermal behaviour was investigated by TG/DTA studies. NLO and laser damage properties were explored using Nd:YAG laser. Moreover, the quantum chemical calculations on 2A5MPNB have been performed by density functional theory (DFT) calculations using the B3LYP method with 6-311++G(d,p) basis set. The predicted first hyperpolarizability is found to be 14.45 times greater than that of urea and suggests that the title compound could be an attractive material for nonlinear optical applications.

  9. Experimental test of quantum nonlocality in three-photon Greenberger-Horne-Zeilinger entanglement

    PubMed

    Pan; Bouwmeester; Daniell; Weinfurter; Zeilinger

    2000-02-03

    Bell's theorem states that certain statistical correlations predicted by quantum physics for measurements on two-particle systems cannot be understood within a realistic picture based on local properties of each individual particle-even if the two particles are separated by large distances. Einstein, Podolsky and Rosen first recognized the fundamental significance of these quantum correlations (termed 'entanglement' by Schrodinger) and the two-particle quantum predictions have found ever-increasing experimental support. A more striking conflict between quantum mechanical and local realistic predictions (for perfect correlations) has been discovered; but experimental verification has been difficult, as it requires entanglement between at least three particles. Here we report experimental confirmation of this conflict, using our recently developed method to observe three-photon entanglement, or 'Greenberger-Horne-Zeilinger' (GHZ) states. The results of three specific experiments, involving measurements of polarization correlations between three photons, lead to predictions for a fourth experiment; quantum physical predictions are mutually contradictory with expectations based on local realism. We find the results of the fourth experiment to be in agreement with the quantum prediction and in striking conflict with local realism.

  10. Novel naïve Bayes classification models for predicting the chemical Ames mutagenicity.

    PubMed

    Zhang, Hui; Kang, Yan-Li; Zhu, Yuan-Yuan; Zhao, Kai-Xia; Liang, Jun-Yu; Ding, Lan; Zhang, Teng-Guo; Zhang, Ji

    2017-06-01

    Prediction of drug candidates for mutagenicity is a regulatory requirement since mutagenic compounds could pose a toxic risk to humans. The aim of this investigation was to develop a novel prediction model of mutagenicity by using a naïve Bayes classifier. The established model was validated by the internal 5-fold cross validation and external test sets. For comparison, the recursive partitioning classifier prediction model was also established and other various reported prediction models of mutagenicity were collected. Among these methods, the prediction performance of naïve Bayes classifier established here displayed very well and stable, which yielded average overall prediction accuracies for the internal 5-fold cross validation of the training set and external test set I set were 89.1±0.4% and 77.3±1.5%, respectively. The concordance of the external test set II with 446 marketed drugs was 90.9±0.3%. In addition, four simple molecular descriptors (e.g., Apol, No. of H donors, Num-Rings and Wiener) related to mutagenicity and five representative substructures of mutagens (e.g., aromatic nitro, hydroxyl amine, nitroso, aromatic amine and N-methyl-N-methylenemethanaminum) produced by ECFP_14 fingerprints were identified. We hope the established naïve Bayes prediction model can be applied to risk assessment processes; and the obtained important information of mutagenic chemicals can guide the design of chemical libraries for hit and lead optimization. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Chemically modulated graphene quantum dot for tuning the photoluminescence as novel sensory probe

    NASA Astrophysics Data System (ADS)

    Hwang, Eunhee; Hwang, Hee Min; Shin, Yonghun; Yoon, Yeoheung; Lee, Hanleem; Yang, Junghee; Bak, Sora; Lee, Hyoyoung

    2016-12-01

    A band gap tuning of environmental-friendly graphene quantum dot (GQD) becomes a keen interest for novel applications such as photoluminescence (PL) sensor. Here, for tuning the band gap of GQD, a hexafluorohydroxypropanyl benzene (HFHPB) group acted as a receptor of a chemical warfare agent was chemically attached on the GQD via the diazonium coupling reaction of HFHPB diazonium salt, providing new HFHPB-GQD material. With a help of the electron withdrawing HFHPB group, the energy band gap of the HFHPB-GQD was widened and its PL decay life time decreased. As designed, after addition of dimethyl methyl phosphonate (DMMP), the PL intensity of HFHPB-GQD sensor sharply increased up to approximately 200% through a hydrogen bond with DMMP. The fast response and short recovery time was proven by quartz crystal microbalance (QCM) analysis. This HFHPB-GQD sensor shows highly sensitive to DMMP in comparison with GQD sensor without HFHPB and graphene. In addition, the HFHPB-GQD sensor showed high selectivity only to the phosphonate functional group among many other analytes and also stable enough for real device applications. Thus, the tuning of the band gap of the photoluminescent GQDs may open up new promising strategies for the molecular detection of target substrates.

  12. Chemically modulated graphene quantum dot for tuning the photoluminescence as novel sensory probe

    PubMed Central

    Hwang, Eunhee; Hwang, Hee Min; Shin, Yonghun; Yoon, Yeoheung; Lee, Hanleem; Yang, Junghee; Bak, Sora; Lee, Hyoyoung

    2016-01-01

    A band gap tuning of environmental-friendly graphene quantum dot (GQD) becomes a keen interest for novel applications such as photoluminescence (PL) sensor. Here, for tuning the band gap of GQD, a hexafluorohydroxypropanyl benzene (HFHPB) group acted as a receptor of a chemical warfare agent was chemically attached on the GQD via the diazonium coupling reaction of HFHPB diazonium salt, providing new HFHPB-GQD material. With a help of the electron withdrawing HFHPB group, the energy band gap of the HFHPB-GQD was widened and its PL decay life time decreased. As designed, after addition of dimethyl methyl phosphonate (DMMP), the PL intensity of HFHPB-GQD sensor sharply increased up to approximately 200% through a hydrogen bond with DMMP. The fast response and short recovery time was proven by quartz crystal microbalance (QCM) analysis. This HFHPB-GQD sensor shows highly sensitive to DMMP in comparison with GQD sensor without HFHPB and graphene. In addition, the HFHPB-GQD sensor showed high selectivity only to the phosphonate functional group among many other analytes and also stable enough for real device applications. Thus, the tuning of the band gap of the photoluminescent GQDs may open up new promising strategies for the molecular detection of target substrates. PMID:27991584

  13. Synthesis, vibrational and quantum chemical investigations of hydrogen bonded complex betaine dihydrogen selenite

    NASA Astrophysics Data System (ADS)

    Arjunan, V.; Marchewka, Mariusz K.; Kalaivani, M.

    2012-10-01

    The molecular complex of betaine with selenious acid namely, betaine dihydrogen selenite (C5H13NO5Se, BDHSe) was synthesised by the reaction of betaine and SeO2 in a 1:1:1 solution of isopropanol, methanol and water. Crystals were grown from this solution by cooling to 253 K for few days. The complex was formed without accompanying proton transfer from selenious acid molecule to betaine. The complete vibrational assignments and analysis of BDHSe have been performed by FTIR, FT-Raman and far-infrared spectral studies. More support on the experimental findings was added from the quantum chemical studies performed with DFT (B3LYP) method using 6-311++G∗∗, 6-31G∗∗, cc-pVDZ and 3-21G basis sets. The structural parameters, energies, thermodynamic parameters and the NBO charges of BDHSe were determined by the DFT method. The 1H and 13C isotropic chemical shifts (δ ppm) of BDHSe with respect to TMS were also calculated using the gauge independent atomic orbital (GIAO) method and compared with the experimental data. SHG experiment was carried out using Kurtz-Perry powder technique. The efficiency of second harmonic generation for BDHSe was estimated relatively to KDP: deff = 0.97 deff (KDP).

  14. The quantum phase-transitions of water

    NASA Astrophysics Data System (ADS)

    Fillaux, François

    2017-08-01

    It is shown that hexagonal ices and steam are macroscopically quantum condensates, with continuous spacetime-translation symmetry, whereas liquid water is a quantum fluid with broken time-translation symmetry. Fusion and vaporization are quantum phase-transitions. The heat capacities, the latent heats, the phase-transition temperatures, the critical temperature, the molar volume expansion of ice relative to water, as well as neutron scattering data and dielectric measurements are explained. The phase-transition mechanisms along with the key role of quantum interferences and that of Hartley-Shannon's entropy are enlightened. The notions of chemical bond and force-field are questioned.

  15. Elucidating reaction mechanisms on quantum computers.

    PubMed

    Reiher, Markus; Wiebe, Nathan; Svore, Krysta M; Wecker, Dave; Troyer, Matthias

    2017-07-18

    With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources.

  16. Elucidating reaction mechanisms on quantum computers

    PubMed Central

    Reiher, Markus; Wiebe, Nathan; Svore, Krysta M.; Wecker, Dave; Troyer, Matthias

    2017-01-01

    With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources. PMID:28674011

  17. Elucidating reaction mechanisms on quantum computers

    NASA Astrophysics Data System (ADS)

    Reiher, Markus; Wiebe, Nathan; Svore, Krysta M.; Wecker, Dave; Troyer, Matthias

    2017-07-01

    With rapid recent advances in quantum technology, we are close to the threshold of quantum devices whose computational powers can exceed those of classical supercomputers. Here, we show that a quantum computer can be used to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical computer simulations used to probe these reaction mechanisms, to significantly increase their accuracy and enable hitherto intractable simulations. Our resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. Our results demonstrate that quantum computers will be able to tackle important problems in chemistry without requiring exorbitant resources.

  18. Elucidating Reaction Mechanisms on Quantum Computers

    NASA Astrophysics Data System (ADS)

    Wiebe, Nathan; Reiher, Markus; Svore, Krysta; Wecker, Dave; Troyer, Matthias

    We show how a quantum computer can be employed to elucidate reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. We discuss how quantum computers can augment classical-computer simulations for such problems, to significantly increase their accuracy and enable hitherto intractable simulations. Detailed resource estimates show that, even when taking into account the substantial overhead of quantum error correction, and the need to compile into discrete gate sets, the necessary computations can be performed in reasonable time on small quantum computers. This demonstrates that quantum computers will realistically be able to tackle important problems in chemistry that are both scientifically and economically significant.

  19. Prediction of the sorption capacities and affinities of organic chemicals by XAD-7.

    PubMed

    Yang, Kun; Qi, Long; Wei, Wei; Wu, Wenhao; Lin, Daohui

    2016-01-01

    Macro-porous resins are widely used as adsorbents for the treatment of organic contaminants in wastewater and for the pre-concentration of organic solutes from water. However, the sorption mechanisms for organic contaminants on such adsorbents have not been systematically investigated so far. Therefore, in this study, the sorption capacities and affinities of 24 organic chemicals by XAD-7 were investigated and the experimentally obtained sorption isotherms were fitted to the Dubinin-Ashtakhov model. Linear positive correlations were observed between the sorption capacities and the solubilities (SW) of the chemicals in water or octanol and between the sorption affinities and the solvatochromic parameters of the chemicals, indicating that the sorption of various organic compounds by XAD-7 occurred by non-linear partitioning into XAD-7, rather than by adsorption on XAD-7 surfaces. Both specific interactions (i.e., hydrogen-bonding interactions) as well as nonspecific interactions were considered to be responsible for the non-linear partitioning. The correlation equations obtained in this study allow the prediction of non-linear partitioning using well-known chemical parameters, namely SW, octanol-water partition coefficients (KOW), and the hydrogen-bonding donor parameter (αm). The effect of pH on the sorption of ionizable organic compounds (IOCs) could also be predicted by combining the correlation equations with additional equations developed from the estimation of IOC dissociation rates. The prediction equations developed in this study and the proposed non-linear partition mechanism shed new light on the selective removal and pre-concentration of organic solutes from water and on the regeneration of exhausted XAD-7 using solvent extraction.

  20. Semiempirical Quantum Chemical Calculations Accelerated on a Hybrid Multicore CPU-GPU Computing Platform.

    PubMed

    Wu, Xin; Koslowski, Axel; Thiel, Walter

    2012-07-10

    In this work, we demonstrate that semiempirical quantum chemical calculations can be accelerated significantly by leveraging the graphics processing unit (GPU) as a coprocessor on a hybrid multicore CPU-GPU computing platform. Semiempirical calculations using the MNDO, AM1, PM3, OM1, OM2, and OM3 model Hamiltonians were systematically profiled for three types of test systems (fullerenes, water clusters, and solvated crambin) to identify the most time-consuming sections of the code. The corresponding routines were ported to the GPU and optimized employing both existing library functions and a GPU kernel that carries out a sequence of noniterative Jacobi transformations during pseudodiagonalization. The overall computation times for single-point energy calculations and geometry optimizations of large molecules were reduced by one order of magnitude for all methods, as compared to runs on a single CPU core.

  1. Ab initio quantum chemical calculation of electron transfer matrix elements for large molecules

    NASA Astrophysics Data System (ADS)

    Zhang, Linda Yu; Friesner, Richard A.; Murphy, Robert B.

    1997-07-01

    Using a diabatic state formalism and pseudospectral numerical methods, we have developed an efficient ab initio quantum chemical approach to the calculation of electron transfer matrix elements for large molecules. The theory is developed at the Hartree-Fock level and validated by comparison with results in the literature for small systems. As an example of the power of the method, we calculate the electronic coupling between two bacteriochlorophyll molecules in various intermolecular geometries. Only a single self-consistent field (SCF) calculation on each of the monomers is needed to generate coupling matrix elements for all of the molecular pairs. The largest calculations performed, utilizing 1778 basis functions, required ˜14 h on an IBM 390 workstation. This is considerably less cpu time than would be necessitated with a supermolecule adiabatic state calculation and a conventional electronic structure code.

  2. Chemical genomic profiling via barcode sequencing to predict compound mode of action

    PubMed Central

    Piotrowski, Jeff S.; Simpkins, Scott W.; Li, Sheena C.; Deshpande, Raamesh; McIlwain, Sean; Ong, Irene; Myers, Chad L.; Boone, Charlie; Andersen, Raymond J.

    2015-01-01

    Summary Chemical genomics is an unbiased, whole-cell approach to characterizing novel compounds to determine mode of action and cellular target. Our version of this technique is built upon barcoded deletion mutants of Saccharomyces cerevisiae and has been adapted to a high-throughput methodology using next-generation sequencing. Here we describe the steps to generate a chemical genomic profile from a compound of interest, and how to use this information to predict molecular mechanism and targets of bioactive compounds. PMID:25618354

  3. Quantum speed limits in open system dynamics.

    PubMed

    del Campo, A; Egusquiza, I L; Plenio, M B; Huelga, S F

    2013-02-01

    Bounds to the speed of evolution of a quantum system are of fundamental interest in quantum metrology, quantum chemical dynamics, and quantum computation. We derive a time-energy uncertainty relation for open quantum systems undergoing a general, completely positive, and trace preserving evolution which provides a bound to the quantum speed limit. When the evolution is of the Lindblad form, the bound is analogous to the Mandelstam-Tamm relation which applies in the unitary case, with the role of the Hamiltonian being played by the adjoint of the generator of the dynamical semigroup. The utility of the new bound is exemplified in different scenarios, ranging from the estimation of the passage time to the determination of precision limits for quantum metrology in the presence of dephasing noise.

  4. Silicon Oxysulfide, OSiS: Rotational Spectrum, Quantum-Chemical Calculations, and Equilibrium Structure.

    PubMed

    Thorwirth, Sven; Mück, Leonie Anna; Gauss, Jürgen; Tamassia, Filippo; Lattanzi, Valerio; McCarthy, Michael C

    2011-06-02

    Silicon oxysulfide, OSiS, and seven of its minor isotopic species have been characterized for the first time in the gas phase at high spectral resolution by means of Fourier transform microwave spectroscopy. The equilibrium structure of OSiS has been determined from the experimental data using calculated vibration-rotation interaction constants. The structural parameters (rO-Si = 1.5064 Å and rSi-S = 1.9133 Å) are in very good agreement with values from high-level quantum chemical calculations using coupled-cluster techniques together with sophisticated additivity and extrapolation schemes. The bond distances in OSiS are very short in comparison with those in SiO and SiS. This unexpected finding is explained by the partial charges calculated for OSiS via a natural population analysis. The results suggest that electrostatic effects rather than multiple bonding are the key factors in determining bonding in this triatomic molecule. The data presented provide the spectroscopic information needed for radio astronomical searches for OSiS.

  5. Lifetime of a Chemically Bound Helium Compound

    NASA Technical Reports Server (NTRS)

    Chaban, Galina M.; Lundell, Jan; Gerber, R. Benny; Kwak, Dochan (Technical Monitor)

    2001-01-01

    The rare-gas atoms are chemically inert, to an extent unique among all elements. This is due to the stable electronic structure of the atoms. Stable molecules with chemically bound rare-gas atoms are, however, known. A first such compound, XePtF6, W2S prepared in 1962 and since then a range of molecules containing radon, xenon and krypton have been obtained. Most recently, a first stable chemically bound compound of argon was prepared, leaving neon and helium as the only elements for which stable chemically bound molecules are not yet known. Electronic structure calculations predict that a metastable species HHeF exists, but significance of the result depends on the unknown lifetime. Here we report quantum dynamics calculations of the lifetime of HHeF, using accurate interactions computed from electronic structure theory. HHeF is shown to disintegrate by tunneling through energy barriers into He + HF and H + He + F the first channel greatly dominating. The lifetime of HHeF is more than 120 picoseconds, that of DHeF is 14 nanoseconds. The relatively long lifetimes are encouraging for the preparation prospects of this first chemically bound helium compound.

  6. Machine learning of molecular electronic properties in chemical compound space

    NASA Astrophysics Data System (ADS)

    Montavon, Grégoire; Rupp, Matthias; Gobre, Vivekanand; Vazquez-Mayagoitia, Alvaro; Hansen, Katja; Tkatchenko, Alexandre; Müller, Klaus-Robert; Anatole von Lilienfeld, O.

    2013-09-01

    The combination of modern scientific computing with electronic structure theory can lead to an unprecedented amount of data amenable to intelligent data analysis for the identification of meaningful, novel and predictive structure-property relationships. Such relationships enable high-throughput screening for relevant properties in an exponentially growing pool of virtual compounds that are synthetically accessible. Here, we present a machine learning model, trained on a database of ab initio calculation results for thousands of organic molecules, that simultaneously predicts multiple electronic ground- and excited-state properties. The properties include atomization energy, polarizability, frontier orbital eigenvalues, ionization potential, electron affinity and excitation energies. The machine learning model is based on a deep multi-task artificial neural network, exploiting the underlying correlations between various molecular properties. The input is identical to ab initio methods, i.e. nuclear charges and Cartesian coordinates of all atoms. For small organic molecules, the accuracy of such a ‘quantum machine’ is similar, and sometimes superior, to modern quantum-chemical methods—at negligible computational cost.

  7. Molecular structure, vibrational analysis (IR and Raman) and quantum chemical investigations of 1-aminoisoquinoline

    NASA Astrophysics Data System (ADS)

    Sivaprakash, S.; Prakash, S.; Mohan, S.; Jose, Sujin P.

    2017-12-01

    Quantum chemical calculations of energy and geometrical parameters of 1-aminoisoquinoline [1-AIQ] were carried out by using DFT/B3LYP method using 6-311G (d,p), 6-311G++(d,p) and cc-pVTZ basis sets. The vibrational wavenumbers were computed for the energetically most stable, optimized geometry. The vibrational assignments were performed on the basis of potential energy distribution (PED) using VEDA program. The NBO analysis was done to investigate the intra molecular charge transfer of the molecule. The frontier molecular orbital (FMO) analysis was carried out and the chemical reactivity descriptors of the molecule were studied. The Mulliken charge analysis, molecular electrostatic potential (MEP), HOMO-LUMO energy gap and the related properties were also investigated at B3LYP level. The absorption spectrum of the molecule was studied from UV-Visible analysis by using time-dependent density functional theory (TD-DFT). Fourier Transform Infrared spectrum (FT-IR) and Raman spectrum of 1-AIQ compound were analyzed and recorded in the range 4000-400 cm-1 and 3500-100 cm-1 respectively. The experimentally determined wavenumbers were compared with those calculated theoretically and they complement each other.

  8. PREDICTION OF CHEMICAL RESIDUES IN AQUATIC ORGANISMS FOR A FIELD DISCHARGE SITUATION.

    EPA Science Inventory

    A field study was performed which compared predicted and measured concentrations of chemicals in receiving water organisms from three sampling locations on Five Mile Creek, Birmingham, Al. Two point source discharges, both from coke manufacturing facilities, were included in the ...

  9. Nontrivial Quantum Effects in Biology: A Skeptical Physicists' View

    NASA Astrophysics Data System (ADS)

    Wiseman, Howard; Eisert, Jens

    The following sections are included: * Introduction * A Quantum Life Principle * A quantum chemistry principle? * The anthropic principle * Quantum Computing in the Brain * Nature did everything first? * Decoherence as the make or break issue * Quantum error correction * Uselessness of quantum algorithms for organisms * Quantum Computing in Genetics * Quantum search * Teleological aspects and the fast-track to life * Quantum Consciousness * Computability and free will * Time scales * Quantum Free Will * Predictability and free will * Determinism and free will * Acknowledgements * References

  10. Implementation of generalized quantum measurements: Superadditive quantum coding, accessible information extraction, and classical capacity limit

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Takeoka, Masahiro; Fujiwara, Mikio; Mizuno, Jun

    2004-05-01

    Quantum-information theory predicts that when the transmission resource is doubled in quantum channels, the amount of information transmitted can be increased more than twice by quantum-channel coding technique, whereas the increase is at most twice in classical information theory. This remarkable feature, the superadditive quantum-coding gain, can be implemented by appropriate choices of code words and corresponding quantum decoding which requires a collective quantum measurement. Recently, an experimental demonstration was reported [M. Fujiwara et al., Phys. Rev. Lett. 90, 167906 (2003)]. The purpose of this paper is to describe our experiment in detail. Particularly, a design strategy of quantum-collective decodingmore » in physical quantum circuits is emphasized. We also address the practical implication of the gain on communication performance by introducing the quantum-classical hybrid coding scheme. We show how the superadditive quantum-coding gain, even in a small code length, can boost the communication performance of conventional coding techniques.« less

  11. Experimental metaphysics2 : The double standard in the quantum-information approach to the foundations of quantum theory

    NASA Astrophysics Data System (ADS)

    Hagar, Amit

    Among the alternatives of non-relativistic quantum mechanics (NRQM) there are those that give different predictions than quantum mechanics in yet-untested circumstances, while remaining compatible with current empirical findings. In order to test these predictions, one must isolate one's system from environmental induced decoherence, which, on the standard view of NRQM, is the dynamical mechanism that is responsible for the 'apparent' collapse in open quantum systems. But while recent advances in condensed-matter physics may lead in the near future to experimental setups that will allow one to test the two hypotheses, namely genuine collapse vs. decoherence, hence make progress toward a solution to the quantum measurement problem, those philosophers and physicists who are advocating an information-theoretic approach to the foundations of quantum mechanics are still unwilling to acknowledge the empirical character of the issue at stake. Here I argue that in doing so they are displaying an unwarranted double standard.

  12. On the bathochromic shift of the absorption by astaxanthin in crustacyanin: a quantum chemical study

    NASA Astrophysics Data System (ADS)

    Durbeej, Bo; Eriksson, Leif A.

    2003-06-01

    The structural origin of the bathochromic shift assumed by the electronic absorption spectrum of protein-bound astaxanthin, the carotenoid that upon binding to crustacyanin is responsible for the blue colouration of lobster shell, is investigated by means of quantum chemical methods. The calculations suggest that the bathochromic shift is largely due to one of the astaxanthin C4 keto groups being hydrogen-bonded to a histidine residue of the surrounding protein, and that the effect of this histidine is directly dependent on its protonation state. Out of the different methodologies (CIS, TD-DFT, and ZINDO/S) employed to calculate wavelengths of maximum absorption, the best agreement with experimental data is obtained using the semiempirical ZINDO/S method.

  13. Low Temperature Synthesis of CdSe Quantum Dots with Amine Derivative and Their Chemical Kinetics

    NASA Astrophysics Data System (ADS)

    Seongmi Hwang,; Youngmin Choi,; Sunho Jeong,; Hakyun Jung,; Chang Gyoun Kim,; Teak-Mo Chung,; Beyong-Hwan Ryu,

    2010-05-01

    The chemical kinetics of growing CdSe nanocrystals was studied in order to investigate the effects of amine capping agents on the size of resulting quantum dots (QDs). CdSe QDs were prepared in phenyl ether, and the amine ligand dependence of QD size was determined. The results show that the size of CdSe nanocrystals can be regulated by controlling reaction rate, with smaller QDs being formed in slower processes. The results of photoluminescence (PL) studies show that the emission wavelengths of the QDs well correlate with particle size. This simple process for forming different-sized QDs, which uses a cheap solvent and various capping agents, has the potential for preparing CdSe nanocrystals more economically.

  14. Occam's Quantum Strop: Synchronizing and Compressing Classical Cryptic Processes via a Quantum Channel.

    PubMed

    Mahoney, John R; Aghamohammadi, Cina; Crutchfield, James P

    2016-02-15

    A stochastic process' statistical complexity stands out as a fundamental property: the minimum information required to synchronize one process generator to another. How much information is required, though, when synchronizing over a quantum channel? Recent work demonstrated that representing causal similarity as quantum state-indistinguishability provides a quantum advantage. We generalize this to synchronization and offer a sequence of constructions that exploit extended causal structures, finding substantial increase of the quantum advantage. We demonstrate that maximum compression is determined by the process' cryptic order--a classical, topological property closely allied to Markov order, itself a measure of historical dependence. We introduce an efficient algorithm that computes the quantum advantage and close noting that the advantage comes at a cost-one trades off prediction for generation complexity.

  15. A study of the relationship between the chemical structures and the fluorescence quantum yields of coumarins, quinoxalinones and benzoxazinones for the development of sensitive fluorescent derivatization reagents.

    PubMed

    Azuma, Kentaro; Suzuki, Sachiko; Uchiyama, Seiichi; Kajiro, Toshi; Santa, Tomofumi; Imai, Kazuhiro

    2003-04-01

    To develop new fluorescent derivatization reagents, we investigated the relationship between the chemical structures and the fluorescence quantum yields (phi(f)) of coumarins, quinoxalinones and benzoxadinones. Forty-six compounds were synthesized and their fluorescence spectra were measured in n-hexane, ethyl acetate, methanol and water. The energy levels of these compounds were calculated by combination of the semi-empirical AM1 and INDO/S (CI = all) methods. The deltaE(Tn(n,pi*), S1(pi,pi*)) (the energy gap between the Tn(n,pi*) and S1(pi,pi*) states) values were well correlated with the phi(f) values, which enables us to predict the phi(f) values from their chemical structures. Based on this relationship, 3-phenyl-7-N-piperazinoquinoxalin-2(1H)-one (PQ-Pz) and 7-(3-(S)-aminopyrrolidin-1-yl)-3-phenylquinoxalin-2-(1H)-one (PQ-APy) were developed as fluorescent derivatization reagents for carboxylic acids. The derivatives of the carboxylic acids with PQ-Pz and PQ-APy showed large phi(f) values even in polar solvents, suggesting that these reagents are suitable for the microanalysis of biologically important carboxylic acids by reversed phase HPLC.

  16. Mixed quantum-classical studies of energy partitioning in unimolecular chemical reactions

    NASA Astrophysics Data System (ADS)

    Bladow, Landon Lowell

    A mixed quantum-classical reaction path Hamiltonian method is utilized to study the dynamics of unimolecular reactions. The method treats motion along the reaction path classically and treats the transverse vibrations quantum mechanically. The theory leads to equations that predict the disposai of the exit-channel potential energy to product translation and vibration. In addition, vibrational state distributions are obtained for the product normal modes. Vibrational excitation results from the curvature of the minimum energy reaction path. The method is applied to six unimolecular reactions: HF elimination from fluoroethane, 1,1-difluoroethane, 1,1-difluoroethene, and trifluoromethane; and HCl elimination from chloroethane and acetyl chloride. The minimum energy paths were calculated at either the MP2 or B3LYP level of theory. In all cases, the majority of the vibrational excitation of the products occurs in the HX fragment. The results are compared to experimental data and other theoretical results, where available. The best agreement between the experimental and calculated HX vibrational distributions is found for the halogenated ethanes, and the experimental deduction that the majority of the HX vibrational excitation arises from the potential energy release is supported. It is believed that the excess energy provided in experiments contributes to the poorer agreement between experiment and theory observed for HF elimination from 1,1-difluoroethene and trifluoromethane. An attempt is described to incorporate a treatment of the excess energy into the present method. However, the sign of the curvature coupling elements is then found to affect the dynamics. Overall, the method appears to be an efficient dynamical tool for modeling the disposal of the exit-channel potential energy in unimolecular reactions.

  17. The Interplay of Quantum Confinement and Hydrogenation in Amorphous Silicon Quantum Dots.

    PubMed

    Askari, Sadegh; Svrcek, Vladmir; Maguire, Paul; Mariotti, Davide

    2015-12-22

    Hydrogenation in amorphous silicon quantum dots (QDs) has a dramatic impact on the corresponding optical properties and band energy structure, leading to a quantum-confined composite material with unique characteristics. The synthesis of a-Si:H QDs is demonstrated with an atmospheric-pressure plasma process, which allows for accurate control of a highly chemically reactive non-equilibrium environment with temperatures well below the crystallization temperature of Si QDs. © 2015 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Some new reaction pathways for the formation of cytosine in interstellar space - A quantum chemical study

    NASA Astrophysics Data System (ADS)

    Gupta, V. P.; Tandon, Poonam; Mishra, Priti

    2013-03-01

    The detection of nucleic acid bases in carbonaceous meteorites suggests that their formation and survival is possible outside of the Earth. Small N-heterocycles, including pyrimidine, purines and nucleobases, have been extensively sought in the interstellar medium. It has been suggested theoretically that reactions between some interstellar molecules may lead to the formation of cytosine, uracil and thymine though these processes involve significantly high potential barriers. We attempted therefore to use quantum chemical techniques to explore if cytosine can possibly form in the interstellar space by radical-radical and radical-molecule interaction schemes, both in the gas phase and in the grains, through barrier-less or low barrier pathways. Results of DFT calculations for the formation of cytosine starting from some of the simple molecules and radicals detected in the interstellar space are being reported. Global and local descriptors such as molecular hardness, softness and electrophilicity, and condensed Fukui functions and local philicity indices were used to understand the mechanistic aspects of chemical reaction. The presence and nature of weak bonds in the molecules and transition states formed during the reaction process have been ascertained using Bader's quantum theory of atoms in molecules (QTAIMs). Two exothermic reaction pathways starting from propynylidyne (CCCH) and cyanoacetylene (HCCCN), respectively, have been identified. While the first reaction path is found to be totally exothermic, it involves a barrier of 12.5 kcal/mol in the gas phase against the lowest value of about 32 kcal/mol reported in the literature. The second path is both exothermic and barrier-less. The later has, therefore, a greater probability of occurrence in the cold interstellar clouds (10-50 K).

  19. Holographic description of a quantum black hole on a computer

    NASA Astrophysics Data System (ADS)

    Hanada, Masanori; Hyakutake, Yoshifumi; Ishiki, Goro; Nishimura, Jun

    2014-05-01

    Black holes have been predicted to radiate particles and eventually evaporate, which has led to the information loss paradox and implies that the fundamental laws of quantum mechanics may be violated. Superstring theory, a consistent theory of quantum gravity, provides a possible solution to the paradox if evaporating black holes can actually be described in terms of standard quantum mechanical systems, as conjectured from the theory. Here, we test this conjecture by calculating the mass of a black hole in the corresponding quantum mechanical system numerically. Our results agree well with the prediction from gravity theory, including the leading quantum gravity correction. Our ability to simulate black holes offers the potential to further explore the yet mysterious nature of quantum gravity through well-established quantum mechanics.

  20. Quantum and classical noise in practical quantum-cryptography systems based on polarization-entangled photons

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Castelletto, S.; Degiovanni, I.P.; Rastello, M.L.

    2003-02-01

    Quantum-cryptography key distribution (QCKD) experiments have been recently reported using polarization-entangled photons. However, in any practical realization, quantum systems suffer from either unwanted or induced interactions with the environment and the quantum measurement system, showing up as quantum and, ultimately, statistical noise. In this paper, we investigate how an ideal polarization entanglement in spontaneous parametric down-conversion (SPDC) suffers quantum noise in its practical implementation as a secure quantum system, yielding errors in the transmitted bit sequence. Since all SPDC-based QCKD schemes rely on the measurement of coincidence to assert the bit transmission between the two parties, we bundle up themore » overall quantum and statistical noise in an exhaustive model to calculate the accidental coincidences. This model predicts the quantum-bit error rate and the sifted key and allows comparisons between different security criteria of the hitherto proposed QCKD protocols, resulting in an objective assessment of performances and advantages of different systems.« less

  1. Simulated quantum computation of molecular energies.

    PubMed

    Aspuru-Guzik, Alán; Dutoi, Anthony D; Love, Peter J; Head-Gordon, Martin

    2005-09-09

    The calculation time for the energy of atoms and molecules scales exponentially with system size on a classical computer but polynomially using quantum algorithms. We demonstrate that such algorithms can be applied to problems of chemical interest using modest numbers of quantum bits. Calculations of the water and lithium hydride molecular ground-state energies have been carried out on a quantum computer simulator using a recursive phase-estimation algorithm. The recursive algorithm reduces the number of quantum bits required for the readout register from about 20 to 4. Mappings of the molecular wave function to the quantum bits are described. An adiabatic method for the preparation of a good approximate ground-state wave function is described and demonstrated for a stretched hydrogen molecule. The number of quantum bits required scales linearly with the number of basis functions, and the number of gates required grows polynomially with the number of quantum bits.

  2. Some Phthalocyanine and Naphthalocyanine Derivatives as Corrosion Inhibitors for Aluminium in Acidic Medium: Experimental, Quantum Chemical Calculations, QSAR Studies and Synergistic Effect of Iodide Ions.

    PubMed

    Dibetsoe, Masego; Olasunkanmi, Lukman O; Fayemi, Omolola E; Yesudass, Sasikumar; Ramaganthan, Baskar; Bahadur, Indra; Adekunle, Abolanle S; Kabanda, Mwadham M; Ebenso, Eno E

    2015-08-28

    The effects of seven macrocyclic compounds comprising four phthalocyanines (Pcs) namely 1,4,8,11,15,18,22,25-octabutoxy-29H,31H-phthalocyanine (Pc1), 2,3,9,10,16,17,23,24-octakis(octyloxy)-29H,31H-phthalocyanine (Pc2), 2,9,16,23-tetra-tert-butyl-29H,31H-phthalocyanine (Pc3) and 29H,31H-phthalocyanine (Pc4), and three naphthalocyanines namely 5,9,14,18,23,27,32,36-octabutoxy-2,3-naphthalocyanine (nPc1), 2,11,20,29-tetra-tert-butyl-2,3-naphthalocyanine (nPc2) and 2,3-naphthalocyanine (nP3) were investigated on the corrosion of aluminium (Al) in 1 M HCl using a gravimetric method, potentiodynamic polarization technique, quantum chemical calculations and quantitative structure activity relationship (QSAR). Synergistic effects of KI on the corrosion inhibition properties of the compounds were also investigated. All the studied compounds showed appreciable inhibition efficiencies, which decrease with increasing temperature from 30 °C to 70 °C. At each concentration of the inhibitor, addition of 0.1% KI increased the inhibition efficiency compared to the absence of KI indicating the occurrence of synergistic interactions between the studied molecules and I(-) ions. From the potentiodynamic polarization studies, the studied Pcs and nPcs are mixed type corrosion inhibitors both without and with addition of KI. The adsorption of the studied molecules on Al surface obeys the Langmuir adsorption isotherm, while the thermodynamic and kinetic parameters revealed that the adsorption of the studied compounds on Al surface is spontaneous and involves competitive physisorption and chemisorption mechanisms. The experimental results revealed the aggregated interactions between the inhibitor molecules and the results further indicated that the peripheral groups on the compounds affect these interactions. The calculated quantum chemical parameters and the QSAR results revealed the possibility of strong interactions between the studied inhibitors and metal surface. QSAR analysis on the

  3. Ferritin-Templated Quantum-Dots for Quantum Logic Gates

    NASA Technical Reports Server (NTRS)

    Choi, Sang H.; Kim, Jae-Woo; Chu, Sang-Hyon; Park, Yeonjoon; King, Glen C.; Lillehei, Peter T.; Kim, Seon-Jeong; Elliott, James R.

    2005-01-01

    Quantum logic gates (QLGs) or other logic systems are based on quantum-dots (QD) with a stringent requirement of size uniformity. The QD are widely known building units for QLGs. The size control of QD is a critical issue in quantum-dot fabrication. The work presented here offers a new method to develop quantum-dots using a bio-template, called ferritin, that ensures QD production in uniform size of nano-scale proportion. The bio-template for uniform yield of QD is based on a ferritin protein that allows reconstitution of core material through the reduction and chelation processes. One of the biggest challenges for developing QLG is the requirement of ordered and uniform size of QD for arrays on a substrate with nanometer precision. The QD development by bio-template includes the electrochemical/chemical reconsitution of ferritins with different core materials, such as iron, cobalt, manganese, platinum, and nickel. The other bio-template method used in our laboratory is dendrimers, precisely defined chemical structures. With ferritin-templated QD, we fabricated the heptagonshaped patterned array via direct nano manipulation of the ferritin molecules with a tip of atomic force microscope (AFM). We also designed various nanofabrication methods of QD arrays using a wide range manipulation techniques. The precise control of the ferritin-templated QD for a patterned arrangement are offered by various methods, such as a site-specific immobilization of thiolated ferritins through local oxidation using the AFM tip, ferritin arrays induced by gold nanoparticle manipulation, thiolated ferritin positioning by shaving method, etc. In the signal measurements, the current-voltage curve is obtained by measuring the current through the ferritin, between the tip and the substrate for potential sweeping or at constant potential. The measured resistance near zero bias was 1.8 teraohm for single holoferritin and 5.7 teraohm for single apoferritin, respectively.

  4. Quantum dot nanoparticle conjugation, characterization, and applications in neuroscience

    NASA Astrophysics Data System (ADS)

    Pathak, Smita

    Quantum dot are semiconducting nanoparticles that have been used for decades in a variety of applications such as solar cells, LEDs and medical imaging. Their use in the last area, however, has been extremely limited despite their potential as revolutionary new biological labeling tools. Quantum dots are much brighter and more stable than conventional fluorophores, making them optimal for high resolution imaging and long term studies. Prior work in this area involves synthesizing and chemically conjugating quantum dots to molecules of interest in-house. However this method is both time consuming and prone to human error. Additionally, non-specific binding and nanoparticle aggregation currently prevent researchers from utilizing this system to its fullest capacity. Another critical issue that has not been addressed is determining the number of ligands bound to nanoparticles, which is crucial for proper interpretation of results. In this work, methods to label fixed cells using two types of chemically modified quantum dots are studied. Reproducible non-specific artifact labeling is consistently demonstrated if antibody-quantum dot conditions are less than optimal. In order to explain this, antibodies bound to quantum dots were characterized and quantified. While other groups have qualitatively characterized antibody functionalized quantum dots using TEM, AFM, UV spectroscopy and gel electrophoresis, and in some cases have reported calculated estimates of the putative number of total antibodies bound to quantum dots, no quantitative experimental results had been reported prior to this work. The chemical functionalization and characterization of quantum dot nanocrystals achieved in this work elucidates binding mechanisms of ligands to nanoparticles and allows researchers to not only translate our tools to studies in their own areas of interest but also derive quantitative results from these studies. This research brings ease of use and increased reliability to

  5. Assessment of quantitative structure-activity relationship of toxicity prediction models for Korean chemical substance control legislation

    PubMed Central

    Kim, Kwang-Yon; Shin, Seong Eun; No, Kyoung Tai

    2015-01-01

    Objectives For successful adoption of legislation controlling registration and assessment of chemical substances, it is important to obtain sufficient toxicological experimental evidence and other related information. It is also essential to obtain a sufficient number of predicted risk and toxicity results. Particularly, methods used in predicting toxicities of chemical substances during acquisition of required data, ultimately become an economic method for future dealings with new substances. Although the need for such methods is gradually increasing, the-required information about reliability and applicability range has not been systematically provided. Methods There are various representative environmental and human toxicity models based on quantitative structure-activity relationships (QSAR). Here, we secured the 10 representative QSAR-based prediction models and its information that can make predictions about substances that are expected to be regulated. We used models that predict and confirm usability of the information expected to be collected and submitted according to the legislation. After collecting and evaluating each predictive model and relevant data, we prepared methods quantifying the scientific validity and reliability, which are essential conditions for using predictive models. Results We calculated predicted values for the models. Furthermore, we deduced and compared adequacies of the models using the Alternative non-testing method assessed for Registration, Evaluation, Authorization, and Restriction of Chemicals Substances scoring system, and deduced the applicability domains for each model. Additionally, we calculated and compared inclusion rates of substances expected to be regulated, to confirm the applicability. Conclusions We evaluated and compared the data, adequacy, and applicability of our selected QSAR-based toxicity prediction models, and included them in a database. Based on this data, we aimed to construct a system that can be used

  6. A perspective on quantum mechanics calculations in ADMET predictions.

    PubMed

    Bowen, J Phillip; Güner, Osman F

    2013-01-01

    Understanding the molecular basis of drug action has been an important objective for pharmaceutical scientists. With the increasing speed of computers and the implementation of quantum chemistry methodologies, pharmacodynamic and pharmacokinetic problems have become more computationally tractable. Historically the former has been the focus of drug design, but within the last two decades efforts to understand the latter have increased. It takes about fifteen years and over $1 billion dollars for a drug to go from laboratory hit, through lead optimization, to final approval by the U.S. Food and Drug Administration. While the costs have increased substantially, the overall clinical success rate for a compound to emerge from clinical trials is approximately 10%. Most of the attrition rate can be traced to ADMET (absorption, distribution, metabolism, excretion, and toxicity) problems, which is a powerful impetus to study these issues at an earlier stage in drug discovery. Quantum mechanics offers pharmaceutical scientists the opportunity to investigate pharmacokinetic problems at the molecular level prior to laboratory preparation and testing. This review will provide a perspective on the use of quantum mechanics or a combination of quantum mechanics coupled with other classical methods in the pharmacokinetic phase of drug discovery. A brief overview of the essential features of theory will be discussed, and a few carefully selected examples will be given to highlight the computational methods.

  7. On Macroscopic Quantum Phenomena in Biomolecules and Cells: From Levinthal to Hopfield

    PubMed Central

    Raković, Dejan; Dugić, Miroljub; Jeknić-Dugić, Jasmina; Plavšić, Milenko; Jaćimovski, Stevo; Šetrajčić, Jovan

    2014-01-01

    In the context of the macroscopic quantum phenomena of the second kind, we hereby seek for a solution-in-principle of the long standing problem of the polymer folding, which was considered by Levinthal as (semi)classically intractable. To illuminate it, we applied quantum-chemical and quantum decoherence approaches to conformational transitions. Our analyses imply the existence of novel macroscopic quantum biomolecular phenomena, with biomolecular chain folding in an open environment considered as a subtle interplay between energy and conformation eigenstates of this biomolecule, governed by quantum-chemical and quantum decoherence laws. On the other hand, within an open biological cell, a system of all identical (noninteracting and dynamically noncoupled) biomolecular proteins might be considered as corresponding spatial quantum ensemble of these identical biomolecular processors, providing spatially distributed quantum solution to a single corresponding biomolecular chain folding, whose density of conformational states might be represented as Hopfield-like quantum-holographic associative neural network too (providing an equivalent global quantum-informational alternative to standard molecular-biology local biochemical approach in biomolecules and cells and higher hierarchical levels of organism, as well). PMID:25028662

  8. Quantum plasmonics: optical properties of a nanomatryushka.

    PubMed

    Kulkarni, Vikram; Prodan, Emil; Nordlander, Peter

    2013-01-01

    Quantum mechanical effects can significantly reduce the plasmon-induced field enhancements around nanoparticles. Here we present a quantum mechanical investigation of the plasmon resonances in a nanomatryushka, which is a concentric core-shell nanoparticle consisting of a solid metallic core encapsulated in a thin metallic shell. We compute the optical response using the time-dependent density functional theory and compare the results with predictions based on the classical electromagnetic theory. We find strong quantum mechanical effects for core-shell spacings below 5 Å, a regime where both the absorption cross section and the local field enhancements differ significantly from the classical predictions. We also show that the workfunction of the metal is a crucial parameter determining the onset and magnitude of quantum effects. For metals with lower workfunctions such as aluminum, the quantum effects are found to be significantly more pronounced than for a noble metal such as gold.

  9. Topological Quantum Entanglement

    DTIC Science & Technology

    2014-02-19

    quantum Hall (FQH) state – the most likely FQH state to host such quasiparticles – is the so-called even-odd effect predicted for quantum interference...interferometer, in which case the oscillations result from the interference of (fractionalized) edge quasiparticles taking two possible paths, or the...even and odd numbers of charge e/4 quasiparticles enclosed within the loop as a function of side gate voltage, which is a clear signature of a non

  10. Conformational analysis, spectroscopic, structure-activity relations and quantum chemical simulation studies of 4-(trifluoromethyl)benzylamine

    NASA Astrophysics Data System (ADS)

    Arjunan, V.; Devi, L.; Mohan, S.

    2018-05-01

    The FT-IR and FT-Raman spectra of 4-trifluoromethylbenzylamine (TFMBA) have been recorded in the range 4000-450 and 4000-100 cm-1 respectively. The conformational analysis of the compound has been carried out to attain stable geometry of the compound. The complete vibrational assignment and analysis of the fundamental modes of the compound are carried out using the experimental FTIR and FT-Raman data and quantum chemical studies. The experimental vibrational frequencies are compared with the wavenumbers obtained theoretically from the B3LYP gradient calculations employing the standard high level 6-311++G** and cc-pVTZ basis sets for the optimised geometry of the compound. The structural parameters, thermodynamic properties and vibrational frequencies of the normal modes obtained from the B3LYP methods are in good agreement with the experimental data. The 1H (400 MHz; CDCl3) and 13C (100 MHz; CDCl3) nuclear magnetic resonance (NMR) spectra were also recorded. The electronic properties, highest occupied molecular orbital and lowest unoccupied molecular orbital energies are measured by DFT approach. The charges of the atoms by natural bond orbital (NBO) analysis are determined by B3LYP/cc-pVTZ method. The structure-chemical reactivity relations of the compound are determined through chemical potential, global hardness, global softness, electronegativity, electrophilicity and local reactivity descriptors by conceptual DFT methods.

  11. In vitro perturbations of targets in cancer hallmark processes predict rodent chemical carcinogenesis.

    PubMed

    Kleinstreuer, Nicole C; Dix, David J; Houck, Keith A; Kavlock, Robert J; Knudsen, Thomas B; Martin, Matthew T; Paul, Katie B; Reif, David M; Crofton, Kevin M; Hamilton, Kerry; Hunter, Ronald; Shah, Imran; Judson, Richard S

    2013-01-01

    Thousands of untested chemicals in the environment require efficient characterization of carcinogenic potential in humans. A proposed solution is rapid testing of chemicals using in vitro high-throughput screening (HTS) assays for targets in pathways linked to disease processes to build models for priority setting and further testing. We describe a model for predicting rodent carcinogenicity based on HTS data from 292 chemicals tested in 672 assays mapping to 455 genes. All data come from the EPA ToxCast project. The model was trained on a subset of 232 chemicals with in vivo rodent carcinogenicity data in the Toxicity Reference Database (ToxRefDB). Individual HTS assays strongly associated with rodent cancers in ToxRefDB were linked to genes, pathways, and hallmark processes documented to be involved in tumor biology and cancer progression. Rodent liver cancer endpoints were linked to well-documented pathways such as peroxisome proliferator-activated receptor signaling and TP53 and novel targets such as PDE5A and PLAUR. Cancer hallmark genes associated with rodent thyroid tumors were found to be linked to human thyroid tumors and autoimmune thyroid disease. A model was developed in which these genes/pathways function as hypothetical enhancers or promoters of rat thyroid tumors, acting secondary to the key initiating event of thyroid hormone disruption. A simple scoring function was generated to identify chemicals with significant in vitro evidence that was predictive of in vivo carcinogenicity in different rat tissues and organs. This scoring function was applied to an external test set of 33 compounds with carcinogenicity classifications from the EPA's Office of Pesticide Programs and successfully (p = 0.024) differentiated between chemicals classified as "possible"/"probable"/"likely" carcinogens and those designated as "not likely" or with "evidence of noncarcinogenicity." This model represents a chemical carcinogenicity prioritization tool supporting targeted

  12. Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

    PubMed Central

    Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

    2014-01-01

    Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

  13. Oral LD50 toxicity modeling and prediction of per- and polyfluorinated chemicals on rat and mouse.

    PubMed

    Bhhatarai, Barun; Gramatica, Paola

    2011-05-01

    Quantitative structure-activity relationship (QSAR) analyses were performed using the LD(50) oral toxicity data of per- and polyfluorinated chemicals (PFCs) on rodents: rat and mouse. PFCs are studied under the EU project CADASTER which uses the available experimental data for prediction and prioritization of toxic chemicals for risk assessment by using the in silico tools. The methodology presented here applies chemometrical analysis on the existing experimental data and predicts the toxicity of new compounds. QSAR analyses were performed on the available 58 mouse and 50 rat LD(50) oral data using multiple linear regression (MLR) based on theoretical molecular descriptors selected by genetic algorithm (GA). Training and prediction sets were prepared a priori from available experimental datasets in terms of structure and response. These sets were used to derive statistically robust and predictive (both internally and externally) models. The structural applicability domain (AD) of the models were verified on 376 per- and polyfluorinated chemicals including those in REACH preregistration list. The rat and mouse endpoints were predicted by each model for the studied compounds, and finally 30 compounds, all perfluorinated, were prioritized as most important for experimental toxicity analysis under the project. In addition, cumulative study on compounds within the AD of all four models, including two earlier published models on LC(50) rodent analysis was studied and the cumulative toxicity trend was observed using principal component analysis (PCA). The similarities and the differences observed in terms of descriptors and chemical/mechanistic meaning encoded by descriptors to prioritize the most toxic compounds are highlighted.

  14. Degradation of Perfluorinated Ether Lubricants on Pure Aluminum Surfaces: Semiempirical Quantum Chemical Modeling

    NASA Technical Reports Server (NTRS)

    Slaby, Scott M.; Ewing, David W.; Zehe, Michael J.

    1997-01-01

    The AM1 semiempirical quantum chemical method was used to model the interaction of perfluoroethers with aluminum surfaces. Perfluorodimethoxymethane and perfluorodimethyl ether were studied interacting with aluminum surfaces, which were modeled by a five-atom cluster and a nine-atom cluster. Interactions were studied for edge (high index) sites and top (low index) sites of the clusters. Both dissociative binding and nondissociative binding were found, with dissociative binding being stronger. The two different ethers bound and dissociated on the clusters in different ways: perfluorodimethoxymethane through its oxygen atoms, but perfluorodimethyl ether through its fluorine atoms. The acetal linkage of perfluorodimeth-oxymethane was the key structural feature of this molecule in its binding and dissociation on the aluminum surface models. The high-index sites of the clusters caused the dissociation of both ethers. These results are consistent with the experimental observation that perfluorinated ethers decompose in contact with sputtered aluminum surfaces.

  15. Quantum transport under ac drive from the leads: A Redfield quantum master equation approach

    NASA Astrophysics Data System (ADS)

    Purkayastha, Archak; Dubi, Yonatan

    2017-08-01

    Evaluating the time-dependent dynamics of driven open quantum systems is relevant for a theoretical description of many systems, including molecular junctions, quantum dots, cavity-QED experiments, cold atoms experiments, and more. Here, we formulate a rigorous microscopic theory of an out-of-equilibrium open quantum system of noninteracting particles on a lattice weakly coupled bilinearly to multiple baths and driven by periodically varying thermodynamic parameters like temperature and chemical potential of the bath. The particles can be either bosonic or fermionic and the lattice can be of any dimension and geometry. Based on the Redfield quantum master equation under Born-Markov approximation, we derive a linear differential equation for an equal time two point correlation matrix, sometimes also called a single-particle density matrix, from which various physical observables, for example, current, can be calculated. Various interesting physical effects, such as resonance, can be directly read off from the equations. Thus, our theory is quite general and gives quite transparent and easy-to-calculate results. We validate our theory by comparing with exact numerical simulations. We apply our method to a generic open quantum system, namely, a double quantum dot coupled to leads with modulating chemical potentials. The two most important experimentally relevant insights from this are as follows: (i) Time-dependent measurements of current for symmetric oscillating voltages (with zero instantaneous voltage bias) can point to the degree of asymmetry in the system-bath coupling and (ii) under certain conditions time-dependent currents can exceed time-averaged currents by several orders of magnitude, and can therefore be detected even when the average current is below the measurement threshold.

  16. Quantum Yield Heterogeneity among Single Nonblinking Quantum Dots Revealed by Atomic Structure-Quantum Optics Correlation

    DOE PAGES

    Orfield, Noah J.; McBride, James R.; Wang, Feng; ...

    2016-02-05

    Physical variations in colloidal nanostructures give rise to heterogeneity in expressed optical behavior. This correlation between nanoscale structure and function demands interrogation of both atomic structure and photophysics at the level of single nanostructures to be fully understood. In this paper, by conducting detailed analyses of fine atomic structure, chemical composition, and time-resolved single-photon photoluminescence data for the same individual nanocrystals, we reveal inhomogeneity in the quantum yields of single nonblinking “giant” CdSe/CdS core/shell quantum dots (g-QDs). We find that each g-QD possesses distinctive single exciton and biexciton quantum yields that result mainly from variations in the degree of charging,more » rather than from volume or structure inhomogeneity. We further establish that there is a very limited nonemissive “dark” fraction (<2%) among the studied g-QDs and present direct evidence that the g-QD core must lack inorganic passivation for the g-QD to be “dark”. Finally and therefore, in contrast to conventional QDs, ensemble photoluminescence quantum yield is principally defined by charging processes rather than the existence of dark g-QDs.« less

  17. Bohm's Quantum Potential and the Visualization of Molecular Structure

    NASA Technical Reports Server (NTRS)

    Levit, Creon; Chancellor, Marisa K. (Technical Monitor)

    1997-01-01

    David Bohm's ontological interpretation of quantum theory can shed light on otherwise counter-intuitive quantum mechanical phenomena including chemical bonding. In the field of quantum chemistry, Richard Bader has shown that the topology of the Laplacian of the electronic charge density characterizes many features of molecular structure and reactivity. Visual and computational examination suggests that the Laplacian of Bader and the quantum potential of Bohm are morphologically equivalent. It appears that Bohmian mechanics and the quantum potential can make chemistry as clear as they makes physics.

  18. Fragment-based 13C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods

    NASA Astrophysics Data System (ADS)

    Hartman, Joshua D.; Monaco, Stephen; Schatschneider, Bohdan; Beran, Gregory J. O.

    2015-09-01

    We assess the quality of fragment-based ab initio isotropic 13C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic 13C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readily in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.

  19. Fragment-based (13)C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods.

    PubMed

    Hartman, Joshua D; Monaco, Stephen; Schatschneider, Bohdan; Beran, Gregory J O

    2015-09-14

    We assess the quality of fragment-based ab initio isotropic (13)C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic (13)C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readily in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.

  20. The structure and photochemical transformation of cyclopropylacetylene radical cation as revealed by matrix EPR and quantum chemical study

    NASA Astrophysics Data System (ADS)

    Shiryaeva, Ekaterina S.; Tyurin, Daniil A.; Feldman, Vladimir I.

    2012-05-01

    The primary radical cation of cyclopropylacetylene was first characterized by EPR spectroscopy in low-temperature freon matrices. The assignment was confirmed by specific deuteration and quantum-chemical calculations at PBE0 and CCSD(T) levels. Photolysis with visible light led to irreversible transformation of the initial species to a ring-open structure. Detailed computational analysis of energy and magnetic resonance parameters of possible reaction products justified formation of pent-3-en-1-yne radical cation (presumably, a (Z)-isomer). This conclusion was also supported by the effect of specific deuteration.

  1. Combined friction force microscopy and quantum chemical investigation of the tribotronic response at the propylammonium nitrate-graphite interface.

    PubMed

    Li, H; Atkin, R; Page, A J

    2015-06-28

    The energetic origins of the variation in friction with potential at the propylammonium nitrate-graphite interface are revealed using friction force microscopy (FFM) in combination with quantum chemical simulations. For boundary layer lubrication, as the FFM tip slides energy is dissipated via (1) boundary layer ions and (2) expulsion of near-surface ion layers from the space between the surface and advancing tip. Simulations reveal how changing the surface potential changes the ion composition of the boundary and near surface layer, which controls energy dissipation through both pathways, and thus the friction.

  2. Effects of quantum confinement and shape on band gap of core/shell quantum dots and nanowires

    NASA Astrophysics Data System (ADS)

    Gao, Faming

    2011-05-01

    A quantum confinement model for nanocrystals developed is extended to study for the optical gap shifts in core/shell quantum dots and nanowires. The chemical bond properties and gap shifts in the InP/ZnS, CdSe/CdS, CdSe/ZnS, and CdTe/ZnS core/shell quantum dots are calculated in detail. The calculated band gaps are in excellent agreement with experimental values. The effects of structural taping and twinning on quantum confinement of InP and Si nanowires are elucidated. It is found theoretically that a competition between the positive Kubo energy-gap shift and the negative surface energy shift plays the crucial role in the optical gaps of these nanosystems.

  3. Occam’s Quantum Strop: Synchronizing and Compressing Classical Cryptic Processes via a Quantum Channel

    NASA Astrophysics Data System (ADS)

    Mahoney, John R.; Aghamohammadi, Cina; Crutchfield, James P.

    2016-02-01

    A stochastic process’ statistical complexity stands out as a fundamental property: the minimum information required to synchronize one process generator to another. How much information is required, though, when synchronizing over a quantum channel? Recent work demonstrated that representing causal similarity as quantum state-indistinguishability provides a quantum advantage. We generalize this to synchronization and offer a sequence of constructions that exploit extended causal structures, finding substantial increase of the quantum advantage. We demonstrate that maximum compression is determined by the process’ cryptic order-a classical, topological property closely allied to Markov order, itself a measure of historical dependence. We introduce an efficient algorithm that computes the quantum advantage and close noting that the advantage comes at a cost-one trades off prediction for generation complexity.

  4. Error Sensitivity to Environmental Noise in Quantum Circuits for Chemical State Preparation.

    PubMed

    Sawaya, Nicolas P D; Smelyanskiy, Mikhail; McClean, Jarrod R; Aspuru-Guzik, Alán

    2016-07-12

    Calculating molecular energies is likely to be one of the first useful applications to achieve quantum supremacy, performing faster on a quantum than a classical computer. However, if future quantum devices are to produce accurate calculations, errors due to environmental noise and algorithmic approximations need to be characterized and reduced. In this study, we use the high performance qHiPSTER software to investigate the effects of environmental noise on the preparation of quantum chemistry states. We simulated 18 16-qubit quantum circuits under environmental noise, each corresponding to a unitary coupled cluster state preparation of a different molecule or molecular configuration. Additionally, we analyze the nature of simple gate errors in noise-free circuits of up to 40 qubits. We find that, in most cases, the Jordan-Wigner (JW) encoding produces smaller errors under a noisy environment as compared to the Bravyi-Kitaev (BK) encoding. For the JW encoding, pure dephasing noise is shown to produce substantially smaller errors than pure relaxation noise of the same magnitude. We report error trends in both molecular energy and electron particle number within a unitary coupled cluster state preparation scheme, against changes in nuclear charge, bond length, number of electrons, noise types, and noise magnitude. These trends may prove to be useful in making algorithmic and hardware-related choices for quantum simulation of molecular energies.

  5. Quantum chemical study of the structure, spectroscopy and reactivity of NO+.(H2O)n=1-5 clusters

    NASA Astrophysics Data System (ADS)

    Linton, Kirsty A.; Wright, Timothy G.; Besley, Nicholas A.

    2018-03-01

    Quantum chemical methods including Møller-Plesset perturbation (MP2) theory and density functional theory (DFT) have been used to study the structure, spectroscopy and reactivity of NO+.(H2O)n=1-5 clusters. MP2/6-311++G** calculations are shown to describe the structure and spectroscopy of the clusters well. DFT calculations with exchange-correlation functionals with a low fraction of Hartree-Fock exchange give a binding energy of NO+.(H2O) that is too high and incorrectly predict the lowest energy structure of NO+.(H2O)2, and this error may be associated with a delocalization of charge onto the water molecule directly binding to NO+. Ab initio molecular dynamics (AIMD) simulations were performed to study the NO+.(H2O)5 H+.(H2O)4 + HONO reaction to investigate the formation of HONO from NO+.(H2O)5. Whether an intracluster reaction to form HONO is observed depends on the level of electronic structure theory used. Of note is that methods that accurately describe the relative energies of the product and reactant clusters did not show reactions on the timescales studied. This suggests that in the upper atmosphere the reaction may occur owing to the energy present in the NO+.(H2O)5 complex following its formation. This article is part of the theme issue `Modern theoretical chemistry'.

  6. EPA'S TOXCAST PROGRAM FOR PREDICTING HAZARD AND PRIORITIZING TOXICITY TESTING OF ENVIRONMENTAL CHEMICALS

    EPA Science Inventory

    EPA is developing methods for utilizing computational chemistry, high-throughput screening (HTS) and various toxicogenomic technologies to predict potential for toxicity and prioritize limited testing resources towards chemicals that likely represent the greatest hazard to human ...

  7. The proposal of architecture for chemical splitting to optimize QSAR models for aquatic toxicity.

    PubMed

    Colombo, Andrea; Benfenati, Emilio; Karelson, Mati; Maran, Uko

    2008-06-01

    One of the challenges in the field of quantitative structure-activity relationship (QSAR) analysis is the correct classification of a chemical compound to an appropriate model for the prediction of activity. Thus, in previous studies, compounds have been divided into distinct groups according to their mode of action or chemical class. In the current study, theoretical molecular descriptors were used to divide 568 organic substances into subsets with toxicity measured for the 96-h lethal median concentration for the Fathead minnow (Pimephales promelas). Simple constitutional descriptors such as the number of aliphatic and aromatic rings and a quantum chemical descriptor, maximum bond order of a carbon atom divide compounds into nine subsets. For each subset of compounds the automatic forward selection of descriptors was applied to construct QSAR models. Significant correlations were achieved for each subset of chemicals and all models were validated with the leave-one-out internal validation procedure (R(2)(cv) approximately 0.80). The results encourage to consider this alternative way for the prediction of toxicity using QSAR subset models without direct reference to the mechanism of toxic action or the traditional chemical classification.

  8. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Alves, Vinicius M.; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599; Muratov, Eugene

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putativemore » sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox.

  9. Predictive Quantum Chemistry: A Step Toward ``Chemistry Without Test Tubes''

    NASA Astrophysics Data System (ADS)

    Perera, Ajith

    2007-12-01

    The merits of the claims made in two recent papers entitled "First generation of pentazole (HN5, pentazolic acid), the final azole, and a zinc pentazolate salt in solution: A new N-dearylation of 1-(p-methoxyphenyl) pyrazoles, a 2-(p-methoxyphenyl) tetrazole and application of the methodology to 1-(p-methoxyphenyl) pentazole" (R. N. Butler, J. C. Stephan and L. A. Burke, J. Chem. Commun. 2003, 1016-1017) and "First generation of the pentazolate anion is solution is far from over" (T. Schroer, R. Haiges, S. Schneider and K. O. Christe, Chem. Commun. 2005, 1607-1609) are verified by predictive quality theoretical methods. Knowing whether the CF3OH in HF solution undergoes protonation to form CF3[OH2]+ is critical to the success of the recently proposed synthetic route to form the prototype perfluorinated alcohol, CF3OH. Chirstie and co-workers first considered the 13C and 19F shielding constants to distinguish CF3OH and CF3[OH2]+, but it turns out that they both have similar chemical shifts. Furthermore, they noted that the computed 13C chemical shifts differ by 11 ppm from the measured ones and claimed that "These findings presented a dilemma because either experimental or the calculated shifts has to be seriously flawed and, therefore chemical shifts alone it was impossible to decide whether CF3OH in liquid HF is protonated or not". Instead of chemical shifts, they propose to use 13C-19F NMR spin-spin coupling constants and argue that the observed 20 Hz difference of 1J(13C-19F) to the increase in the covalent character upon protonation. The reported discrepancy in computed and measured chemical shifts is reexamined and the spin-spin coupling constants results are verified by the predicative-level calculations.

  10. The prediction of crystal structure by merging knowledge methods with first principles quantum mechanics

    NASA Astrophysics Data System (ADS)

    Ceder, Gerbrand

    2007-03-01

    The prediction of structure is a key problem in computational materials science that forms the platform on which rational materials design can be performed. Finding structure by traditional optimization methods on quantum mechanical energy models is not possible due to the complexity and high dimensionality of the coordinate space. An unusual, but efficient solution to this problem can be obtained by merging ideas from heuristic and ab initio methods: In the same way that scientist build empirical rules by observation of experimental trends, we have developed machine learning approaches that extract knowledge from a large set of experimental information and a database of over 15,000 first principles computations, and used these to rapidly direct accurate quantum mechanical techniques to the lowest energy crystal structure of a material. Knowledge is captured in a Bayesian probability network that relates the probability to find a particular crystal structure at a given composition to structure and energy information at other compositions. We show that this approach is highly efficient in finding the ground states of binary metallic alloys and can be easily generalized to more complex systems.

  11. Quantum limit of heat flow across a single electronic channel.

    PubMed

    Jezouin, S; Parmentier, F D; Anthore, A; Gennser, U; Cavanna, A; Jin, Y; Pierre, F

    2013-11-01

    Quantum physics predicts that there is a fundamental maximum heat conductance across a single transport channel and that this thermal conductance quantum, G(Q), is universal, independent of the type of particles carrying the heat. Such universality, combined with the relationship between heat and information, signals a general limit on information transfer. We report on the quantitative measurement of the quantum-limited heat flow for Fermi particles across a single electronic channel, using noise thermometry. The demonstrated agreement with the predicted G(Q) establishes experimentally this basic building block of quantum thermal transport. The achieved accuracy of below 10% opens access to many experiments involving the quantum manipulation of heat.

  12. Preface: Special Topic on Nuclear Quantum Effects

    NASA Astrophysics Data System (ADS)

    Tuckerman, Mark; Ceperley, David

    2018-03-01

    Although the observable universe strictly obeys the laws of quantum mechanics, in many instances, a classical description that either ignores quantum effects entirely or accounts for them at a very crude level is sufficient to describe a wide variety of phenomena. However, when this approximation breaks down, as is often the case for processes involving light nuclei, a full quantum treatment becomes indispensable. This Special Topic in The Journal of Chemical Physics showcases recent advances in our understanding of nuclear quantum effects in condensed phases as well as novel algorithmic developments and applications that have enhanced the capability to study these effects.

  13. Preface: Special Topic on Nuclear Quantum Effects.

    PubMed

    Tuckerman, Mark; Ceperley, David

    2018-03-14

    Although the observable universe strictly obeys the laws of quantum mechanics, in many instances, a classical description that either ignores quantum effects entirely or accounts for them at a very crude level is sufficient to describe a wide variety of phenomena. However, when this approximation breaks down, as is often the case for processes involving light nuclei, a full quantum treatment becomes indispensable. This Special Topic in The Journal of Chemical Physics showcases recent advances in our understanding of nuclear quantum effects in condensed phases as well as novel algorithmic developments and applications that have enhanced the capability to study these effects.

  14. Modeling the Non-Equilibrium Process of the Chemical Adsorption of Ammonia on GaN(0001) Reconstructed Surfaces Based on Steepest-Entropy-Ascent Quantum Thermodynamics.

    PubMed

    Kusaba, Akira; Li, Guanchen; von Spakovsky, Michael R; Kangawa, Yoshihiro; Kakimoto, Koichi

    2017-08-15

    Clearly understanding elementary growth processes that depend on surface reconstruction is essential to controlling vapor-phase epitaxy more precisely. In this study, ammonia chemical adsorption on GaN(0001) reconstructed surfaces under metalorganic vapor phase epitaxy (MOVPE) conditions (3Ga-H and N ad -H + Ga-H on a 2 × 2 unit cell) is investigated using steepest-entropy-ascent quantum thermodynamics (SEAQT). SEAQT is a thermodynamic-ensemble based, first-principles framework that can predict the behavior of non-equilibrium processes, even those far from equilibrium where the state evolution is a combination of reversible and irreversible dynamics. SEAQT is an ideal choice to handle this problem on a first-principles basis since the chemical adsorption process starts from a highly non-equilibrium state. A result of the analysis shows that the probability of adsorption on 3Ga-H is significantly higher than that on N ad -H + Ga-H. Additionally, the growth temperature dependence of these adsorption probabilities and the temperature increase due to the heat of reaction is determined. The non-equilibrium thermodynamic modeling applied can lead to better control of the MOVPE process through the selection of preferable reconstructed surfaces. The modeling also demonstrates the efficacy of DFT-SEAQT coupling for determining detailed non-equilibrium process characteristics with a much smaller computational burden than would be entailed with mechanics-based, microscopic-mesoscopic approaches.

  15. Modeling the Non-Equilibrium Process of the Chemical Adsorption of Ammonia on GaN(0001) Reconstructed Surfaces Based on Steepest-Entropy-Ascent Quantum Thermodynamics

    PubMed Central

    Kusaba, Akira; von Spakovsky, Michael R.; Kangawa, Yoshihiro; Kakimoto, Koichi

    2017-01-01

    Clearly understanding elementary growth processes that depend on surface reconstruction is essential to controlling vapor-phase epitaxy more precisely. In this study, ammonia chemical adsorption on GaN(0001) reconstructed surfaces under metalorganic vapor phase epitaxy (MOVPE) conditions (3Ga-H and Nad-H + Ga-H on a 2 × 2 unit cell) is investigated using steepest-entropy-ascent quantum thermodynamics (SEAQT). SEAQT is a thermodynamic-ensemble based, first-principles framework that can predict the behavior of non-equilibrium processes, even those far from equilibrium where the state evolution is a combination of reversible and irreversible dynamics. SEAQT is an ideal choice to handle this problem on a first-principles basis since the chemical adsorption process starts from a highly non-equilibrium state. A result of the analysis shows that the probability of adsorption on 3Ga-H is significantly higher than that on Nad-H + Ga-H. Additionally, the growth temperature dependence of these adsorption probabilities and the temperature increase due to the heat of reaction is determined. The non-equilibrium thermodynamic modeling applied can lead to better control of the MOVPE process through the selection of preferable reconstructed surfaces. The modeling also demonstrates the efficacy of DFT-SEAQT coupling for determining detailed non-equilibrium process characteristics with a much smaller computational burden than would be entailed with mechanics-based, microscopic-mesoscopic approaches. PMID:28809816

  16. Clinical Potential of Quantum Dots

    PubMed Central

    Iga, Arthur M.; Robertson, John H. P.; Winslet, Marc C.; Seifalian, Alexander M.

    2007-01-01

    Advances in nanotechnology have led to the development of novel fluorescent probes called quantum dots. Quantum dots have revolutionalized the processes of tagging molecules within research settings and are improving sentinel lymph node mapping and identification in vivo studies. As the unique physical and chemical properties of these fluorescent probes are being unraveled, new potential methods of early cancer detection, rapid spread and therapeutic management, that is, photodynamic therapy are being explored. Encouraging results of optical and real time identification of sentinel lymph nodes and lymph flow using quantum dots in vivo models are emerging. Quantum dots have also superseded many of the limitations of organic fluorophores and are a promising alternative as a research tool. In this review, we examine the promising clinical potential of quantum dots, their hindrances for clinical use and the current progress in abrogating their inherent toxicity. PMID:18317518

  17. Interaction of surface hydroxyls with adsorbed molecules. A quantum-chemical study

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Geerlings, P.; Tariel, N.; Botrel, A.

    1984-11-08

    A study has been conducted to explain the interaction mechanisms of (bridging and terminal) surface hydroxyl groups with molecules, using ab initio, EHT, and CNDO/2-FA quantum-chemical calculations. Bond strength variations and charge shifts were found to be in complete agreement with Gutmann's rules, and provide a basis for the understanding of the Bronsted acid properties of zeolites and amorphous silica-alumina. A quantitative measure of the interaction strength is possible by referring to the experimentally determined donor number (Gutmann) following many molecules, but care should be taken for those molecules for which the donor strength was determined by indirect methods. Onlymore » a few exceptions to Gutmann's rules should exist, e.g., in those cases where the atom interacting with the proton is not the most electronegative of the donor molecule (such as for CO). Individual bonds in a given complex are more susceptible to perturbations (changes in composition and interactions with adsorbing molecules) if the coordination number increases. These rules are in agreement with the observations and apply to all reactions (inter- or intramolecular) involving a change in coordination. 52 references, 6 figures, 4 tables.« less

  18. Computational neural networks in chemistry: Model free mapping devices for predicting chemical reactivity from molecular structure

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Elrod, D.W.

    1992-01-01

    Computational neural networks (CNNs) are a computational paradigm inspired by the brain's massively parallel network of highly interconnected neurons. The power of computational neural networks derives not so much from their ability to model the brain as from their ability to learn by example and to map highly complex, nonlinear functions, without the need to explicitly specify the functional relationship. Two central questions about CNNs were investigated in the context of predicting chemical reactions: (1) the mapping properties of neural networks and (2) the representation of chemical information for use in CNNs. Chemical reactivity is here considered an example ofmore » a complex, nonlinear function of molecular structure. CNN's were trained using modifications of the back propagation learning rule to map a three dimensional response surface similar to those typically observed in quantitative structure-activity and structure-property relationships. The computational neural network's mapping of the response surface was found to be robust to the effects of training sample size, noisy data and intercorrelated input variables. The investigation of chemical structure representation led to the development of a molecular structure-based connection-table representation suitable for neural network training. An extension of this work led to a BE-matrix structure representation that was found to be general for several classes of reactions. The CNN prediction of chemical reactivity and regiochemistry was investigated for electrophilic aromatic substitution reactions, Markovnikov addition to alkenes, Saytzeff elimination from haloalkanes, Diels-Alder cycloaddition, and retro Diels-Alder ring opening reactions using these connectivity-matrix derived representations. The reaction predictions made by the CNNs were more accurate than those of an expert system and were comparable to predictions made by chemists.« less

  19. Conceptual versus Algorithmic Learning in High School Chemistry: The Case of Basic Quantum Chemical Concepts--Part 1. Statistical Analysis of a Quantitative Study

    ERIC Educational Resources Information Center

    Papaphotis, Georgios; Tsaparlis, Georgios

    2008-01-01

    Part 1 of the findings are presented of a quantitative study (n = 125) on basic quantum chemical concepts taught in the twelfth grade (age 17-18 years) in Greece. A paper-and-pencil test of fourteen questions was used. The study compared performance in five questions that tested recall of knowledge or application of algorithmic procedures (type-A…

  20. From consumption to harvest: Environmental fate prediction of excreted ionizable trace organic chemicals.

    PubMed

    Polesel, Fabio; Plósz, Benedek Gy; Trapp, Stefan

    2015-11-01

    Excreted trace organic chemicals, e.g., pharmaceuticals and biocides, typically undergo incomplete elimination in municipal wastewater treatment plants (WWTPs) and are released to surface water via treated effluents and to agricultural soils through sludge amendment and/or irrigation with freshwater or reclaimed wastewater. Recent research has shown the tendency for these substances to accumulate in food crops. In this study, we developed and applied a simulation tool to predict the fate of three ionizable trace chemicals (triclosan-TCS, furosemide-FUR, ciprofloxacin-CIP) from human consumption/excretion up to the accumulation in soil and plant, following field amendment with sewage sludge or irrigation with river water (assuming dilution of WWTP effluent). The simulation tool combines the SimpleTreat model modified for fate prediction of ionizable chemicals in a generic WWTP and a recently developed dynamic soil-plant uptake model. The simulation tool was tested using country-specific (e.g., consumption/emission rates, precipitation and temperature) input data. A Monte Carlo-based approach was adopted to account for the uncertainty associated to physico-chemical and biokinetic model parameters. Results obtained in this study suggest significant accumulation of TCS and CIP in sewage sludge (1.4-2.8 mg kgDW(-1)) as compared to FUR (0.02-0.11 mg kgDW(-1)). For the latter substance, more than half of the influent load (60.1%-72.5%) was estimated to be discharged via WWTP effluent. Specific emission rates (g ha(-1) a(-1)) of FUR to soil via either sludge application or irrigation were up to 300 times lower than for TCS and CIP. Nevertheless, high translocation potential to wheat was predicted for FUR, reaching concentrations up to 4.3 μg kgDW(-1) in grain. Irrigation was found to enhance the relative translocation of FUR to plant (45.3%-48.9% of emission to soil), as compared to sludge application (21.9%-27.6%). A comparison with peer-reviewed literature showed

  1. Are quantum-mechanical-like models possible, or necessary, outside quantum physics?

    NASA Astrophysics Data System (ADS)

    Plotnitsky, Arkady

    2014-12-01

    This article examines some experimental conditions that invite and possibly require recourse to quantum-mechanical-like mathematical models (QMLMs), models based on the key mathematical features of quantum mechanics, in scientific fields outside physics, such as biology, cognitive psychology, or economics. In particular, I consider whether the following two correlative features of quantum phenomena that were decisive for establishing the mathematical formalism of quantum mechanics play similarly important roles in QMLMs elsewhere. The first is the individuality and discreteness of quantum phenomena, and the second is the irreducibly probabilistic nature of our predictions concerning them, coupled to the particular character of the probabilities involved, as different from the character of probabilities found in classical physics. I also argue that these features could be interpreted in terms of a particular form of epistemology that suspends and even precludes a causal and, in the first place, realist description of quantum objects and processes. This epistemology limits the descriptive capacity of quantum theory to the description, classical in nature, of the observed quantum phenomena manifested in measuring instruments. Quantum mechanics itself only provides descriptions, probabilistic in nature, concerning numerical data pertaining to such phenomena, without offering a physical description of quantum objects and processes. While QMLMs share their use of the quantum-mechanical or analogous mathematical formalism, they may differ by the roles, if any, the two features in question play in them and by different ways of interpreting the phenomena they considered and this formalism itself. This article will address those differences as well.

  2. Controlling the Properties of Matter with Quantum Dots

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Klimov, Victor

    2017-03-22

    Solar cells and photodetectors could soon be made from new types of materials based on semiconductor quantum dots, thanks to new insights based on ultrafast measurements capturing real-time photoconversion processes. Photoconversion is a process wherein the energy of a photon, or quantum of light, is converted into other forms of energy, for example, chemical or electrical. Semiconductor quantum dots are chemically synthesized crystalline nanoparticles that have been studied for more than three decades in the context of various photoconversion schemes including photovoltaics (generation of photo-electricity) and photo-catalysis (generation of “solar fuels”). The appeal of quantum dots comes from the unmatchedmore » tunability of their physical properties, which can be adjusted by controlling the size, shape and composition of the dots. At Los Alamos, the research connects to the institutional mission of solving national security challenges through scientific excellence, in this case focusing on novel physical principles for highly efficient photoconversion, charge manipulation in exploratory device structures and novel nanomaterials.« less

  3. Holographic description of a quantum black hole on a computer.

    PubMed

    Hanada, Masanori; Hyakutake, Yoshifumi; Ishiki, Goro; Nishimura, Jun

    2014-05-23

    Black holes have been predicted to radiate particles and eventually evaporate, which has led to the information loss paradox and implies that the fundamental laws of quantum mechanics may be violated. Superstring theory, a consistent theory of quantum gravity, provides a possible solution to the paradox if evaporating black holes can actually be described in terms of standard quantum mechanical systems, as conjectured from the theory. Here, we test this conjecture by calculating the mass of a black hole in the corresponding quantum mechanical system numerically. Our results agree well with the prediction from gravity theory, including the leading quantum gravity correction. Our ability to simulate black holes offers the potential to further explore the yet mysterious nature of quantum gravity through well-established quantum mechanics. Copyright © 2014, American Association for the Advancement of Science.

  4. Higher-order kinetic expansion of quantum dissipative dynamics: mapping quantum networks to kinetic networks.

    PubMed

    Wu, Jianlan; Cao, Jianshu

    2013-07-28

    We apply a new formalism to derive the higher-order quantum kinetic expansion (QKE) for studying dissipative dynamics in a general quantum network coupled with an arbitrary thermal bath. The dynamics of system population is described by a time-convoluted kinetic equation, where the time-nonlocal rate kernel is systematically expanded of the order of off-diagonal elements of the system Hamiltonian. In the second order, the rate kernel recovers the expression of the noninteracting-blip approximation method. The higher-order corrections in the rate kernel account for the effects of the multi-site quantum coherence and the bath relaxation. In a quantum harmonic bath, the rate kernels of different orders are analytically derived. As demonstrated by four examples, the higher-order QKE can reliably predict quantum dissipative dynamics, comparing well with the hierarchic equation approach. More importantly, the higher-order rate kernels can distinguish and quantify distinct nontrivial quantum coherent effects, such as long-range energy transfer from quantum tunneling and quantum interference arising from the phase accumulation of interactions.

  5. Structure-based predictions of 13C-NMR chemical shifts for a series of 2-functionalized 5-(methylsulfonyl)-1-phenyl-1H-indoles derivatives using GA-based MLR method

    NASA Astrophysics Data System (ADS)

    Ghavami, Raouf; Sadeghi, Faridoon; Rasouli, Zolikha; Djannati, Farhad

    2012-12-01

    Experimental values for the 13C NMR chemical shifts (ppm, TMS = 0) at 300 K ranging from 96.28 ppm (C4' of indole derivative 17) to 159.93 ppm (C4' of indole derivative 23) relative to deuteride chloroform (CDCl3, 77.0 ppm) or dimethylsulfoxide (DMSO, 39.50 ppm) as internal reference in CDCl3 or DMSO-d6 solutions have been collected from literature for thirty 2-functionalized 5-(methylsulfonyl)-1-phenyl-1H-indole derivatives containing different substituted groups. An effective quantitative structure-property relationship (QSPR) models were built using hybrid method combining genetic algorithm (GA) based on stepwise selection multiple linear regression (SWS-MLR) as feature-selection tools and correlation models between each carbon atom of indole derivative and calculated descriptors. Each compound was depicted by molecular structural descriptors that encode constitutional, topological, geometrical, electrostatic, and quantum chemical features. The accuracy of all developed models were confirmed using different types of internal and external procedures and various statistical tests. Furthermore, the domain of applicability for each model which indicates the area of reliable predictions was defined.

  6. Assessing deep and shallow learning methods for quantitative prediction of acute chemical toxicity.

    PubMed

    Liu, Ruifeng; Madore, Michael; Glover, Kyle P; Feasel, Michael G; Wallqvist, Anders

    2018-05-02

    Animal-based methods for assessing chemical toxicity are struggling to meet testing demands. In silico approaches, including machine-learning methods, are promising alternatives. Recently, deep neural networks (DNNs) were evaluated and reported to outperform other machine-learning methods for quantitative structure-activity relationship modeling of molecular properties. However, most of the reported performance evaluations relied on global performance metrics, such as the root mean squared error (RMSE) between the predicted and experimental values of all samples, without considering the impact of sample distribution across the activity spectrum. Here, we carried out an in-depth analysis of DNN performance for quantitative prediction of acute chemical toxicity using several datasets. We found that the overall performance of DNN models on datasets of up to 30,000 compounds was similar to that of random forest (RF) models, as measured by the RMSE and correlation coefficients between the predicted and experimental results. However, our detailed analyses demonstrated that global performance metrics are inappropriate for datasets with a highly uneven sample distribution, because they show a strong bias for the most populous compounds along the toxicity spectrum. For highly toxic compounds, DNN and RF models trained on all samples performed much worse than the global performance metrics indicated. Surprisingly, our variable nearest neighbor method, which utilizes only structurally similar compounds to make predictions, performed reasonably well, suggesting that information of close near neighbors in the training sets is a key determinant of acute toxicity predictions.

  7. Quantum-Like Bayesian Networks for Modeling Decision Making

    PubMed Central

    Moreira, Catarina; Wichert, Andreas

    2016-01-01

    In this work, we explore an alternative quantum structure to perform quantum probabilistic inferences to accommodate the paradoxical findings of the Sure Thing Principle. We propose a Quantum-Like Bayesian Network, which consists in replacing classical probabilities by quantum probability amplitudes. However, since this approach suffers from the problem of exponential growth of quantum parameters, we also propose a similarity heuristic that automatically fits quantum parameters through vector similarities. This makes the proposed model general and predictive in contrast to the current state of the art models, which cannot be generalized for more complex decision scenarios and that only provide an explanatory nature for the observed paradoxes. In the end, the model that we propose consists in a nonparametric method for estimating inference effects from a statistical point of view. It is a statistical model that is simpler than the previous quantum dynamic and quantum-like models proposed in the literature. We tested the proposed network with several empirical data from the literature, mainly from the Prisoner's Dilemma game and the Two Stage Gambling game. The results obtained show that the proposed quantum Bayesian Network is a general method that can accommodate violations of the laws of classical probability theory and make accurate predictions regarding human decision-making in these scenarios. PMID:26858669

  8. Test battery with the human cell line activation test, direct peptide reactivity assay and DEREK based on a 139 chemical data set for predicting skin sensitizing potential and potency of chemicals.

    PubMed

    Takenouchi, Osamu; Fukui, Shiho; Okamoto, Kenji; Kurotani, Satoru; Imai, Noriyasu; Fujishiro, Miyuki; Kyotani, Daiki; Kato, Yoshinao; Kasahara, Toshihiko; Fujita, Masaharu; Toyoda, Akemi; Sekiya, Daisuke; Watanabe, Shinichi; Seto, Hirokazu; Hirota, Morihiko; Ashikaga, Takao; Miyazawa, Masaaki

    2015-11-01

    To develop a testing strategy incorporating the human cell line activation test (h-CLAT), direct peptide reactivity assay (DPRA) and DEREK, we created an expanded data set of 139 chemicals (102 sensitizers and 37 non-sensitizers) by combining the existing data set of 101 chemicals through the collaborative projects of Japan Cosmetic Industry Association. Of the additional 38 chemicals, 15 chemicals with relatively low water solubility (log Kow > 3.5) were selected to clarify the limitation of testing strategies regarding the lipophilic chemicals. Predictivities of the h-CLAT, DPRA and DEREK, and the combinations thereof were evaluated by comparison to results of the local lymph node assay. When evaluating 139 chemicals using combinations of three methods based on integrated testing strategy (ITS) concept (ITS-based test battery) and a sequential testing strategy (STS) weighing the predictive performance of the h-CLAT and DPRA, overall similar predictivities were found as before on the 101 chemical data set. An analysis of false negative chemicals suggested a major limitation of our strategies was the testing of low water-soluble chemicals. When excluded the negative results for chemicals with log Kow > 3.5, the sensitivity and accuracy of ITS improved to 97% (91 of 94 chemicals) and 89% (114 of 128). Likewise, the sensitivity and accuracy of STS to 98% (92 of 94) and 85% (111 of 129). Moreover, the ITS and STS also showed good correlation with local lymph node assay on three potency classifications, yielding accuracies of 74% (ITS) and 73% (STS). Thus, the inclusion of log Kow in analysis could give both strategies a higher predictive performance. Copyright © 2015 John Wiley & Sons, Ltd.

  9. Semiempirical Quantum Mechanical Methods for Noncovalent Interactions for Chemical and Biochemical Applications

    PubMed Central

    2016-01-01

    Semiempirical (SE) methods can be derived from either Hartree–Fock or density functional theory by applying systematic approximations, leading to efficient computational schemes that are several orders of magnitude faster than ab initio calculations. Such numerical efficiency, in combination with modern computational facilities and linear scaling algorithms, allows application of SE methods to very large molecular systems with extensive conformational sampling. To reliably model the structure, dynamics, and reactivity of biological and other soft matter systems, however, good accuracy for the description of noncovalent interactions is required. In this review, we analyze popular SE approaches in terms of their ability to model noncovalent interactions, especially in the context of describing biomolecules, water solution, and organic materials. We discuss the most significant errors and proposed correction schemes, and we review their performance using standard test sets of molecular systems for quantum chemical methods and several recent applications. The general goal is to highlight both the value and limitations of SE methods and stimulate further developments that allow them to effectively complement ab initio methods in the analysis of complex molecular systems. PMID:27074247

  10. Quantum chemical modeling of enzymatic reactions: the case of histone lysine methyltransferase.

    PubMed

    Georgieva, Polina; Himo, Fahmi

    2010-06-01

    Quantum chemical cluster models of enzyme active sites are today an important and powerful tool in the study of various aspects of enzymatic reactivity. This methodology has been applied to a wide spectrum of reactions and many important mechanistic problems have been solved. Herein, we report a systematic study of the reaction mechanism of the histone lysine methyltransferase (HKMT) SET7/9 enzyme, which catalyzes the methylation of the N-terminal histone tail of the chromatin structure. In this study, HKMT SET7/9 serves as a representative case to examine the modeling approach for the important class of methyl transfer enzymes. Active site models of different sizes are used to evaluate the methodology. In particular, the dependence of the calculated energies on the model size, the influence of the dielectric medium, and the particular choice of the dielectric constant are discussed. In addition, we examine the validity of some technical aspects, such as geometry optimization in solvent or with a large basis set, and the use of different density functional methods. Copyright 2010 Wiley Periodicals, Inc.

  11. Quantum chemical determination of Young's modulus of lignin. Calculations on a beta-O-4' model compound.

    PubMed

    Elder, Thomas

    2007-11-01

    The calculation of Young's modulus of lignin has been examined by subjecting a dimeric model compound to strain, coupled with the determination of energy and stress. The computational results, derived from quantum chemical calculations, are in agreement with available experimental results. Changes in geometry indicate that modifications in dihedral angles occur in response to linear strain. At larger levels of strain, bond rupture is evidenced by abrupt changes in energy, structure, and charge. Based on the current calculations, the bond scission may be occurring through a homolytic reaction between aliphatic carbon atoms. These results may have implications in the reactivity of lignin especially when subjected to processing methods that place large mechanical forces on the structure.

  12. Evidence for a Quantum-to-Classical Transition in a Pair of Coupled Quantum Rotors

    NASA Astrophysics Data System (ADS)

    Gadway, Bryce; Reeves, Jeremy; Krinner, Ludwig; Schneble, Dominik

    2013-05-01

    The understanding of how classical dynamics can emerge in closed quantum systems is a problem of fundamental importance. Remarkably, while classical behavior usually arises from coupling to thermal fluctuations or random spectral noise, it may also be an innate property of certain isolated, periodically driven quantum systems. Here, we experimentally realize the simplest such system, consisting of two coupled, kicked quantum rotors, by subjecting a coherent atomic matter wave to two periodically pulsed, incommensurate optical lattices. Momentum transport in this system is found to be radically different from that in a single kicked rotor, with a breakdown of dynamical localization and the emergence of classical diffusion. Our observation, which confirms a long-standing prediction for many-dimensional quantum-chaotic systems, sheds new light on the quantum-classical correspondence.

  13. Statistics-based model for prediction of chemical biosynthesis yield from Saccharomyces cerevisiae

    PubMed Central

    2011-01-01

    Background The robustness of Saccharomyces cerevisiae in facilitating industrial-scale production of ethanol extends its utilization as a platform to synthesize other metabolites. Metabolic engineering strategies, typically via pathway overexpression and deletion, continue to play a key role for optimizing the conversion efficiency of substrates into the desired products. However, chemical production titer or yield remains difficult to predict based on reaction stoichiometry and mass balance. We sampled a large space of data of chemical production from S. cerevisiae, and developed a statistics-based model to calculate production yield using input variables that represent the number of enzymatic steps in the key biosynthetic pathway of interest, metabolic modifications, cultivation modes, nutrition and oxygen availability. Results Based on the production data of about 40 chemicals produced from S. cerevisiae, metabolic engineering methods, nutrient supplementation, and fermentation conditions described therein, we generated mathematical models with numerical and categorical variables to predict production yield. Statistically, the models showed that: 1. Chemical production from central metabolic precursors decreased exponentially with increasing number of enzymatic steps for biosynthesis (>30% loss of yield per enzymatic step, P-value = 0); 2. Categorical variables of gene overexpression and knockout improved product yield by 2~4 folds (P-value < 0.1); 3. Addition of notable amount of intermediate precursors or nutrients improved product yield by over five folds (P-value < 0.05); 4. Performing the cultivation in a well-controlled bioreactor enhanced the yield of product by three folds (P-value < 0.05); 5. Contribution of oxygen to product yield was not statistically significant. Yield calculations for various chemicals using the linear model were in fairly good agreement with the experimental values. The model generally underestimated the ethanol production as

  14. Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

    PubMed Central

    Shen, Yang; Bax, Ad

    2013-01-01

    A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥ 90% fraction of the residues, with an error rate smaller than ca 3.5%, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (φ,ψ) torsion angles of ca 12°. TALOS-N also reports sidechain χ1 rotameric states for about 50% of the residues, and a consistency with reference structures of 89%. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts. PMID:23728592

  15. Vibrational spectroscopic, molecular docking and quantum chemical studies on 6-aminonicotinamide

    NASA Astrophysics Data System (ADS)

    Mohamed Asath, R.; Premkumar, S.; Mathavan, T.; Milton Franklin Benial, A.

    2017-04-01

    The most stable molecular structure of 6-aminonicotinamide (ANA) molecule was predicted by conformational analysis and vibrational spectral analysis was carried out by experimental and theoretical methods. The calculated and experimentally observed vibrational frequencies were assigned and compared. The π→π* electronic transition of the molecule was predicted by theoretically calculated ultraviolet-visible spectra in gas and liquid phase and further validated experimentally using ethanol as a solvent. Frontier molecular orbitals analysis was carried out to probe the reactive nature of the ANA molecule and further the site selectivity to specific chemical reactions were effectively analyzed by Fukui function calculation. The molecular electrostatic potential surface was simulated to confirm the reactive sites of the molecule. The natural bond orbital analysis was also performed to understand the intra molecular interactions, which confirms the bioactivity of the ANA molecule. Neuroprotective nature of the ANA molecule was analyzed by molecular docking analysis and the ANA molecule was identified as a good inhibitor against Alzheimer's disease.

  16. Frictional lubricity enhanced by quantum mechanics.

    PubMed

    Zanca, Tommaso; Pellegrini, Franco; Santoro, Giuseppe E; Tosatti, Erio

    2018-04-03

    The quantum motion of nuclei, generally ignored in the physics of sliding friction, can affect in an important manner the frictional dissipation of a light particle forced to slide in an optical lattice. The density matrix-calculated evolution of the quantum version of the basic Prandtl-Tomlinson model, describing the dragging by an external force of a point particle in a periodic potential, shows that purely classical friction predictions can be very wrong. The strongest quantum effect occurs not for weak but for strong periodic potentials, where barriers are high but energy levels in each well are discrete, and resonant Rabi or Landau-Zener tunneling to states in the nearest well can preempt classical stick-slip with nonnegligible efficiency, depending on the forcing speed. The resulting permeation of otherwise unsurmountable barriers is predicted to cause quantum lubricity, a phenomenon which we expect should be observable in the recently implemented sliding cold ion experiments.

  17. Nonlinear absorption properties of AlGaAs/GaAs multiple quantum wells grown by metalorganic chemical vapor deposition

    NASA Technical Reports Server (NTRS)

    Lee, Hsing-Chung; Kost, A.; Kawase, M.; Hariz, A.; Dapkus, P. Daniel

    1988-01-01

    The nonlinear absorption properties of the excitonic resonances associated with multiple quantum wells (MQWs) in AlGaAs/GaAs grown by metalorganic chemical vapor deposition are reported. The dependence of the saturation properties on growth parameters, especially growth temperature, and the well width are described. The minimum measured saturation intensity for these materials is 250 W/sq cm, the lowest reported value to date. The low saturation intensities are the result of excellent minority carrier properties. A systematic study of minority carrier lifetimes in quantum wells are reported. Lifetimes range from 50-350 ns depending on growth temperature and well width. When corrected for lateral diffusion effects and the measured minority carrier lifetime, the saturation data suggest that saturation intensities as low as 2.3 W/sq cm can be achieved in this system. The first measurements of the dependence of the exciton area and the magnitude of the excitonic absorption on well width are prsented. The growth of MQW structures on transparent GaP substrates is demonstrated and the electroabsorption properties of these structures are reviewed.

  18. Quantum chemical investigations of AlN-doped C60 for use as a nano-biosensor in detection of mispairing between DNA bases.

    PubMed

    Siddiqui, Shamoon Ahmad; Bouarissa, Nadir; Rasheed, Tabish; Al-Hajry, A

    2014-12-01

    Quantum chemical calculations were carried out to study the electronic structure and stability of adenine-thymine and the rare tautomer of adenine-thymine base pairs along with their Cu 2+ complexes and their interactions with AlN-modified fullerene (C58AlN) using Density Functional Theory (B3LYP method). Since, these two forms of base pairs and their Cu 2+ complexes have almost similar electronic structures, their chemical differentiation is an extremely difficult task. In this investigation, we have observed that AlN-doped C 60 could be used as a potentially viable nanoscale sensor to detect these two base pairs as well as their Cu2+ complexes.

  19. Quantum chemical approaches in structure-based virtual screening and lead optimization

    NASA Astrophysics Data System (ADS)

    Cavasotto, Claudio N.; Adler, Natalia S.; Aucar, Maria G.

    2018-05-01

    Today computational chemistry is a consolidated tool in drug lead discovery endeavors. Due to methodological developments and to the enormous advance in computer hardware, methods based on quantum mechanics (QM) have gained great attention in the last 10 years, and calculations on biomacromolecules are becoming increasingly explored, aiming to provide better accuracy in the description of protein-ligand interactions and the prediction of binding affinities. In principle, the QM formulation includes all contributions to the energy, accounting for terms usually missing in molecular mechanics force-fields, such as electronic polarization effects, metal coordination, and covalent binding; moreover, QM methods are systematically improvable, and provide a greater degree of transferability. In this mini-review we present recent applications of explicit QM-based methods in small-molecule docking and scoring, and in the calculation of binding free-energy in protein-ligand systems. Although the routine use of QM-based approaches in an industrial drug lead discovery setting remains a formidable challenging task, it is likely they will increasingly become active players within the drug discovery pipeline.

  20. Three waves for quantum gravity

    NASA Astrophysics Data System (ADS)

    Calmet, Xavier; Latosh, Boris

    2018-03-01

    Using effective field theoretical methods, we show that besides the already observed gravitational waves, quantum gravity predicts two further massive classical fields leading to two new massive waves. We set a limit on the masses of these new modes using data from the Eöt-Wash experiment. We point out that the existence of these new states is a model independent prediction of quantum gravity. We then explain how these new classical fields could impact astrophysical processes and in particular the binary inspirals of neutron stars or black holes. We calculate the emission rate of these new states in binary inspirals astrophysical processes.

  1. Use of external cavity quantum cascade laser compliance voltage in real-time trace gas sensing of multiple chemicals

    NASA Astrophysics Data System (ADS)

    Phillips, Mark C.; Taubman, Matthew S.; Kriesel, Jason

    2015-01-01

    We describe a prototype trace gas sensor designed for real-time detection of multiple chemicals. The sensor uses an external cavity quantum cascade laser (ECQCL) swept over its tuning range of 940-1075 cm-1 (9.30-10.7 μm) at a 10 Hz repetition rate. The sensor was designed for operation in multiple modes, including gas sensing within a multi-pass Heriott cell and intracavity absorption sensing using the ECQCL compliance voltage. In addition, the ECQCL compliance voltage was used to reduce effects of long-term drifts in the ECQCL output power. The sensor was characterized for noise, drift, and detection of chemicals including ammonia, methanol, ethanol, isopropanol, Freon- 134a, Freon-152a, and diisopropyl methylphosphonate (DIMP). We also present use of the sensor for mobile detection of ammonia downwind of cattle facilities, in which concentrations were recorded at 1-s intervals.

  2. Quantum Chemistry, 5th Edition by Ira N. Levine

    NASA Astrophysics Data System (ADS)

    Hinde, Robert J.

    2000-12-01

    Of course, there is no one- or two-week shortcut by which nonspecialists can master enough quantum mechanics to become informed users of quantum chemical techniques. Nevertheless, a text that integrated the fundamentals of quantum theory with a rigorous introduction to quantum chemistry could help instructors design a class that would benefit both these nonspecialists and graduate students in physical chemistry. Could such a class overcome the (undeserved) stigma associated with the physical chemistry curriculum? That remains to be seen.

  3. Predicting the NMR spectra of nucleotides by DFT calculations: cyclic uridine monophosphate.

    PubMed

    Bagno, Alessandro; Rastrelli, Federico; Saielli, Giacomo

    2008-06-01

    We present an experimental and quantum chemical NMR study of the mononucleotide cyclic uridine monophosphate in water. Spectral parameters ((1)H and (13)C chemical shifts and (1)H--(1)H, (13)C--(1)H, (31)P--(13)C and (31)P--(1)H spin-spin coupling constants) have been carefully obtained experimentally and calculated using DFT methods including the solvent effect and the conformational flexibility of the solute. This study confirms that the (1)H and (13)C spectra of polar, flexible molecules in aqueous solution can be predicted with a high level of accuracy, comparable to that obtained for less complex systems. Copyright (c) 2008 John Wiley & Sons, Ltd

  4. Quantum vacuum noise in physics and cosmology.

    PubMed

    Davies, P. C. W.

    2001-09-01

    The concept of the vacuum in quantum field theory is a subtle one. Vacuum states have a rich and complex set of properties that produce distinctive, though usually exceedingly small, physical effects. Quantum vacuum noise is familiar in optical and electronic devices, but in this paper I wish to consider extending the discussion to systems in which gravitation, or large accelerations, are important. This leads to the prediction of vacuum friction: The quantum vacuum can act in a manner reminiscent of a viscous fluid. One result is that rapidly changing gravitational fields can create particles from the vacuum, and in turn the backreaction on the gravitational dynamics operates like a damping force. I consider such effects in early universe cosmology and the theory of quantum black holes, including the possibility that the large-scale structure of the universe might be produced by quantum vacuum noise in an early inflationary phase. I also discuss the curious phenomenon that an observer who accelerates through a quantum vacuum perceives a bath of thermal radiation closely analogous to Hawking radiation from black holes, even though an inertial observer registers no particles. The effects predicted raise very deep and unresolved issues about the nature of quantum particles, the role of the observer, and the relationship between the quantum vacuum and the concepts of information and entropy. (c) 2001 American Institute of Physics.

  5. In situ electron-beam polymerization stabilized quantum dot micelles.

    PubMed

    Travert-Branger, Nathalie; Dubois, Fabien; Renault, Jean-Philippe; Pin, Serge; Mahler, Benoit; Gravel, Edmond; Dubertret, Benoit; Doris, Eric

    2011-04-19

    A polymerizable amphiphile polymer containing PEG was synthesized and used to encapsulate quantum dots in micelles. The quantum dot micelles were then polymerized using a "clean" electron beam process that did not require any post-irradiation purification. Fluorescence spectroscopy revealed that the polymerized micelles provided an organic coating that preserved the quantum dot fluorescence better than nonpolymerized micelles, even under harsh conditions. © 2011 American Chemical Society

  6. Combined spectroscopic and quantum chemical studies of ezetimibe

    NASA Astrophysics Data System (ADS)

    Prajapati, Preeti; Pandey, Jaya; Shimpi, Manishkumar R.; Srivastava, Anubha; Tandon, Poonam; Velaga, Sitaram P.; Sinha, Kirti

    2016-12-01

    Ezetimibe (EZT) is a hypocholesterolemic agent used for the treatment of elevated blood cholesterol levels as it lowers the blood cholesterol by blocking the absorption of cholesterol in intestine. Study aims to combine experimental and computational methods to provide insights into the structural and vibrational spectroscopic properties of EZT which is important for explaining drug substance physical and biological properties. Computational study on molecular properties of ezetimibe is presented using density functional theory (DFT) with B3LYP functional and 6-311++G(d,p) basis set. A detailed vibrational assignment has been done for the observed IR and Raman spectra of EZT. In addition to the conformational study, hydrogen bonding and molecular docking studies have been also performed. For conformational studies, the double well potential energy curves have been plotted for the rotation around the six flexible bonds of the molecule. UV absorption spectrum was examined in methanol solvent and compared with calculated one in solvent environment (IEF-PCM) using TD-DFT/6-31G basis set. HOMO-LUMO energy gap of both the conformers have also been calculated in order to predict its chemical reactivity and stability. The stability of the molecule was also examined by means of natural bond analysis (NBO) analysis. To account for the chemical reactivity and site selectivity of the molecules, molecular electrostatic potential (MEPS) map has been plotted. The combination of experimental and calculated results provide an insight into the structural and vibrational spectroscopic properties of EZT. In order to give an insight for the biological activity of EZT, molecular docking of EZT with protein NPC1L1 has been done.

  7. Chemical Potentials, Activity Coefficients, and Solubility in Aqueous NaCl Solutions: Prediction by Polarizable Force Fields.

    PubMed

    Moučka, Filip; Nezbeda, Ivo; Smith, William R

    2015-04-14

    We describe a computationally efficient molecular simulation methodology for calculating the concentration dependence of the chemical potentials of both solute and solvent in aqueous electrolyte solutions, based on simulations of the salt chemical potential alone. We use our approach to study the predictions for aqueous NaCl solutions at ambient conditions of these properties by the recently developed polarizable force fields (FFs) AH/BK3 of Kiss and Baranyai (J. Chem. Phys. 2013, 138, 204507) and AH/SWM4-DP of Lamoureux and Roux (J. Phys. Chem. B 2006, 110, 3308 - 3322) and by the nonpolarizable JC FF of Joung and Cheatham tailored to SPC/E water (J. Phys. Chem. B 2008, 112, 9020 - 9041). We also consider their predictions of the concentration dependence of the electrolyte activity coefficient, the crystalline solid chemical potential, the electrolyte solubility, and the solution specific volume. We first highlight the disagreement in the literature concerning calculations of solubility by means of molecular simulation in the case of the JC FF and provide strong evidence of the correctness of our methodology based on recent independently obtained results for this important test case. We then compare the predictions of the three FFs with each other and with experiment and draw conclusions concerning their relative merits, with particular emphasis on the salt chemical potential and activity coefficient vs concentration curves and their derivatives. The latter curves have only previously been available from Kirkwood-Buff integrals, which require approximate numerical integrations over system pair correlation functions at each concentration. Unlike the case of the other FFs, the AH/BK3 curves are nearly parallel to the corresponding experimental curves at moderate and higher concentrations. This leads to an excellent prediction of the water chemical potential via the Gibbs-Duhem equation and enables the activity coefficient curve to be brought into excellent agreement

  8. Quantum.Ligand.Dock: protein-ligand docking with quantum entanglement refinement on a GPU system.

    PubMed

    Kantardjiev, Alexander A

    2012-07-01

    Quantum.Ligand.Dock (protein-ligand docking with graphic processing unit (GPU) quantum entanglement refinement on a GPU system) is an original modern method for in silico prediction of protein-ligand interactions via high-performance docking code. The main flavour of our approach is a combination of fast search with a special account for overlooked physical interactions. On the one hand, we take care of self-consistency and proton equilibria mutual effects of docking partners. On the other hand, Quantum.Ligand.Dock is the the only docking server offering such a subtle supplement to protein docking algorithms as quantum entanglement contributions. The motivation for development and proposition of the method to the community hinges upon two arguments-the fundamental importance of quantum entanglement contribution in molecular interaction and the realistic possibility to implement it by the availability of supercomputing power. The implementation of sophisticated quantum methods is made possible by parallelization at several bottlenecks on a GPU supercomputer. The high-performance implementation will be of use for large-scale virtual screening projects, structural bioinformatics, systems biology and fundamental research in understanding protein-ligand recognition. The design of the interface is focused on feasibility and ease of use. Protein and ligand molecule structures are supposed to be submitted as atomic coordinate files in PDB format. A customization section is offered for addition of user-specified charges, extra ionogenic groups with intrinsic pK(a) values or fixed ions. Final predicted complexes are ranked according to obtained scores and provided in PDB format as well as interactive visualization in a molecular viewer. Quantum.Ligand.Dock server can be accessed at http://87.116.85.141/LigandDock.html.

  9. Simultaneous prediction of enzyme orthologs from chemical transformation patterns for de novo metabolic pathway reconstruction

    PubMed Central

    Tabei, Yasuo; Yamanishi, Yoshihiro; Kotera, Masaaki

    2016-01-01

    Motivation: Metabolic pathways are an important class of molecular networks consisting of compounds, enzymes and their interactions. The understanding of global metabolic pathways is extremely important for various applications in ecology and pharmacology. However, large parts of metabolic pathways remain unknown, and most organism-specific pathways contain many missing enzymes. Results: In this study we propose a novel method to predict the enzyme orthologs that catalyze the putative reactions to facilitate the de novo reconstruction of metabolic pathways from metabolome-scale compound sets. The algorithm detects the chemical transformation patterns of substrate–product pairs using chemical graph alignments, and constructs a set of enzyme-specific classifiers to simultaneously predict all the enzyme orthologs that could catalyze the putative reactions of the substrate–product pairs in the joint learning framework. The originality of the method lies in its ability to make predictions for thousands of enzyme orthologs simultaneously, as well as its extraction of enzyme-specific chemical transformation patterns of substrate–product pairs. We demonstrate the usefulness of the proposed method by applying it to some ten thousands of metabolic compounds, and analyze the extracted chemical transformation patterns that provide insights into the characteristics and specificities of enzymes. The proposed method will open the door to both primary (central) and secondary metabolism in genomics research, increasing research productivity to tackle a wide variety of environmental and public health matters. Availability and Implementation: Contact: maskot@bio.titech.ac.jp PMID:27307627

  10. Essential Set of Molecular Descriptors for ADME Prediction in Drug and Environmental Chemical Space

    EPA Science Inventory

    Historically, the disciplines of pharmacology and toxicology have embraced quantitative structure-activity relationships (QSAR) and quantitative structure-property relationships (QSPR) to predict ADME properties or biological activities of untested chemicals. The question arises ...

  11. Fragment-based {sup 13}C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hartman, Joshua D.; Beran, Gregory J. O., E-mail: gregory.beran@ucr.edu; Monaco, Stephen

    2015-09-14

    We assess the quality of fragment-based ab initio isotropic {sup 13}C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic {sup 13}C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readilymore » in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.« less

  12. Chemical production in electrocautery smoke by a novel predictive model.

    PubMed

    Wu, Y-C; Tang, C-S; Huang, H-Y; Liu, C-H; Chen, Y-L; Chen, D-R; Lin, Y-W

    2011-01-01

    The hazards of electrocautery smoke have been known for decades. However, few clinical studies have been conducted to analyze the responsible variables of the smoke production. This study collected clinical smoke samples and systematically analyzed all possible factors. Thirty diathermy smoke samples were collected during mastectomy and abdominal cavity operations. Samples were analyzed using a gas chromatographer with a flame ionization detector. Data were applied to construct prediction models for chemical production from electrosurgeries to identify all possible factors that impact chemical production during electrosurgery. Toluene was detected in 27 smoke samples (90%) with concentrations of 0.003-0.463 mg/m(3) and production of 176.0-2,780.0 ng. Ethyl benzene and styrene were identified in very few cases. General linear regression analysis demonstrates that surgery type, patient age, electrocautery duration and imparted coagulation energy explained 67.63% of the variation in toluene production. Surgery type and patient age are known prior to surgery. In terms of risk precaution, the operating team should pay close attention to exposure when certain positive factors of increasing the chemical production are known in advance. Copyright © 2011 S. Karger AG, Basel.

  13. Testing predictions of the quantum landscape multiverse 1: the Starobinsky inflationary potential

    NASA Astrophysics Data System (ADS)

    Di Valentino, Eleonora; Mersini-Houghton, Laura

    2017-03-01

    The 2015 Planck data release has placed tight constraints on the allowed class of inflationary models. The current data favors concave downwards inflationary potentials while offering interesting hints on possible deviations from the standard picture of CMB perturbations. We here test the predictions of the theory of the origin of the universe from the landscape multiverse, against the most recent Planck data, for the case of concave downwards inflationary potentials, such as the Starobinsky model of inflation. By considering the quantum entanglement correction of the multiverse, we can place a lower limit on the local `SUSY breaking' scale b > 1.2 × 107 GeV at 95% c.l. from Planck TT+lowTEB. We find that this limit is consistent with the range for b that allows the landscape multiverse to explain a serie of anomalies present in the current data.

  14. Old Wine in New Bottles: Quantum Theory in Historical Perspective.

    ERIC Educational Resources Information Center

    Bent, Henry A.

    1984-01-01

    Discusses similarities between chemistry and three central concepts of quantum physics: (1) stationary states; (2) wave functions; and (3) complementarity. Based on these and other similarities, it is indicated that quantum physics is a chemical physics. (JN)

  15. Nonlinear absorption in AlGaAs/GaAs multiple quantum well structures grown by metalorganic chemical vapor deposition

    NASA Technical Reports Server (NTRS)

    Lee, H. C.; Hariz, A.; Dapkus, P. D.; Kost, A.; Kawase, M.

    1987-01-01

    This paper reports the study of growth conditions for achieving the sharp exciton resonances and low-intensity saturation of these resonances in AlGaAs-GaAs multiple quantum well structures grown by metalorganic chemical vapor deposition. Low growth temperature is necessary to observe this sharp resonance feature at room temperature. The optimal growth conditions are a tradeoff between the high temperatures required for high quality AlGaAs and low temperatures required for high-purity GaAs. A strong optical saturation of the excitonic absorption has been observed. A saturation density as low as 250 W/sq cm is reported.

  16. Parameters for the RM1 Quantum Chemical Calculation of Complexes of the Trications of Thulium, Ytterbium and Lutetium

    PubMed Central

    Filho, Manoel A. M.; Dutra, José Diogo L.; Rocha, Gerd B.; Simas, Alfredo M.

    2016-01-01

    The RM1 quantum chemical model for the calculation of complexes of Tm(III), Yb(III) and Lu(III) is advanced. Subsequently, we tested the models by fully optimizing the geometries of 126 complexes. We then compared the optimized structures with known crystallographic ones from the Cambridge Structural Database. Results indicate that, for thulium complexes, the accuracy in terms of the distances between the lanthanide ion and its directly coordinated atoms is about 2%. Corresponding results for ytterbium and lutetium are both 3%, levels of accuracy useful for the design of lanthanide complexes, targeting their countless applications. PMID:27223475

  17. Zinc sulfide quantum dots for photocatalytic and sensing applications

    NASA Astrophysics Data System (ADS)

    Sergeev, Alexander A.; Leonov, Andrei A.; Zhuikova, Elena I.; Postnova, Irina V.; Voznesenskiy, Sergey S.

    2017-09-01

    Herein, we report the photocatalytic and sensing applications of pure and Mn-doped ZnS quantum dots. The quantum dots were prepared by a chemical precipitation in an aqueous solution in the presence of glutathione as a stabilizing agent. The synthesized quantum dots were used as effective photocatalyst for the degradation of methylene blue dye. Interestingly, fully degradation of methylene blue dye was achieved in 5 min using pure ZnS quantum dots. Further, the synthesized quantum dots were used as efficient sensing element for methane fluorescent sensor. Interfering studies confirmed that the developed sensor possesses very good sensitivity and selectivity towards methane.

  18. High-Throughput Predictive Approaches to Evaluating Chemicals in Food Contact Materials: Migration, Exposure, and Alternatives Identification

    EPA Science Inventory

    This is a presentation describing CSS research on HT predictive methods to modeling exposure and predicting functional substitutes. It will be presented at a forum co-sponsored by the State of California and UC Berekeley on evaluation of chemical alternatives for food contact ch...

  19. Path Integrals for Electronic Densities, Reactivity Indices, and Localization Functions in Quantum Systems

    PubMed Central

    Putz, Mihai V.

    2009-01-01

    The density matrix theory, the ancestor of density functional theory, provides the immediate framework for Path Integral (PI) development, allowing the canonical density be extended for the many-electronic systems through the density functional closure relationship. Yet, the use of path integral formalism for electronic density prescription presents several advantages: assures the inner quantum mechanical description of the system by parameterized paths; averages the quantum fluctuations; behaves as the propagator for time-space evolution of quantum information; resembles Schrödinger equation; allows quantum statistical description of the system through partition function computing. In this framework, four levels of path integral formalism were presented: the Feynman quantum mechanical, the semiclassical, the Feynman-Kleinert effective classical, and the Fokker-Planck non-equilibrium ones. In each case the density matrix or/and the canonical density were rigorously defined and presented. The practical specializations for quantum free and harmonic motions, for statistical high and low temperature limits, the smearing justification for the Bohr’s quantum stability postulate with the paradigmatic Hydrogen atomic excursion, along the quantum chemical calculation of semiclassical electronegativity and hardness, of chemical action and Mulliken electronegativity, as well as by the Markovian generalizations of Becke-Edgecombe electronic focalization functions – all advocate for the reliability of assuming PI formalism of quantum mechanics as a versatile one, suited for analytically and/or computationally modeling of a variety of fundamental physical and chemical reactivity concepts characterizing the (density driving) many-electronic systems. PMID:20087467

  20. Path integrals for electronic densities, reactivity indices, and localization functions in quantum systems.

    PubMed

    Putz, Mihai V

    2009-11-10

    The density matrix theory, the ancestor of density functional theory, provides the immediate framework for Path Integral (PI) development, allowing the canonical density be extended for the many-electronic systems through the density functional closure relationship. Yet, the use of path integral formalism for electronic density prescription presents several advantages: assures the inner quantum mechanical description of the system by parameterized paths; averages the quantum fluctuations; behaves as the propagator for time-space evolution of quantum information; resembles Schrödinger equation; allows quantum statistical description of the system through partition function computing. In this framework, four levels of path integral formalism were presented: the Feynman quantum mechanical, the semiclassical, the Feynman-Kleinert effective classical, and the Fokker-Planck non-equilibrium ones. In each case the density matrix or/and the canonical density were rigorously defined and presented. The practical specializations for quantum free and harmonic motions, for statistical high and low temperature limits, the smearing justification for the Bohr's quantum stability postulate with the paradigmatic Hydrogen atomic excursion, along the quantum chemical calculation of semiclassical electronegativity and hardness, of chemical action and Mulliken electronegativity, as well as by the Markovian generalizations of Becke-Edgecombe electronic focalization functions - all advocate for the reliability of assuming PI formalism of quantum mechanics as a versatile one, suited for analytically and/or computationally modeling of a variety of fundamental physical and chemical reactivity concepts characterizing the (density driving) many-electronic systems.

  1. Remote explosive and chemical agent detection using broadly tunable mid-infrared external cavity quantum cascade lasers

    NASA Astrophysics Data System (ADS)

    Rayner, Timothy; Weida, Miles; Pushkarsky, Michael; Day, Timothy

    2007-04-01

    Terrorists both with IEDs and suicide bombers are targeting civilian infrastructures such as transportation systems. Although explosive detection technologies exist and are used effectively in aviation, these technologies do not lend themselves well to protecting open architecture soft targets, as they are focused on a checkpoint form factor that limits throughput. However, remote detection of explosives and other chemicals would enable these kinds of targets to be protected without interrupting the flow of commerce. Tunable mid-IR laser technology offers the opportunity to detect explosives and other chemicals remotely and quickly. Most chemical compounds, including explosives, have their fundamental vibrational modes in the mid-infrared region (3 to 15μm). There are a variety of techniques that focus on examining interactions that have proven effective in the laboratory but could never work in the field due to complexity, size, reliability and cost. Daylight Solutions has solved these problems by integrating quantum cascade gain media into external tunable cavities. This has resulted in miniaturized, broadly tunable mid-IR laser sources. The laser sources have a capability to tune to +/- 5% of their center wavelength, which means they can sweep through an entire absorption spectrum to ensure very good detection and false alarm performance compared with fixed wavelength devices. These devices are also highly portable, operate at room temperature, and generate 10's to 100's of mW in optical power, in pulsed and continuous wave configurations. Daylight Solutions is in the process of developing a variety of standoff explosive and chemical weapon detection systems using this technology.

  2. Quantum chemical calculations in the structural analysis of phloretin

    NASA Astrophysics Data System (ADS)

    Gómez-Zavaglia, Andrea

    2009-07-01

    In this work, a conformational search on the molecule of phloretin [2',4',6'-Trihydroxy-3-(4-hydroxyphenyl)-propiophenone] has been performed. The molecule of phloretin has eight dihedral angles, four of them taking part in the carbon backbone and the other four, related with the orientation of the hydroxyl groups. A systematic search involving a random variation of the dihedral angles has been used to generate input structures for the quantum chemical calculations. Calculations at the DFT(B3LYP)/6-311++G(d,p) level of theory permitted the identification of 58 local minima belonging to the C 1 symmetry point group. The molecular structures of the conformers have been analyzed using hierarchical cluster analysis. This method allowed us to group conformers according to their similarities, and thus, to correlate the conformers' stability with structural parameters. The dendrogram obtained from the hierarchical cluster analysis depicted two main clusters. Cluster I included all the conformers with relative energies lower than 25 kJ mol -1 and cluster II, the remaining conformers. The possibility of forming intramolecular hydrogen bonds resulted the main factor contributing for the stability. Accordingly, all conformers depicting intramolecular H-bonds belong to cluster I. These conformations are clearly favored when the carbon backbone is as planar as possible. The values of the νC dbnd O and νOH vibrational modes were compared among all the conformers of phloretin. The redshifts associated with intramolecular H-bonds were correlated with the H-bonds distances and energies.

  3. Ab initio quantum chemistry: methodology and applications.

    PubMed

    Friesner, Richard A

    2005-05-10

    This Perspective provides an overview of state-of-the-art ab initio quantum chemical methodology and applications. The methods that are discussed include coupled cluster theory, localized second-order Moller-Plesset perturbation theory, multireference perturbation approaches, and density functional theory. The accuracy of each approach for key chemical properties is summarized, and the computational performance is analyzed, emphasizing significant advances in algorithms and implementation over the past decade. Incorporation of a condensed-phase environment by means of mixed quantum mechanical/molecular mechanics or self-consistent reaction field techniques, is presented. A wide range of illustrative applications, focusing on materials science and biology, are discussed briefly.

  4. Species-Specific Predictive Signatures of Developmental Toxicity Using the ToxCast Chemical Library

    EPA Science Inventory

    EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive signatures that correlate with observed in vivo toxicity. In vitro profiling methods from ToxCast data consist of over 600 high-throughput screening (HTS) and high-content screening ...

  5. Evaluation of in silico tools to predict the skin sensitization potential of chemicals.

    PubMed

    Verheyen, G R; Braeken, E; Van Deun, K; Van Miert, S

    2017-01-01

    Public domain and commercial in silico tools were compared for their performance in predicting the skin sensitization potential of chemicals. The packages were either statistical based (Vega, CASE Ultra) or rule based (OECD Toolbox, Toxtree, Derek Nexus). In practice, several of these in silico tools are used in gap filling and read-across, but here their use was limited to make predictions based on presence/absence of structural features associated to sensitization. The top 400 ranking substances of the ATSDR 2011 Priority List of Hazardous Substances were selected as a starting point. Experimental information was identified for 160 chemically diverse substances (82 positive and 78 negative). The prediction for skin sensitization potential was compared with the experimental data. Rule-based tools perform slightly better, with accuracies ranging from 0.6 (OECD Toolbox) to 0.78 (Derek Nexus), compared with statistical tools that had accuracies ranging from 0.48 (Vega) to 0.73 (CASE Ultra - LLNA weak model). Combining models increased the performance, with positive and negative predictive values up to 80% and 84%, respectively. However, the number of substances that were predicted positive or negative for skin sensitization in both models was low. Adding more substances to the dataset will increase the confidence in the conclusions reached. The insights obtained in this evaluation are incorporated in a web database www.asopus.weebly.com that provides a potential end user context for the scope and performance of different in silico tools with respect to a common dataset of curated skin sensitization data.

  6. Quantum Effects in Biology

    NASA Astrophysics Data System (ADS)

    Mohseni, Masoud; Omar, Yasser; Engel, Gregory S.; Plenio, Martin B.

    2014-08-01

    List of contributors; Preface; Part I. Introduction: 1. Quantum biology: introduction Graham R. Fleming and Gregory D. Scholes; 2. Open quantum system approaches to biological systems Alireza Shabani, Masoud Mohseni, Seogjoo Jang, Akihito Ishizaki, Martin Plenio, Patrick Rebentrost, Alàn Aspuru-Guzik, Jianshu Cao, Seth Lloyd and Robert Silbey; 3. Generalized Förster resonance energy transfer Seogjoo Jang, Hoda Hossein-Nejad and Gregory D. Scholes; 4. Multidimensional electronic spectroscopy Tomáš Mančal; Part II. Quantum Effects in Bacterial Photosynthetic Energy Transfer: 5. Structure, function, and quantum dynamics of pigment protein complexes Ioan Kosztin and Klaus Schulten; 6. Direct observation of quantum coherence Gregory S. Engel; 7. Environment-assisted quantum transport Masoud Mohseni, Alàn Aspuru-Guzik, Patrick Rebentrost, Alireza Shabani, Seth Lloyd, Susana F. Huelga and Martin B. Plenio; Part III. Quantum Effects in Higher Organisms and Applications: 8. Excitation energy transfer in higher plants Elisabet Romero, Vladimir I. Novoderezhkin and Rienk van Grondelle; 9. Electron transfer in proteins Spiros S. Skourtis; 10. A chemical compass for bird navigation Ilia A. Solov'yov, Thorsten Ritz, Klaus Schulten and Peter J. Hore; 11. Quantum biology of retinal Klaus Schulten and Shigehiko Hayashi; 12. Quantum vibrational effects on sense of smell A. M. Stoneham, L. Turin, J. C. Brookes and A. P. Horsfield; 13. A perspective on possible manifestations of entanglement in biological systems Hans J. Briegel and Sandu Popescu; 14. Design and applications of bio-inspired quantum materials Mohan Sarovar, Dörthe M. Eisele and K. Birgitta Whaley; 15. Coherent excitons in carbon nanotubes Leonas Valkunas and Darius Abramavicius; Glossary; References; Index.

  7. Prediction of the effect of formulation on the toxicity of chemicals.

    PubMed

    Mistry, Pritesh; Neagu, Daniel; Sanchez-Ruiz, Antonio; Trundle, Paul R; Vessey, Jonathan D; Gosling, John Paul

    2017-01-01

    Two approaches for the prediction of which of two vehicles will result in lower toxicity for anticancer agents are presented. Machine-learning models are developed using decision tree, random forest and partial least squares methodologies and statistical evidence is presented to demonstrate that they represent valid models. Separately, a clustering method is presented that allows the ordering of vehicles by the toxicity they show for chemically-related compounds.

  8. Studies of quantum dots in the quantum Hall regime

    NASA Astrophysics Data System (ADS)

    Goldmann, Eyal

    We present two studies of quantum dots in the quantum Hall regime. In the first study, presented in Chapter 3, we investigate the edge reconstruction phenomenon believed to occur when the quantum dot filling fraction is n≲1 . Our approach involves the examination of large dots (≤40 electrons) using a partial diagonalization technique in which the occupancies of the deep interior orbitals are frozen. To interpret the results of this calculation, we evaluate the overlap between the diagonalized ground state and a set of trial wavefunctions which we call projected necklace (PN) states. A PN state is simply the angular momentum projection of a maximum density droplet surrounded by a ring of localized electrons. Our calculations reveal that PN states have up to 99% overlap with the diagonalized ground states, and are lower in energy than the states identified in Chamon and Wen's study of the edge reconstruction. In the second study, presented in Chapter 4, we investigate quantum dots in the fractional quantum Hall regime using a Hartree formulation of composite fermion theory. We find that under appropriate conditions, the chemical potential of the dots oscillates periodically with B due to the transfer of composite fermions between quasi-Landau bands. This effect is analogous the addition spectrum oscillations which occur in quantum dots in the integer quantum Hall regime. Period f0 oscillations are found in sharply confined dots with filling factors nu = 2/5 and nu = 2/3. Period 3 f0 oscillations are found in a parabolically confined nu = 2/5 dot. More generally, we argue that the oscillation period of dots with band pinning should vary continuously with B, whereas the period of dots without band pinning is f0 .

  9. Electrostatic thin film chemical and biological sensor

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Prelas, Mark A.; Ghosh, Tushar K.; Tompson, Jr., Robert V.

    A chemical and biological agent sensor includes an electrostatic thin film supported by a substrate. The film includes an electrostatic charged surface to attract predetermined biological and chemical agents of interest. A charge collector associated with said electrostatic thin film collects charge associated with surface defects in the electrostatic film induced by the predetermined biological and chemical agents of interest. A preferred sensing system includes a charge based deep level transient spectroscopy system to read out charges from the film and match responses to data sets regarding the agents of interest. A method for sensing biological and chemical agents includesmore » providing a thin sensing film having a predetermined electrostatic charge. The film is exposed to an environment suspected of containing the biological and chemical agents. Quantum surface effects on the film are measured. Biological and/or chemical agents can be detected, identified and quantified based on the measured quantum surface effects.« less

  10. Design strategy for terahertz quantum dot cascade lasers.

    PubMed

    Burnett, Benjamin A; Williams, Benjamin S

    2016-10-31

    The development of quantum dot cascade lasers has been proposed as a path to obtain terahertz semiconductor lasers that operate at room temperature. The expected benefit is due to the suppression of nonradiative electron-phonon scattering and reduced dephasing that accompanies discretization of the electronic energy spectrum. We present numerical modeling which predicts that simple scaling of conventional quantum well based designs to the quantum dot regime will likely fail due to electrical instability associated with high-field domain formation. A design strategy adapted for terahertz quantum dot cascade lasers is presented which avoids these problems. Counterintuitively, this involves the resonant depopulation of the laser's upper state with the LO-phonon energy. The strategy is tested theoretically using a density matrix model of transport and gain, which predicts sufficient gain for lasing at stable operating points. Finally, the effect of quantum dot size inhomogeneity on the optical lineshape is explored, suggesting that the design concept is robust to a moderate amount of statistical variation.

  11. Coherent control of diamond defects for quantum information science and quantum sensing

    NASA Astrophysics Data System (ADS)

    Maurer, Peter

    . This opens the door for the engineering of nano-scaled chemical reactions to the study of temperature dependent biological processes. Finally, a novel technique is introduced that facilitates optical spin detection with nanoscale resolution based on an optical far-field technique; by combining this with a 'quantum Zeno' like effect coherent manipulation of nominally identical spins at a nanoscale is achieved.

  12. Species-specific predictive models of developmental toxicity using the ToxCast chemical library

    EPA Science Inventory

    EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive models that correlate with observed in vivo toxicity. In vitro profiling methods are based on ToxCast data, consisting of over 600 high-throughput screening (HTS) and high-content sc...

  13. The furan microsolvation blind challenge for quantum chemical methods: First steps

    NASA Astrophysics Data System (ADS)

    Gottschalk, Hannes C.; Poblotzki, Anja; Suhm, Martin A.; Al-Mogren, Muneerah M.; Antony, Jens; Auer, Alexander A.; Baptista, Leonardo; Benoit, David M.; Bistoni, Giovanni; Bohle, Fabian; Dahmani, Rahma; Firaha, Dzmitry; Grimme, Stefan; Hansen, Andreas; Harding, Michael E.; Hochlaf, Majdi; Holzer, Christof; Jansen, Georg; Klopper, Wim; Kopp, Wassja A.; Kröger, Leif C.; Leonhard, Kai; Mouhib, Halima; Neese, Frank; Pereira, Max N.; Ulusoy, Inga S.; Wuttke, Axel; Mata, Ricardo A.

    2018-01-01

    Herein we present the results of a blind challenge to quantum chemical methods in the calculation of dimerization preferences in the low temperature gas phase. The target of study was the first step of the microsolvation of furan, 2-methylfuran and 2,5-dimethylfuran with methanol. The dimers were investigated through IR spectroscopy of a supersonic jet expansion. From the measured bands, it was possible to identify a persistent hydrogen bonding OH-O motif in the predominant species. From the presence of another band, which can be attributed to an OH-π interaction, we were able to assert that the energy gap between the two types of dimers should be less than or close to 1 kJ/mol across the series. These values served as a first evaluation ruler for the 12 entries featured in the challenge. A tentative stricter evaluation of the challenge results is also carried out, combining theoretical and experimental results in order to define a smaller error bar. The process was carried out in a double-blind fashion, with both theory and experimental groups unaware of the results on the other side, with the exception of the 2,5-dimethylfuran system which was featured in an earlier publication.

  14. Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties.

    PubMed

    Yue, Zhenyu; Zhang, Wenna; Lu, Yongming; Yang, Qiaoyue; Ding, Qiuying; Xia, Junfeng; Chen, Yan

    2015-01-01

    Natural products play a significant role in cancer chemotherapy. They are likely to provide many lead structures, which can be used as templates for the construction of novel drugs with enhanced antitumor activity. Traditional research approaches studied structure-activity relationship of natural products and obtained key structural properties, such as chemical bond or group, with the purpose of ascertaining their effect on a single cell line or a single tissue type. Here, for the first time, we develop a machine learning method to comprehensively predict natural products responses against a panel of cancer cell lines based on both the gene expression and the chemical properties of natural products. The results on two datasets, training set and independent test set, show that this proposed method yields significantly better prediction accuracy. In addition, we also demonstrate the predictive power of our proposed method by modeling the cancer cell sensitivity to two natural products, Curcumin and Resveratrol, which indicate that our method can effectively predict the response of cancer cell lines to these two natural products. Taken together, the method will facilitate the identification of natural products as cancer therapies and the development of precision medicine by linking the features of patient genomes to natural product sensitivity.

  15. Weak Measurement and Quantum Smoothing of a Superconducting Qubit

    NASA Astrophysics Data System (ADS)

    Tan, Dian

    In quantum mechanics, the measurement outcome of an observable in a quantum system is intrinsically random, yielding a probability distribution. The state of the quantum system can be described by a density matrix rho(t), which depends on the information accumulated until time t, and represents our knowledge about the system. The density matrix rho(t) gives probabilities for the outcomes of measurements at time t. Further probing of the quantum system allows us to refine our prediction in hindsight. In this thesis, we experimentally examine a quantum smoothing theory in a superconducting qubit by introducing an auxiliary matrix E(t) which is conditioned on information obtained from time t to a final time T. With the complete information before and after time t, the pair of matrices [rho(t), E(t)] can be used to make smoothed predictions for the measurement outcome at time t. We apply the quantum smoothing theory in the case of continuous weak measurement unveiling the retrodicted quantum trajectories and weak values. In the case of strong projective measurement, while the density matrix rho(t) with only diagonal elements in a given basis |n〉 may be treated as a classical mixture, we demonstrate a failure of this classical mixture description in determining the smoothed probabilities for the measurement outcome at time t with both diagonal rho(t) and diagonal E(t). We study the correlations between quantum states and weak measurement signals and examine aspects of the time symmetry of continuous quantum measurement. We also extend our study of quantum smoothing theory to the case of resonance fluorescence of a superconducting qubit with homodyne measurement and observe some interesting effects such as the modification of the excited state probabilities, weak values, and evolution of the predicted and retrodicted trajectories.

  16. Quantum entanglement of angular momentum states with quantum numbers up to 10,010

    PubMed Central

    Fickler, Robert; Campbell, Geoff; Buchler, Ben; Lam, Ping Koy; Zeilinger, Anton

    2016-01-01

    Photons with a twisted phase front carry a quantized amount of orbital angular momentum (OAM) and have become important in various fields of optics, such as quantum and classical information science or optical tweezers. Because no upper limit on the OAM content per photon is known, they are also interesting systems to experimentally challenge quantum mechanical prediction for high quantum numbers. Here, we take advantage of a recently developed technique to imprint unprecedented high values of OAM, namely spiral phase mirrors, to generate photons with more than 10,000 quanta of OAM. Moreover, we demonstrate quantum entanglement between these large OAM quanta of one photon and the polarization of its partner photon. To our knowledge, this corresponds to entanglement with the largest quantum number that has been demonstrated in an experiment. The results may also open novel ways to couple single photons to massive objects, enhance angular resolution, and highlight OAM as a promising way to increase the information capacity of a single photon. PMID:27856742

  17. Quantum entanglement of angular momentum states with quantum numbers up to 10,010

    NASA Astrophysics Data System (ADS)

    Fickler, Robert; Campbell, Geoff; Buchler, Ben; Lam, Ping Koy; Zeilinger, Anton

    2016-11-01

    Photons with a twisted phase front carry a quantized amount of orbital angular momentum (OAM) and have become important in various fields of optics, such as quantum and classical information science or optical tweezers. Because no upper limit on the OAM content per photon is known, they are also interesting systems to experimentally challenge quantum mechanical prediction for high quantum numbers. Here, we take advantage of a recently developed technique to imprint unprecedented high values of OAM, namely spiral phase mirrors, to generate photons with more than 10,000 quanta of OAM. Moreover, we demonstrate quantum entanglement between these large OAM quanta of one photon and the polarization of its partner photon. To our knowledge, this corresponds to entanglement with the largest quantum number that has been demonstrated in an experiment. The results may also open novel ways to couple single photons to massive objects, enhance angular resolution, and highlight OAM as a promising way to increase the information capacity of a single photon.

  18. Quantum entanglement of angular momentum states with quantum numbers up to 10,010.

    PubMed

    Fickler, Robert; Campbell, Geoff; Buchler, Ben; Lam, Ping Koy; Zeilinger, Anton

    2016-11-29

    Photons with a twisted phase front carry a quantized amount of orbital angular momentum (OAM) and have become important in various fields of optics, such as quantum and classical information science or optical tweezers. Because no upper limit on the OAM content per photon is known, they are also interesting systems to experimentally challenge quantum mechanical prediction for high quantum numbers. Here, we take advantage of a recently developed technique to imprint unprecedented high values of OAM, namely spiral phase mirrors, to generate photons with more than 10,000 quanta of OAM. Moreover, we demonstrate quantum entanglement between these large OAM quanta of one photon and the polarization of its partner photon. To our knowledge, this corresponds to entanglement with the largest quantum number that has been demonstrated in an experiment. The results may also open novel ways to couple single photons to massive objects, enhance angular resolution, and highlight OAM as a promising way to increase the information capacity of a single photon.

  19. Measuring the excitations in a new S  =  1/2 quantum spin chain material with competing interactions

    NASA Astrophysics Data System (ADS)

    Rule, K. C.; Mole, R. A.; Zanardo, J.; Krause-Heuer, A.; Darwish, T.; Lerch, M.; Yu, D.

    2018-05-01

    Recently a new one-dimensional (1D) quantum spin chain system has been reported: catena-dichloro(2-Cl-3Mpy)copper(II), (where 2-Cl-3Mpy=2-chloro-3-methylpyridine). Preliminary calculations and bulk magnetic property measurements indicate that this system does not undergo magnetic ordering down to 1.8 K and is a prime candidate for investigating frustration in a J 1/J 2 system (where the nearest neighbour interactions, J 1, are ferromagnetic and the next nearest neighbour interactions, J 2, are antiferromagnetic). Calculations predicted three possible magnetic interaction strengths for J 1 below 6 meV depending on the orientation of the ligand. For one of the predicted J 1 values, the existence of a quantum critical point is implied. A deuterated sample of catena-dichloro(2-Cl-3Mpy)copper(II) was synthesised and the excitations measured using inelastic neutron scattering. Scattering indicated the most likely scenario involves spin-chains where each chain consists of only one of the three possible magnetic excitations in this material, rather than the completely random array of exchange interactions within each chain as predicted by Herringer et al (2014 Chem. Eur. J. 20 8355–62). This indicates the possibility of tuning the chemical structure to favour a system which may exhibit a quantum critical point.

  20. Measuring the excitations in a new S  =  1/2 quantum spin chain material with competing interactions.

    PubMed

    Rule, K C; Mole, R A; Zanardo, J; Krause-Heuer, A; Darwish, T; Lerch, M; Yu, D

    2018-05-31

    Recently a new one-dimensional (1D) quantum spin chain system has been reported: catena-dichloro(2-Cl-3Mpy)copper(II), (where 2-Cl-3Mpy=2-chloro-3-methylpyridine). Preliminary calculations and bulk magnetic property measurements indicate that this system does not undergo magnetic ordering down to 1.8 K and is a prime candidate for investigating frustration in a J 1 /J 2 system (where the nearest neighbour interactions, J 1 , are ferromagnetic and the next nearest neighbour interactions, J 2 , are antiferromagnetic). Calculations predicted three possible magnetic interaction strengths for J 1 below 6 meV depending on the orientation of the ligand. For one of the predicted J 1 values, the existence of a quantum critical point is implied. A deuterated sample of catena-dichloro(2-Cl-3Mpy)copper(II) was synthesised and the excitations measured using inelastic neutron scattering. Scattering indicated the most likely scenario involves spin-chains where each chain consists of only one of the three possible magnetic excitations in this material, rather than the completely random array of exchange interactions within each chain as predicted by Herringer et al (2014 Chem. Eur. J. 20 8355-62). This indicates the possibility of tuning the chemical structure to favour a system which may exhibit a quantum critical point.