Drug Release Kinetics and Transport Mechanisms of Non-degradable and Degradable Polymeric Delivery Systems

PubMed Central

Fu, Yao; Kao, Weiyuan John

2010-01-01

Importance of the field The advancement in material design and engineering has led to the rapid development of novel materials with increasing complexity and functions. Both non-degradable and degradable polymers have found wide applications in the controlled delivery field. Studies on drug release kinetics provide important information into the function of material systems. To elucidate the detailed transport mechanism and the structure-function relationship of a material system, it is critical to bridge the gap between the macroscopic data and the transport behavior at the molecular level. Areas covered in this review The structure and function information of selected non-degradable and degradable polymers have been collected and summarized from literatures published after 1990s. The release kinetics of selected drug compounds from various material systems will be discussed in case studies. Recent progresses in the mathematical models based on different transport mechanisms will be highlighted. What the reader will gain This article aims to provide an overview of structure-function relationships of selected non-degradable and degradable polymers as drug delivery matrices. Take home message Understanding the structure-function relationship of the material system is key to the successful design of a delivery system for a particular application. Moreover, developing complex polymeric matrices requires more robust mathematical models to elucidate the solute transport mechanisms. PMID:20331353

Higher-Order Theory for Functionally Graded Materials

NASA Technical Reports Server (NTRS)

Aboudi, J.; Pindera, M. J.; Arnold, Steven M.

2001-01-01

Functionally graded materials (FGM's) are a new generation of engineered materials wherein the microstructural details are spatially varied through nonuniform distribution of the reinforcement phase(s). Engineers accomplish this by using reinforcements with different properties, sizes, and shapes, as well as by interchanging the roles of the reinforcement and matrix phases in a continuous manner (ref. 1). The result is a microstructure that produces continuously or discretely changing thermal and mechanical properties at the macroscopic or continuum scale. This new concept of engineering the material's microstructure marks the beginning of a revolution both in the materials science and mechanics of materials areas since it allows one, for the first time, to fully integrate the material and structural considerations into the final design of structural components. Functionally graded materials are ideal candidates for applications involving severe thermal gradients, ranging from thermal structures in advanced aircraft and aerospace engines to computer circuit boards. Owing to the many variables that control the design of functionally graded microstructures, full exploitation of the FGM's potential requires the development of appropriate modeling strategies for their response to combined thermomechanical loads. Previously, most computational strategies for the response of FGM's did not explicitly couple the material's heterogeneous microstructure with the structural global analysis. Rather, local effective or macroscopic properties at a given point within the FGM were first obtained through homogenization based on a chosen micromechanics scheme and then subsequently used in a global thermomechanical analysis.

Nature-Inspired Structural Materials for Flexible Electronic Devices.

PubMed

Liu, Yaqing; He, Ke; Chen, Geng; Leow, Wan Ru; Chen, Xiaodong

2017-10-25

Exciting advancements have been made in the field of flexible electronic devices in the last two decades and will certainly lead to a revolution in peoples' lives in the future. However, because of the poor sustainability of the active materials in complex stress environments, new requirements have been adopted for the construction of flexible devices. Thus, hierarchical architectures in natural materials, which have developed various environment-adapted structures and materials through natural selection, can serve as guides to solve the limitations of materials and engineering techniques. This review covers the smart designs of structural materials inspired by natural materials and their utility in the construction of flexible devices. First, we summarize structural materials that accommodate mechanical deformations, which is the fundamental requirement for flexible devices to work properly in complex environments. Second, we discuss the functionalities of flexible devices induced by nature-inspired structural materials, including mechanical sensing, energy harvesting, physically interacting, and so on. Finally, we provide a perspective on newly developed structural materials and their potential applications in future flexible devices, as well as frontier strategies for biomimetic functions. These analyses and summaries are valuable for a systematic understanding of structural materials in electronic devices and will serve as inspirations for smart designs in flexible electronics.

Advances in Fabrication Materials of Honeycomb Structure Films by the Breath-Figure Method

PubMed Central

Heng, Liping; Wang, Bin; Li, Muchen; Zhang, Yuqi; Jiang, Lei

2013-01-01

Creatures in nature possess almost perfect structures and properties, and exhibit harmonization and unification between structure and function. Biomimetics, mimicking nature for engineering solutions, provides a model for the development of functional surfaces with special properties. Recently, honeycomb structure materials have attracted wide attention for both fundamental research and practical applications and have become an increasingly hot research topic. Though progress in the field of breath-figure formation has been reviewed, the advance in the fabrication materials of bio-inspired honeycomb structure films has not been discussed. Here we review the recent progress of honeycomb structure fabrication materials which were prepared by the breath-figure method. The application of breath figures for the generation of all kinds of honeycomb is discussed. PMID:28809319

Polyphosphazine-based polymer materials

DOEpatents

Fox, Robert V.; Avci, Recep; Groenewold, Gary S.

2010-05-25

Methods of removing contaminant matter from porous materials include applying a polymer material to a contaminated surface, irradiating the contaminated surface to cause redistribution of contaminant matter, and removing at least a portion of the polymer material from the surface. Systems for decontaminating a contaminated structure comprising porous material include a radiation device configured to emit electromagnetic radiation toward a surface of a structure, and at least one spray device configured to apply a capture material onto the surface of the structure. Polymer materials that can be used in such methods and systems include polyphosphazine-based polymer materials having polyphosphazine backbone segments and side chain groups that include selected functional groups. The selected functional groups may include iminos, oximes, carboxylates, sulfonates, .beta.-diketones, phosphine sulfides, phosphates, phosphites, phosphonates, phosphinates, phosphine oxides, monothio phosphinic acids, and dithio phosphinic acids.

From molecular chemistry to hybrid nanomaterials. Design and functionalization.

PubMed

Mehdi, Ahmad; Reye, Catherine; Corriu, Robert

2011-02-01

This tutorial review reports upon the organisation and functionalization of two families of hybrid organic-inorganic materials. We attempted to show in both cases the best ways permitting the organisation of materials in terms of properties at the nanometric scale. The first family concerns mesoporous hybrid organic-inorganic materials prepared in the presence of a structure-directing agent. We describe the functionalization of the channel pores of ordered mesoporous silica, that of the silica framework, as well as the functionalization of both of them simultaneously. This family is currently one of the best supports for exploring polyfunctional materials, which can provide a route to interactive materials. The second family concerns lamellar hybrid organic-inorganic materials which is a new class of nanostructured materials. These materials were first obtained by self-assembly, as a result of van der Waals interactions of bridged organosilica precursors containing long alkylene chains during the sol-gel process, without any structure directing agent. This methodology has been extended to functional materials. It is also shown that such materials can be obtained from monosilylated precursors.

Non-linear Mechanics of Three-dimensional Architected Materials; Design of Soft and Functional Systems and Structures

NASA Astrophysics Data System (ADS)

Babaee, Sahab

In the search for materials with new properties, there have been significant advances in recent years aimed at the construction of architected materials whose behavior is governed by structure, rather than composition. Through careful design of the material's architecture, new mechanical properties have been demonstrated, including negative Poisson's ratio, high stiffness to weight ratio and mechanical cloaking. However, most of the proposed architected materials (also known as mechanical metamaterials) have a unique structure that cannot be recon figured after fabrication, making them suitable only for a specific task. This thesis focuses on the design of architected materials that take advantage of the applied large deformation to enhance their functionality. Mechanical instabilities, which have been traditionally viewed as a failure mode with research focusing on how to avoid them, are exploited to achieve novel and tunable functionalities. In particular I demonstrate the design of mechanical metamaterials with tunable negative Poisson ratio, adaptive phononic band gaps, acoustic switches, and reconfigurable origami-inspired waveguides. Remarkably, due to large deformation capability and full reversibility of soft materials, the responses of the proposed designs are reversible, repeatable, and scale independent. The results presented here pave the way for the design of a new class of soft, active, adaptive, programmable and tunable structures and systems with unprecedented performance and improved functionalities.

An Exploration of Several Structural Measurement Techniques for Usage with Functionally Graded Materials

DTIC Science & Technology

2006-12-01

Welsch, and E.W. Collings, eds. Materials Properties Handbook: Titanium Alloys . ASM International: 1994. p. 179 Davis, Joseph, ed. Properties ...AN EXPLORATION OF SEVERAL STRUCTURAL MEASUREMENT TECHNIQUES FOR USAGE WITH FUNCTIONALLY GRADED...of Defense, or the United States Government. AFIT/GAE/ENY/07-D03 AN EXPLORATION OF SEVERAL STRUCTURAL MEASUREMENT TECHNIQUES FOR USAGE WITH

Correction: Conceptual design of tetraazaporphyrin- and subtetraazaporphyrin-based functional nanocarbon materials: electronic structures, topologies, optical properties, and methane storage capacities.

PubMed

Belosludov, Rodion V; Rhoda, Hannah M; Zhdanov, Ravil K; Belosludov, Vladimir R; Kawazoe, Yoshiyuki; Nemykin, Victor N

2017-08-02

Correction for 'Conceptual design of tetraazaporphyrin- and subtetraazaporphyrin-based functional nanocarbon materials: electronic structures, topologies, optical properties, and methane storage capacities' by Rodion V. Belosludov et al., Phys. Chem. Chem. Phys., 2016, 18, 13503-13518.

Methods for removing contaminant matter from a porous material

DOEpatents

Fox, Robert V [Idaho Falls, ID; Avci, Recep [Bozeman, MT; Groenewold, Gary S [Idaho Falls, ID

2010-11-16

Methods of removing contaminant matter from porous materials include applying a polymer material to a contaminated surface, irradiating the contaminated surface to cause redistribution of contaminant matter, and removing at least a portion of the polymer material from the surface. Systems for decontaminating a contaminated structure comprising porous material include a radiation device configured to emit electromagnetic radiation toward a surface of a structure, and at least one spray device configured to apply a capture material onto the surface of the structure. Polymer materials that can be used in such methods and systems include polyphosphazine-based polymer materials having polyphosphazine backbone segments and side chain groups that include selected functional groups. The selected functional groups may include iminos, oximes, carboxylates, sulfonates, .beta.-diketones, phosphine sulfides, phosphates, phosphites, phosphonates, phosphinates, phosphine oxides, monothio phosphinic acids, and dithio phosphinic acids.

Tailoring vibration mode shapes using topology optimization and functionally graded material concepts

NASA Astrophysics Data System (ADS)

Montealegre Rubio, Wilfredo; Paulino, Glaucio H.; Nelli Silva, Emilio Carlos

2011-02-01

Tailoring specified vibration modes is a requirement for designing piezoelectric devices aimed at dynamic-type applications. A technique for designing the shape of specified vibration modes is the topology optimization method (TOM) which finds an optimum material distribution inside a design domain to obtain a structure that vibrates according to specified eigenfrequencies and eigenmodes. Nevertheless, when the TOM is applied to dynamic problems, the well-known grayscale or intermediate material problem arises which can invalidate the post-processing of the optimal result. Thus, a more natural way for solving dynamic problems using TOM is to allow intermediate material values. This idea leads to the functionally graded material (FGM) concept. In fact, FGMs are materials whose properties and microstructure continuously change along a specific direction. Therefore, in this paper, an approach is presented for tailoring user-defined vibration modes, by applying the TOM and FGM concepts to design functionally graded piezoelectric transducers (FGPT) and non-piezoelectric structures (functionally graded structures—FGS) in order to achieve maximum and/or minimum vibration amplitudes at certain points of the structure, by simultaneously finding the topology and material gradation function. The optimization problem is solved by using sequential linear programming. Two-dimensional results are presented to illustrate the method.

Biphasic DC measurement approach for enhanced measurement stability and multi-channel sampling of self-sensing multi-functional structural materials doped with carbon-based additives

NASA Astrophysics Data System (ADS)

Downey, Austin; D'Alessandro, Antonella; Ubertini, Filippo; Laflamme, Simon; Geiger, Randall

2017-06-01

Investigation of multi-functional carbon-based self-sensing structural materials for structural health monitoring applications is a topic of growing interest. These materials are self-sensing in the sense that they can provide measurable electrical outputs corresponding to physical changes such as strain or induced damage. Nevertheless, the development of an appropriate measurement technique for such materials is yet to be achieved, as many results in the literature suggest that these materials exhibit a drift in their output when measured with direct current (DC) methods. In most of the cases, the electrical output is a resistance and the reported drift is an increase in resistance from the time the measurement starts due to material polarization. Alternating current methods seem more appropriate at eliminating the time drift. However, published results show they are not immune to drift. Moreover, the use of multiple impedance measurement devices (LCR meters) does not allow for the simultaneous multi-channel sampling of multi-sectioned self-sensing materials due to signal crosstalk. The capability to simultaneously monitor multiple sections of self-sensing structural materials is needed to deploy these multi-functional materials for structural health monitoring. Here, a biphasic DC measurement approach with a periodic measure/discharge cycle in the form of a square wave sensing current is used to provide consistent, stable resistance measurements for self-sensing structural materials. DC measurements are made during the measurement region of the square wave while material depolarization is obtained during the discharge region of the periodic signal. The proposed technique is experimentally shown to remove the signal drift in a carbon-based self-sensing cementitious material while providing simultaneous multi-channel measurements of a multi-sectioned self-sensing material. The application of the proposed electrical measurement technique appears promising for real-time utilization of self-sensing materials in structural health monitoring.

Self-assembled materials and supramolecular chemistry within microfluidic environments: from common thermodynamic states to non-equilibrium structures.

PubMed

Sevim, S; Sorrenti, A; Franco, C; Furukawa, S; Pané, S; deMello, A J; Puigmartí-Luis, J

2018-05-01

Self-assembly is a crucial component in the bottom-up fabrication of hierarchical supramolecular structures and advanced functional materials. Control has traditionally relied on the use of encoded building blocks bearing suitable moieties for recognition and interaction, with targeting of the thermodynamic equilibrium state. On the other hand, nature leverages the control of reaction-diffusion processes to create hierarchically organized materials with surprisingly complex biological functions. Indeed, under non-equilibrium conditions (kinetic control), the spatio-temporal command of chemical gradients and reactant mixing during self-assembly (the creation of non-uniform chemical environments for example) can strongly affect the outcome of the self-assembly process. This directly enables a precise control over material properties and functions. In this tutorial review, we show how the unique physical conditions offered by microfluidic technologies can be advantageously used to control the self-assembly of materials and of supramolecular aggregates in solution, making possible the isolation of intermediate states and unprecedented non-equilibrium structures, as well as the emergence of novel functions. Selected examples from the literature will be used to confirm that microfluidic devices are an invaluable toolbox technology for unveiling, understanding and steering self-assembly pathways to desired structures, properties and functions, as well as advanced processing tools for device fabrication and integration.

Granule-by-granule reconstruction of a sandpile from x-ray microtomography data

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

Seidler, G. T.; Martinez, G.; Seeley, L. H.

2000-12-01

Mesoscale disordered materials are ubiquitous in industry and in the environment. Any fundamental understanding of the transport and mechanical properties of such materials must follow from a thorough understanding of their structure. However, in the overwhelming majority of cases, experimental characterization of such materials has been limited to first- and second-order structural correlation functions, i.e., the mean filling fraction and the structural autocorrelation function. We report here the successful combination of synchrotron x-ray microtomography and image processing to determine the full three-dimensional real-space structure of a model disordered material, a granular bed of relatively monodisperse glass spheres. Specifically, we determinemore » the center location and the local connectivity of each granule. This complete knowledge of structure can be used to calculate otherwise inaccessible high-order correlation functions. We analyze nematic order parameters for contact bonds to characterize the geometric anisotropy or fabric induced by the sample boundary conditions. Away from the boundaries we find short-range bond orientational order exhibiting characteristics of the underlying polytetrahedral structure.« less

Photomobile polymer materials with crosslinked liquid-crystalline structures: molecular design, fabrication, and functions.

PubMed

Ube, Toru; Ikeda, Tomiki

2014-09-22

Crosslinked liquid-crystalline polymer materials that macroscopically deform when irradiated with light have been extensively studied in the past decade because of their potential in various applications, such as microactuators and microfluidic devices. The basic motions of these materials are contraction-expansion and bending-unbending, which are observed mainly in polysiloxanes and polyacrylates that contain photochromic moieties. Other sophisticated motions such as twisting, oscillation, rotation, and translational motion have also been achieved. In recent years, efforts have been made to improve the photoresponsive and mechanical properties of this novel class of materials through the modification of molecular structures, development of new fabrication methods, and construction of composite structures. Herein, we review structures, functions, and working mechanisms of photomobile materials and recent advances in this field. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Directed assembly of bio-inspired hierarchical materials with controlled nanofibrillar architectures

NASA Astrophysics Data System (ADS)

Tseng, Peter; Napier, Bradley; Zhao, Siwei; Mitropoulos, Alexander N.; Applegate, Matthew B.; Marelli, Benedetto; Kaplan, David L.; Omenetto, Fiorenzo G.

2017-05-01

In natural systems, directed self-assembly of structural proteins produces complex, hierarchical materials that exhibit a unique combination of mechanical, chemical and transport properties. This controlled process covers dimensions ranging from the nano- to the macroscale. Such materials are desirable to synthesize integrated and adaptive materials and systems. We describe a bio-inspired process to generate hierarchically defined structures with multiscale morphology by using regenerated silk fibroin. The combination of protein self-assembly and microscale mechanical constraints is used to form oriented, porous nanofibrillar networks within predesigned macroscopic structures. This approach allows us to predefine the mechanical and physical properties of these materials, achieved by the definition of gradients in nano- to macroscale order. We fabricate centimetre-scale material geometries including anchors, cables, lattices and webs, as well as functional materials with structure-dependent strength and anisotropic thermal transport. Finally, multiple three-dimensional geometries and doped nanofibrillar constructs are presented to illustrate the facile integration of synthetic and natural additives to form functional, interactive, hierarchical networks.

Predicting the Influence of Nano-Scale Material Structure on the In-Plane Buckling of Orthotropic Plates

NASA Technical Reports Server (NTRS)

Gates, Thomas S.; Odegard, Gregory M.; Nemeth, Michael P.; Frankland, Sarah-Jane V.

2004-01-01

A multi-scale analysis of the structural stability of a carbon nanotube-polymer composite material is developed. The influence of intrinsic molecular structure, such as nanotube length, volume fraction, orientation and chemical functionalization, is investigated by assessing the relative change in critical, in-plane buckling loads. The analysis method relies on elastic properties predicted using the hierarchical, constitutive equations developed from the equivalent-continuum modeling technique applied to the buckling analysis of an orthotropic plate. The results indicate that for the specific composite materials considered in this study, a composite with randomly orientated carbon nanotubes consistently provides the highest values of critical buckling load and that for low volume fraction composites, the non-functionalized nanotube material provides an increase in critical buckling stability with respect to the functionalized system.

Functional materials discovery using energy-structure-function maps

NASA Astrophysics Data System (ADS)

Pulido, Angeles; Chen, Linjiang; Kaczorowski, Tomasz; Holden, Daniel; Little, Marc A.; Chong, Samantha Y.; Slater, Benjamin J.; McMahon, David P.; Bonillo, Baltasar; Stackhouse, Chloe J.; Stephenson, Andrew; Kane, Christopher M.; Clowes, Rob; Hasell, Tom; Cooper, Andrew I.; Day, Graeme M.

2017-03-01

Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy-structure-function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy-structure-function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.

Functional materials discovery using energy-structure-function maps.

PubMed

Pulido, Angeles; Chen, Linjiang; Kaczorowski, Tomasz; Holden, Daniel; Little, Marc A; Chong, Samantha Y; Slater, Benjamin J; McMahon, David P; Bonillo, Baltasar; Stackhouse, Chloe J; Stephenson, Andrew; Kane, Christopher M; Clowes, Rob; Hasell, Tom; Cooper, Andrew I; Day, Graeme M

2017-03-30

Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy-structure-function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy-structure-function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.

Enhanced protective role in materials with gradient structural orientations: Lessons from Nature.

PubMed

Liu, Zengqian; Zhu, Yankun; Jiao, Da; Weng, Zhaoyong; Zhang, Zhefeng; Ritchie, Robert O

2016-10-15

Living organisms are adept at resisting contact deformation and damage by assembling protective surfaces with spatially varied mechanical properties, i.e., by creating functionally graded materials. Such gradients, together with multiple length-scale hierarchical structures, represent the two prime characteristics of many biological materials to be translated into engineering design. Here, we examine one design motif from a variety of biological tissues and materials where site-specific mechanical properties are generated for enhanced protection by adopting gradients in structural orientation over multiple length-scales, without manipulation of composition or microstructural dimension. Quantitative correlations are established between the structural orientations and local mechanical properties, such as stiffness, strength and fracture resistance; based on such gradients, the underlying mechanisms for the enhanced protective role of these materials are clarified. Theoretical analysis is presented and corroborated through numerical simulations of the indentation behavior of composites with distinct orientations. The design strategy of such bioinspired gradients is outlined in terms of the geometry of constituents. This study may offer a feasible approach towards generating functionally graded mechanical properties in synthetic materials for improved contact damage resistance. Living organisms are adept at resisting contact damage by assembling protective surfaces with spatially varied mechanical properties, i.e., by creating functionally-graded materials. Such gradients, together with multiple length-scale hierarchical structures, represent the prime characteristics of many biological materials. Here, we examine one design motif from a variety of biological tissues where site-specific mechanical properties are generated for enhanced protection by adopting gradients in structural orientation at multiple length-scales, without changes in composition or microstructural dimension. The design strategy of such bioinspired gradients is outlined in terms of the geometry of constituents. This study may offer a feasible approach towards generating functionally-graded mechanical properties in synthetic materials for improved damage resistance. Published by Elsevier Ltd.

Final Technical Report for DE-SC0001878 [Theory and Simulation of Defects in Oxide Materials

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

Chelikowsky, James R.

2014-04-14

We explored a wide variety of oxide materials and related problems, including materials at the nanoscale and generic problems associated with oxide materials such as the development of more efficient computational tools to examine these materials. We developed and implemented methods to understand the optical and structural properties of oxides. For ground state properties, our work is predominantly based on pseudopotentials and density functional theory (DFT), including new functionals and going beyond the local density approximation (LDA): LDA+U. To study excited state properties (quasiparticle and optical excitations), we use time dependent density functional theory, the GW approach, and GW plusmore » Bethe-Salpeter equation (GW-BSE) methods based on a many-body Green function approaches. Our work focused on the structural, electronic, optical and magnetic properties of defects (such as oxygen vacancies) in hafnium oxide, titanium oxide (both bulk and clusters) and related materials. We calculated the quasiparticle defect states and charge transition levels of oxygen vacancies in monoclinic hafnia. we presented a milestone G0W0 study of two of the crystalline phases of dye-sensitized TiO{sub 2} clusters. We employed hybrid density functional theory to examine the electronic structure of sexithiophene/ZnO interfaces. To identify the possible effect of epitaxial strain on stabilization of the ferromagnetic state of LaCoO{sub 3} (LCO), we compare the total energy of the magnetic and nonmagnetic states of the strained theoretical bulk structure.« less

Analysis of Thermal Power Generation Capacity for a Skutterudite-Based Thermoelectric Functional Structure

NASA Astrophysics Data System (ADS)

Sun, Yajing; Chen, Gang; Bai, Guanghui; Yang, Xuqiu; Li, Peng; Zhai, Pengcheng

2017-05-01

Due to military or other requirements for hypersonic aircraft, the energy supply devices with the advantages of small size and light weight are urgently needed. Compared with the traditional energy supply method, the skutterudite-based thermoelectric (TE) functional structure is expected to generate electrical energy with a smaller structural space in the hypersonic aircraft. This paper mainly focuses on the responded thermal and electrical characteristics of the skutterudite-based TE functional structure (TEFS) under strong heat flux loads. We conduct TE simulations on the transient model of the TEFS with consideration of the heat flux loads and thermal radiation in the hot end and the cooling effect of the phase change material (PCM) in the cold end. We investigate several influential factors on the power generation capacity, such as the phase transition temperature of the PCM, the heat flux loads, the thickness of the TE materials and the thermal conductivity of the frame materials. The results show that better power generation capacity can be achieved with thicker TE materials, lower phase transition temperature and suitable thermal conductivity of the frame materials.

Density functional calculations on structural materials for nuclear energy applications and functional materials for photovoltaic energy applications (abstract only).

PubMed

Domain, C; Olsson, P; Becquart, C S; Legris, A; Guillemoles, J F

2008-02-13

Ab initio density functional theory calculations are carried out in order to predict the evolution of structural materials under aggressive working conditions such as cases with exposure to corrosion and irradiation, as well as to predict and investigate the properties of functional materials for photovoltaic energy applications. Structural metallic materials used in nuclear facilities are subjected to irradiation which induces the creation of large amounts of point defects. These defects interact with each other as well as with the different elements constituting the alloys, which leads to modifications of the microstructure and the mechanical properties. VASP (Vienna Ab initio Simulation Package) has been used to determine the properties of point defect clusters and also those of extended defects such as dislocations. The resulting quantities, such as interaction energies and migration energies, are used in larger scale simulation methods in order to build predictive tools. For photovoltaic energy applications, ab initio calculations are used in order to search for new semiconductors and possible element substitutions for existing ones in order to improve their efficiency.

Building membrane nanopores

NASA Astrophysics Data System (ADS)

Howorka, Stefan

2017-07-01

Membrane nanopores--hollow nanoscale barrels that puncture biological or synthetic membranes--have become powerful tools in chemical- and biosensing, and have achieved notable success in portable DNA sequencing. The pores can be self-assembled from a variety of materials, including proteins, peptides, synthetic organic compounds and, more recently, DNA. But which building material is best for which application, and what is the relationship between pore structure and function? In this Review, I critically compare the characteristics of the different building materials, and explore the influence of the building material on pore structure, dynamics and function. I also discuss the future challenges of developing nanopore technology, and consider what the next-generation of nanopore structures could be and where further practical applications might emerge.

An unusual type of polymorphism in a liquid crystal

DOE PAGES

Li, Lin; Salamonczyk, Miroslaw; Shadpour, Sasan; ...

2018-02-19

Polymorphism is a remarkable concept in chemistry, materials science, computer science, and biology. Whether it is the ability of a material to exist in two or more crystal structures, a single interface connecting to two different entities, or alternative phenotypes of an organism, polymorphism determines function and properties. In materials science, polymorphism can be found in an impressively wide range of materials, including crystalline materials, minerals, metals, alloys, and polymers. Here in this paper we report on polymorphism in a liquid crystal. A bent-core liquid crystal with a single chiral side chain forms two structurally and morphologically significantly different liquidmore » crystal phases solely depending on the cooling rate from the isotropic liquid state. On slow cooling, the thermodynamically more stable oblique columnar phase forms, and on rapid cooling, a not heretofore reported helical microfilament phase. Since structure determines function and properties, the structural color for these phases also differs.« less

An unusual type of polymorphism in a liquid crystal

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

Li, Lin; Salamonczyk, Miroslaw; Shadpour, Sasan

Polymorphism is a remarkable concept in chemistry, materials science, computer science, and biology. Whether it is the ability of a material to exist in two or more crystal structures, a single interface connecting to two different entities, or alternative phenotypes of an organism, polymorphism determines function and properties. In materials science, polymorphism can be found in an impressively wide range of materials, including crystalline materials, minerals, metals, alloys, and polymers. Here in this paper we report on polymorphism in a liquid crystal. A bent-core liquid crystal with a single chiral side chain forms two structurally and morphologically significantly different liquidmore » crystal phases solely depending on the cooling rate from the isotropic liquid state. On slow cooling, the thermodynamically more stable oblique columnar phase forms, and on rapid cooling, a not heretofore reported helical microfilament phase. Since structure determines function and properties, the structural color for these phases also differs.« less

Cellulose-Based Biomimetics and Their Applications.

PubMed

Almeida, Ana P C; Canejo, João P; Fernandes, Susete N; Echeverria, Coro; Almeida, Pedro L; Godinho, Maria H

2018-05-01

Nature has been producing cellulose since long before man walked the surface of the earth. Millions of years of natural design and testing have resulted in cellulose-based structures that are an inspiration for the production of synthetic materials based on cellulose with properties that can mimic natural designs, functions, and properties. Here, five sections describe cellulose-based materials with characteristics that are inspired by gratings that exist on the petals of the plants, structurally colored materials, helical filaments produced by plants, water-responsive materials in plants, and environmental stimuli-responsive tissues found in insects and plants. The synthetic cellulose-based materials described herein are in the form of fibers and films. Fascinating multifunctional materials are prepared from cellulose-based liquid crystals and from composite cellulosic materials that combine functionality with structural performance. Future and recent applications are outlined. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Self-assembled hierarchically structured organic-inorganic composite systems.

PubMed

Tritschler, Ulrich; Cölfen, Helmut

2016-05-13

Designing bio-inspired, multifunctional organic-inorganic composite materials is one of the most popular current research objectives. Due to the high complexity of biocomposite structures found in nacre and bone, for example, a one-pot scalable and versatile synthesis approach addressing structural key features of biominerals and affording bio-inspired, multifunctional organic-inorganic composites with advanced physical properties is highly challenging. This article reviews recent progress in synthesizing organic-inorganic composite materials via various self-assembly techniques and in this context highlights a recently developed bio-inspired synthesis concept for the fabrication of hierarchically structured, organic-inorganic composite materials. This one-step self-organization concept based on simultaneous liquid crystal formation of anisotropic inorganic nanoparticles and a functional liquid crystalline polymer turned out to be simple, fast, scalable and versatile, leading to various (multi-)functional composite materials, which exhibit hierarchical structuring over several length scales. Consequently, this synthesis approach is relevant for further progress and scientific breakthrough in the research field of bio-inspired and biomimetic materials.

Biotemplated materials for sustainable energy and environment: current status and challenges.

PubMed

Zhou, Han; Fan, Tongxiang; Zhang, Di

2011-10-17

Materials science will play a key role in the further development of emerging solutions for the increasing problems of energy and environment. Materials found in nature have many inspiring structures, such as hierarchical organizations, periodic architectures, or nanostructures, that endow them with amazing functions, such as energy harvesting and conversion, antireflection, structural coloration, superhydrophobicity, and biological self-assembly. Biotemplating is an effective strategy to obtain morphology-controllable materials with structural specificity, complexity, and related unique functions. Herein, we highlight the synthesis and application of biotemplated materials for six key areas of energy and environment technologies, namely, photocatalytic hydrogen evolution, CO(2) reduction, solar cells, lithium-ion batteries, photocatalytic degradation, and gas/vapor sensing. Although the applications differ from each other, a common fundamental challenge is to realize optimum structures for improved performances. We highlight the role of four typical structures derived from biological systems exploited to optimize properties: hierarchical (porous) structures, periodic (porous) structures, hollow structures, and nanostructures. We also provide examples of using biogenic elements (e.g., C, Si, N, I, P, S) for the creation of active materials. Finally, we disscuss the challenges of achieving the desired performance for large-scale commercial applications and provide some useful prototypes from nature for the biomimetic design of new materials or systems. The emphasis is mainly focused on the structural effects and compositional utilization of biotemplated materials. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Strategies for Directing the Structure and Function of 3D Collagen Biomaterials across Length Scales

PubMed Central

Walters, Brandan D.; Stegemann, Jan P.

2013-01-01

Collagen type I is a widely used natural biomaterial that has found utility in a variety of biological and medical applications. Its well characterized structure and role as an extracellular matrix protein make it a highly relevant material for controlling cell function and mimicking tissue properties. Collagen type I is abundant in a number of tissues, and can be isolated as a purified protein. This review focuses on hydrogel biomaterials made by reconstituting collagen type I from a solubilized form, with an emphasis on in vitro studies in which collagen structure can be controlled. The hierarchical structure of collagen from the nanoscale to the macroscale is described, with an emphasis on how structure is related to function across scales. Methods of reconstituting collagen into hydrogel materials are presented, including molding of macroscopic constructs, creation of microscale modules, and electrospinning of nanoscale fibers. The modification of collagen biomaterials to achieve desired structures and functions is also addressed, with particular emphasis on mechanical control of collagen structure, creation of collagen composite materials, and crosslinking of collagenous matrices. Biomaterials scientists have made remarkable progress in rationally designing collagen-based biomaterials and in applying them to both the study of biology and for therapeutic benefit. This broad review illustrates recent examples of techniques used to control collagen structure, and to thereby direct its biological and mechanical functions. PMID:24012608

Multi-paradigm simulation at nanoscale: Methodology and application to functional carbon material

NASA Astrophysics Data System (ADS)

Su, Haibin

2012-12-01

Multiparadigm methods to span the scales from quantum mechanics to practical issues of functional nanoassembly and nanofabrication are enabling first principles predictions to guide and complement the experimental developments by designing and optimizing computationally the materials compositions and structures to assemble nanoscale systems with the requisite properties. In this talk, we employ multi-paradigm approaches to investigate functional carbon materials with versatile character, including fullerene, carbon nanotube (CNT), graphene, and related hybrid structures, which have already created an enormous impact on next generation nano devices. The topics will cover the reaction dynamics of C60 dimerization and the more challenging complex tubular fullerene formation process in the peapod structures; the computational design of a new generation of peapod nano-oscillators, the predicted magnetic state in Nano Buds; opto-electronic properties of graphene nanoribbons; and disorder / vibronic effects on transport in carbonrich materials.

Recent advances in biomimetic sensing technologies.

PubMed

Johnson, E A C; Bonser, R H C; Jeronimidis, G

2009-04-28

The importance of biological materials has long been recognized from the molecular level to higher levels of organization. Whereas, in traditional engineering, hardness and stiffness are considered desirable properties in a material, biology makes considerable and advantageous use of softer, more pliable resources. The development, structure and mechanics of these materials are well documented and will not be covered here. The purpose of this paper is, however, to demonstrate the importance of such materials and, in particular, the functional structures they form. Using only a few simple building blocks, nature is able to develop a plethora of diverse materials, each with a very different set of mechanical properties and from which a seemingly impossibly large number of assorted structures are formed. There is little doubt that this is made possible by the fact that the majority of biological 'materials' or 'structures' are based on fibres and that these fibres provide opportunities for functional hierarchies. We show how these structures have inspired a new generation of innovative technologies in the science and engineering community. Particular attention is given to the use of insects as models for biomimetically inspired innovations.

A level set-based topology optimization method for simultaneous design of elastic structure and coupled acoustic cavity using a two-phase material model

NASA Astrophysics Data System (ADS)

Noguchi, Yuki; Yamamoto, Takashi; Yamada, Takayuki; Izui, Kazuhiro; Nishiwaki, Shinji

2017-09-01

This papers proposes a level set-based topology optimization method for the simultaneous design of acoustic and structural material distributions. In this study, we develop a two-phase material model that is a mixture of an elastic material and acoustic medium, to represent an elastic structure and an acoustic cavity by controlling a volume fraction parameter. In the proposed model, boundary conditions at the two-phase material boundaries are satisfied naturally, avoiding the need to express these boundaries explicitly. We formulate a topology optimization problem to minimize the sound pressure level using this two-phase material model and a level set-based method that obtains topologies free from grayscales. The topological derivative of the objective functional is approximately derived using a variational approach and the adjoint variable method and is utilized to update the level set function via a time evolutionary reaction-diffusion equation. Several numerical examples present optimal acoustic and structural topologies that minimize the sound pressure generated from a vibrating elastic structure.

Graphene Emerges as a Versatile Template for Materials Preparation.

PubMed

Li, Zhengjie; Wu, Sida; Lv, Wei; Shao, Jiao-Jing; Kang, Feiyu; Yang, Quan-Hong

2016-05-01

Graphene and its derivatives are emerging as a class of novel but versatile templates for the controlled preparation and functionalization of materials. In this paper a conceptual review on graphene-based templates is given, highlighting their versatile roles in materials preparation. Graphene is capable of acting as a low-dimensional hard template, where its two-dimensional morphology directs the formation of novel nanostructures. Graphene oxide and other functionalized graphenes are amphiphilic and may be seen as soft templates for formatting the growth or inducing the controlled assembly of nanostructures. In addition, nanospaces in restacked graphene can be used for confining the growth of sheet-like nanostructures, and assemblies of interlinked graphenes can behave either as skeletons for the formation of composite materials or as sacrificial templates for novel materials with a controlled network structure. In summary, flexible graphene and its derivatives together with an increasing number of assembled structures show great potentials as templates for materials production. Many challenges remain, for example precise structural control of such novel templates and the removal of the non-functional remaining templates. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The journey from forensic to predictive materials science using density functional theory

DOE PAGES

Schultz, Peter A.

2017-09-12

Approximate methods for electronic structure, implemented in sophisticated computer codes and married to ever-more powerful computing platforms, have become invaluable in chemistry and materials science. The maturing and consolidation of quantum chemistry codes since the 1980s, based upon explicitly correlated electronic wave functions, has made them a staple of modern molecular chemistry. Here, the impact of first principles electronic structure in physics and materials science had lagged owing to the extra formal and computational demands of bulk calculations.

The journey from forensic to predictive materials science using density functional theory

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

Schultz, Peter A.

Approximate methods for electronic structure, implemented in sophisticated computer codes and married to ever-more powerful computing platforms, have become invaluable in chemistry and materials science. The maturing and consolidation of quantum chemistry codes since the 1980s, based upon explicitly correlated electronic wave functions, has made them a staple of modern molecular chemistry. Here, the impact of first principles electronic structure in physics and materials science had lagged owing to the extra formal and computational demands of bulk calculations.

Nano-architecture of metal-organic frameworks

NASA Astrophysics Data System (ADS)

Milichko, Valentin A.; Zalogina, Anastasiia; Mingabudinova, Leila R.; Vinogradov, Alexander V.; Ubyivovk, Evgeniy; Krasilin, Andrei A.; Mukhin, Ivan; Zuev, Dmitry A.; Makarov, Sergey V.; Pidko, Evgeny A.

2017-09-01

Change the shape and size of materials supports new functionalities never found in the sources. This strategy has been recently applied for porous crystalline materials - metal-organic frameworks (MOFs) to create hollow nanoscale structures or mesostructures with improved functional properties. However, such structures are characterized by amorphous state or polycrystallinity which limits their applicability. Here we follow this strategy to create such nano- and mesostructures with perfect crystallinity and new photonics functionalities by laser or focused ion beam fabrication.

Nanomoulding of Functional Materials, a Versatile Complementary Pattern Replication Method to Nanoimprinting

PubMed Central

Battaglia, Corsin; Söderström, Karin; Escarré, Jordi; Haug, Franz-Josef; Despeisse, Matthieu; Ballif, Christophe

2013-01-01

We describe a nanomoulding technique which allows low-cost nanoscale patterning of functional materials, materials stacks and full devices. Nanomoulding combined with layer transfer enables the replication of arbitrary surface patterns from a master structure onto the functional material. Nanomoulding can be performed on any nanoimprinting setup and can be applied to a wide range of materials and deposition processes. In particular we demonstrate the fabrication of patterned transparent zinc oxide electrodes for light trapping applications in solar cells. PMID:23380874

Materials by Design—A Perspective From Atoms to Structures

PubMed Central

Buehler, Markus J.

2013-01-01

Biological materials are effectively synthesized, controlled, and used for a variety of purposes—in spite of limitations in energy, quality, and quantity of their building blocks. Whereas the chemical composition of materials in the living world plays a some role in achieving functional properties, the way components are connected at different length scales defines what material properties can be achieved, how they can be altered to meet functional requirements, and how they fail in disease states and other extreme conditions. Recent work has demonstrated this by using large-scale computer simulations to predict materials properties from fundamental molecular principles, combined with experimental work and new mathematical techniques to categorize complex structure-property relationships into a systematic framework. Enabled by such categorization, we discuss opportunities based on the exploitation of concepts from distinct hierarchical systems that share common principles in how function is created, linking music to materials science. PMID:24163499

Multi-Physics MRI-Based Two-Layer Fluid-Structure Interaction Anisotropic Models of Human Right and Left Ventricles with Different Patch Materials: Cardiac Function Assessment and Mechanical Stress Analysis

PubMed Central

Tang, Dalin; Yang, Chun; Geva, Tal; Gaudette, Glenn; del Nido, Pedro J.

2011-01-01

Multi-physics right and left ventricle (RV/LV) fluid-structure interaction (FSI) models were introduced to perform mechanical stress analysis and evaluate the effect of patch materials on RV function. The FSI models included three different patch materials (Dacron scaffold, treated pericardium, and contracting myocardium), two-layer construction, fiber orientation, and active anisotropic material properties. The models were constructed based on cardiac magnetic resonance (CMR) images acquired from a patient with severe RV dilatation and solved by ADINA. Our results indicate that the patch model with contracting myocardium leads to decreased stress level in the patch area, improved RV function and patch area contractility. PMID:21765559

Identifying the Atomic-Level Effects of Metal Composition on the Structure and Catalytic Activity of Peptide-Templated Materials

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

Merrill, Nicholas A.; McKee, Erik M.; Merino, Kyle C.

2015-10-12

Bioinspired approaches for the formation of metallic nanomaterials have been extensively employed for a diverse range of applications including diagnostics and catalysis. These materials can often be used under sustainable conditions; however, it is challenging to control the material size, morphology, and composition simultaneously. Here we have employed the R5 peptide, which forms a 3D scaffold to direct the size and linear shape of bimetallic PdAu nanomaterials for catalysis. The materials were prepared at varying Pd:Au ratios to probe optimal compositions to achieve maximal catalytic efficiency. These materials were extensively characterized at the atomic level using transmission electron microscopy, extendedmore » X-ray absorption fine structure spectroscopy, and atomic pair distribution function analysis derived from high-energy X-ray diffraction patterns to provide highly resolved structural information. The results confirmed PdAu alloy formation, but also demonstrated that significant surface structural disorder was present. The catalytic activity of the materials was studied for olefin hydrogenation, which demonstrated enhanced reactivity from the bimetallic structures.These results present a pathway to the bioinspired production of multimetallic materials with enhanced properties, which can be assessed via a suite of characterization methods to fully ascertain structure/function relationships.« less

Mechanical Properties of Nanostructured Materials Determined Through Molecular Modeling Techniques

NASA Technical Reports Server (NTRS)

Clancy, Thomas C.; Gates, Thomas S.

2005-01-01

The potential for gains in material properties over conventional materials has motivated an effort to develop novel nanostructured materials for aerospace applications. These novel materials typically consist of a polymer matrix reinforced with particles on the nanometer length scale. In this study, molecular modeling is used to construct fully atomistic models of a carbon nanotube embedded in an epoxy polymer matrix. Functionalization of the nanotube which consists of the introduction of direct chemical bonding between the polymer matrix and the nanotube, hence providing a load transfer mechanism, is systematically varied. The relative effectiveness of functionalization in a nanostructured material may depend on a variety of factors related to the details of the chemical bonding and the polymer structure at the nanotube-polymer interface. The objective of this modeling is to determine what influence the details of functionalization of the carbon nanotube with the polymer matrix has on the resulting mechanical properties. By considering a range of degree of functionalization, the structure-property relationships of these materials is examined and mechanical properties of these models are calculated using standard techniques.

Combining electronic structure and many-body theory with large databases: A method for predicting the nature of 4 f states in Ce compounds

NASA Astrophysics Data System (ADS)

Herper, H. C.; Ahmed, T.; Wills, J. M.; Di Marco, I.; Björkman, T.; Iuşan, D.; Balatsky, A. V.; Eriksson, O.

2017-08-01

Recent progress in materials informatics has opened up the possibility of a new approach to accessing properties of materials in which one assays the aggregate properties of a large set of materials within the same class in addition to a detailed investigation of each compound in that class. Here we present a large scale investigation of electronic properties and correlated magnetism in Ce-based compounds accompanied by a systematic study of the electronic structure and 4 f -hybridization function of a large body of Ce compounds. We systematically study the electronic structure and 4 f -hybridization function of a large body of Ce compounds with the goal of elucidating the nature of the 4 f states and their interrelation with the measured Kondo energy in these compounds. The hybridization function has been analyzed for more than 350 data sets (being part of the IMS database) of cubic Ce compounds using electronic structure theory that relies on a full-potential approach. We demonstrate that the strength of the hybridization function, evaluated in this way, allows us to draw precise conclusions about the degree of localization of the 4 f states in these compounds. The theoretical results are entirely consistent with all experimental information, relevant to the degree of 4 f localization for all investigated materials. Furthermore, a more detailed analysis of the electronic structure and the hybridization function allows us to make precise statements about Kondo correlations in these systems. The calculated hybridization functions, together with the corresponding density of states, reproduce the expected exponential behavior of the observed Kondo temperatures and prove a consistent trend in real materials. This trend allows us to predict which systems may be correctly identified as Kondo systems. A strong anticorrelation between the size of the hybridization function and the volume of the systems has been observed. The information entropy for this set of systems is about 0.42. Our approach demonstrates the predictive power of materials informatics when a large number of materials is used to establish significant trends. This predictive power can be used to design new materials with desired properties. The applicability of this approach for other correlated electron systems is discussed.

Graphene-based hybrid structures combined with functional materials of ferroelectrics and semiconductors.

PubMed

Jie, Wenjing; Hao, Jianhua

2014-06-21

Fundamental studies and applications of 2-dimensional (2D) graphene may be deepened and broadened via combining graphene sheets with various functional materials, which have been extended from the traditional insulator of SiO2 to a versatile range of dielectrics, semiconductors and metals, as well as organic compounds. Among them, ferroelectric materials have received much attention due to their unique ferroelectric polarization. As a result, many attractive characteristics can be shown in graphene/ferroelectric hybrid systems. On the other hand, graphene can be integrated with conventional semiconductors and some newly-discovered 2D layered materials to form distinct Schottky junctions, yielding fascinating behaviours and exhibiting the potential for various applications in future functional devices. This review article is an attempt to illustrate the most recent progress in the fabrication, operation principle, characterization, and promising applications of graphene-based hybrid structures combined with various functional materials, ranging from ferroelectrics to semiconductors. We focus on mechanically exfoliated and chemical-vapor-deposited graphene sheets integrated in numerous advanced devices. Some typical hybrid structures have been highlighted, aiming at potential applications in non-volatile memories, transparent flexible electrodes, solar cells, photodetectors, and so on.

Graphene-based hybrid structures combined with functional materials of ferroelectrics and semiconductors

NASA Astrophysics Data System (ADS)

Jie, Wenjing; Hao, Jianhua

2014-05-01

Fundamental studies and applications of 2-dimensional (2D) graphene may be deepened and broadened via combining graphene sheets with various functional materials, which have been extended from the traditional insulator of SiO2 to a versatile range of dielectrics, semiconductors and metals, as well as organic compounds. Among them, ferroelectric materials have received much attention due to their unique ferroelectric polarization. As a result, many attractive characteristics can be shown in graphene/ferroelectric hybrid systems. On the other hand, graphene can be integrated with conventional semiconductors and some newly-discovered 2D layered materials to form distinct Schottky junctions, yielding fascinating behaviours and exhibiting the potential for various applications in future functional devices. This review article is an attempt to illustrate the most recent progress in the fabrication, operation principle, characterization, and promising applications of graphene-based hybrid structures combined with various functional materials, ranging from ferroelectrics to semiconductors. We focus on mechanically exfoliated and chemical-vapor-deposited graphene sheets integrated in numerous advanced devices. Some typical hybrid structures have been highlighted, aiming at potential applications in non-volatile memories, transparent flexible electrodes, solar cells, photodetectors, and so on.

Microstructure and Dynamic Failure Properties of Freeze-Cast Materials for Thermobaric Warhead Cases

DTIC Science & Technology

2012-12-01

Function LLNL Lawrence Livermore National Laboratory PDF Probability Density Function PMMA Poly(Methyl Methacrylate) RM Reactive Materials SEM...FREEZE CAST MATERIALS Freeze casting technology combines compounds such as aluminum oxide and poly(methyl methacrylate) ( PMMA ) to develop a...Subsequently, the porous structure can be infiltrated with a variety of materials, such as a standard polymer like PMMA . This hybrid material is believed

Local structure studies of materials using pair distribution function analysis

NASA Astrophysics Data System (ADS)

Peterson, Joseph W.

A collection of pair distribution function studies on various materials is presented in this dissertation. In each case, local structure information of interest pushes the current limits of what these studies can accomplish. The goal is to provide insight into the individual material behaviors as well as to investigate ways to expand the current limits of PDF analysis. Where possible, I provide a framework for how PDF analysis might be applied to a wider set of material phenomena. Throughout the dissertation, I discuss 0 the capabilities of the PDF method to provide information pertaining to a material's structure and properties, ii) current limitations in the conventional approach to PDF analysis, iii) possible solutions to overcome certain limitations in PDF analysis, and iv) suggestions for future work to expand and improve the capabilities PDF analysis.

Architecture engineering of supercapacitor electrode materials

NASA Astrophysics Data System (ADS)

Chen, Kunfeng; Li, Gong; Xue, Dongfeng

2016-02-01

The biggest challenge for today’s supercapacitor systems readily possessing high power density is their low energy density. Their electrode materials with controllable structure, specific surface area, electronic conductivity, and oxidation state, have long been highlighted. Architecture engineering of functional electrode materials toward powerful supercapacitor systems is becoming a big fashion in the community. The construction of ion-accessible tunnel structures can microscopically increase the specific capacitance and materials utilization; stiff 3D structures with high specific surface area can macroscopically assure high specific capacitance. Many exciting findings in electrode materials mainly focus on the construction of ice-folded graphene paper, in situ functionalized graphene, in situ crystallizing colloidal ionic particles and polymorphic metal oxides. This feature paper highlights some recent architecture engineering strategies toward high-energy supercapacitor electrode systems, including electric double-layer capacitance (EDLC) and pseudocapacitance.

What can one learn about material structure given a single first-principles calculation?

NASA Astrophysics Data System (ADS)

Rajen, Nicholas; Coh, Sinisa

2018-05-01

We extract a variable X from electron orbitals Ψn k and energies En k in the parent high-symmetry structure of a wide range of complex oxides: perovskites, rutiles, pyrochlores, and cristobalites. Even though calculation was done only in the parent structure, with no distortions, we show that X dictates material's true ground-state structure. We propose using Wannier functions to extract concealed variables such as X both for material structure prediction and for high-throughput approaches.

Programming the Assembly of Unnatural Materials with Nucleic Acids

NASA Astrophysics Data System (ADS)

Mirkin, Chad

Nature directs the assembly of enormously complex and highly functional materials through an encoded class of biomolecules, nucleic acids. The establishment of a similarly programmable code for the construction of synthetic, unnatural materials would allow researchers to impart functionality by precisely positioning all material components. Although it is exceedingly difficult to control the complex interactions between atomic and molecular species in such a manner, interactions between nanoscale components can be directed through the ligands attached to their surface. Our group has shown that nucleic acids can be used as highly programmable surface ligands to control the spacing and symmetry of nanoparticle building blocks in structurally sophisticated and functional materials. These nucleic acids function as programmable ``bonds'' between nanoparticle ``atoms,'' analogous to a nanoscale genetic code for assembling materials. The sequence and length tunability of nucleic acid bonds has allowed us to define a powerful set of design rules for the construction of nanoparticle superlattices with more than 30 unique lattice symmetries, tunable defect structures and interparticle spacings, and several well-defined crystal habits. Further, the nature of the nucleic acid bond enables an additional level of structural control: temporal regulation of dynamic material response to external biomolecular and chemical stimuli. This control allows for the reversible transformation between thermodynamic states with different crystal symmetries, particle stoichiometries, thermal stabilities, and interparticle spacings on demand. Notably, our unique genetic approach affords functional nanoparticle architectures that, among many other applications, can be used to systematically explore and manipulate optoelectronic material properties, such as tunable interparticle plasmonic interactions, microstructure-directed energy emission, and coupled plasmonic and photonic modes.

Dynamic and structural control utilizing smart materials and structures

NASA Technical Reports Server (NTRS)

Rogers, C. A.; Robertshaw, H. H.

1989-01-01

An account is given of several novel 'smart material' structural control concepts that are currently under development. The thrust of these investigations is the evolution of intelligent materials and structures superceding the recently defined variable-geometry trusses and shape memory alloy-reinforced composites; the substances envisioned will be able to autonomously evaluate emergent environmental conditions and adapt to them, and even change their operational objectives. While until now the primary objective of the developmental efforts presently discussed has been materials that mimic biological functions, entirely novel concepts may be formulated in due course.

Controlled surface functionality of magnetic nanoparticles by layer-by-layer assembled nano-films

NASA Astrophysics Data System (ADS)

Choi, Daheui; Son, Boram; Park, Tai Hyun; Hong, Jinkee

2015-04-01

Over the past several years, the preparation of functionalized nanoparticles has been aggressively pursued in order to develop desired structures, compositions, and structural order. Among the various nanoparticles, iron oxide magnetic nanoparticles (MNPs) have shown great promise because the material generated using these MNPs can be used in a variety of biomedical applications and possible bioactive functionalities. In this study, we report the development of various functionalized MNPs (F-MNPs) generated using the layer-by-layer (LbL) self-assembly method. To provide broad functional opportunities, we fabricated F-MNP bio-toolbox by using three different materials: synthetic polymers, natural polymers, and carbon materials. Each of these F-MNPs displays distinct properties, such as enhanced thickness or unique morphologies. In an effort to explore their biomedical applications, we generated basic fibroblast growth factor (bFGF)-loaded F-MNPs. The bFGF-loaded F-MNPs exhibited different release mechanisms and loading amounts, depending on the film material and composition order. Moreover, bFGF-loaded F-MNPs displayed higher biocompatibility and possessed superior proliferation properties than the bare MNPs and pure bFGF, respectively. We conclude that by simply optimizing the building materials and the nanoparticle's film composition, MNPs exhibiting various bioactive properties can be generated.Over the past several years, the preparation of functionalized nanoparticles has been aggressively pursued in order to develop desired structures, compositions, and structural order. Among the various nanoparticles, iron oxide magnetic nanoparticles (MNPs) have shown great promise because the material generated using these MNPs can be used in a variety of biomedical applications and possible bioactive functionalities. In this study, we report the development of various functionalized MNPs (F-MNPs) generated using the layer-by-layer (LbL) self-assembly method. To provide broad functional opportunities, we fabricated F-MNP bio-toolbox by using three different materials: synthetic polymers, natural polymers, and carbon materials. Each of these F-MNPs displays distinct properties, such as enhanced thickness or unique morphologies. In an effort to explore their biomedical applications, we generated basic fibroblast growth factor (bFGF)-loaded F-MNPs. The bFGF-loaded F-MNPs exhibited different release mechanisms and loading amounts, depending on the film material and composition order. Moreover, bFGF-loaded F-MNPs displayed higher biocompatibility and possessed superior proliferation properties than the bare MNPs and pure bFGF, respectively. We conclude that by simply optimizing the building materials and the nanoparticle's film composition, MNPs exhibiting various bioactive properties can be generated. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr07373h

Effects of crystal structure and composition on the photocatalytic performance of Ta-O-N functional materials.

PubMed

Liu, Qing-Lu; Zhao, Zong-Yan; Yi, Jian-Hong

2018-05-07

For photocatalytic applications, the response of a material to the solar spectrum and its redox capabilities are two important factors determined by the band gap and band edge position of the electronic structure of the material. The crystal structure and composition of the photocatalyst are fundamental for determining the above factors. In this article, we examine the functional material Ta-O-N as an example of how to discuss relationships among these factors in detail with the use of theoretical calculations. To explore how the crystal structure and composition influence the photocatalytic performance, two groups of Ta-O-N materials were considered: the first group included ε-Ta 2 O 5 , TaON, and Ta 3 N 5 ; the second group included β-Ta 2 O 5 , δ-Ta 2 O 5 , ε-Ta 2 O 5 , and amorphous-Ta 2 O 5 . Calculation results indicated that the band gap and band edge position are determined by interactions between the atomic core and valence electrons, the overlap of valence electronic states, and the localization of valence states. Ta 3 N 5 and TaON are suitable candidates for efficient photocatalysts owing to their photocatalytic water-splitting ability and good utilization efficiency of solar energy. δ-Ta 2 O 5 has a strong oxidation potential and a band gap suitable for absorbing visible light. Thus, it can be applied to photocatalytic degradation of most pollutants. Although a-Ta 2 O 5 , ε-Ta 2 O 5 , and β-Ta 2 O 5 cannot be directly used as photocatalysts, they can still be applied to modify conventional Ta-O-N photocatalysts, owing to their similar composition and structure. These calculation results will be helpful as reference data for analyzing the photocatalytic performance of more complicated Ta-O-N functional materials. On the basis of these findings, one could design novel Ta-O-N functional materials for specific photocatalytic applications by tuning the composition and crystal structure.

Types of architectural structures and the use of smart materials

NASA Astrophysics Data System (ADS)

Tavşan, Cengiz; Sipahi, Serkan

2017-07-01

The developments in technology following the industrial revolution had their share of impact on both construction techniques, and material technologies. The change in the materials used by the construction industry brought along numerous innovations, which, in turn, took on an autonomous trend of development given the rise of nano-tech materials. Today, nano-tech materials are used extensively in numerous construction categories. Nano-tech materials, in general, are characterized by their reactionary nature, with the intent of repeating the reactions again and again under certain conditions. That is why nano-tech materials are often called smart materials. In construction industry, smart materials are categorized under 4 major perspectives: Shape-shifting smart materials, power generating smart materials, self-maintenance smart materials, and smart materials providing a high level of insulation. In architecture, various categories of construction often tend to exhibit their own approaches to design, materials, and construction techniques. This is a direct consequence of the need for different solutions for different functions. In this context, the use of technological materials should lead to the use of a set of smart materials for a given category of structures, while another category utilizes yet another set. In the present study, the smart materials used in specific categories of structures were reviewed with reference to nano-tech practices implemented in Europe, with a view to try and reveal the changes in the use of smart materials with reference to categories of structures. The study entails a discussion to test the hypothesis that nano-tech materials vary with reference to structure categories, on the basis of 18 examples from various structure categories, built by the construction firms with the highest level of potential in terms of doing business in Europe. The study comprises 3 major sections: The first section reiterates what the literature has to say about smart materials; the second discusses the types and characteristics of smart materials over the tables detailing their utilization and functions in the structures included in the set of examples. The final section of the study, on the other hand, elaborates on the findings, discussing them with reference to the types of structures.

Metal-organic frameworks and their derived materials for electrochemical energy storage and conversion: Promises and challenges.

PubMed

Wu, Hao Bin; Lou, Xiong Wen David

2017-12-01

In addition to their conventional uses, metal-organic frameworks (MOFs) have recently emerged as an interesting class of functional materials and precursors of inorganic materials for electrochemical energy storage and conversion technologies. This class of MOF-related materials can be broadly categorized into two groups: pristine MOF-based materials and MOF-derived functional materials. Although the diversity in composition and structure leads to diverse and tunable functionalities of MOF-based materials, it appears that much more effort in this emerging field is devoted to synthesizing MOF-derived materials for electrochemical applications. This is in view of two main drawbacks of MOF-based materials: the low conductivity nature and the stability issue. On the contrary, MOF-derived synthesis strategies have substantial advantages in controlling the composition and structure of MOF-derived materials. From this perspective, we review some emerging applications of both groups of MOF-related materials as electrode materials for rechargeable batteries and electrochemical capacitors, efficient electrocatalysts, and even electrolytes for electrochemical devices. By highlighting the advantages and challenges of each class of materials for different applications, we hope to shed some light on the future development of this highly exciting area.

Metal-organic frameworks and their derived materials for electrochemical energy storage and conversion: Promises and challenges

PubMed Central

Wu, Hao Bin; Lou, Xiong Wen (David)

2017-01-01

In addition to their conventional uses, metal-organic frameworks (MOFs) have recently emerged as an interesting class of functional materials and precursors of inorganic materials for electrochemical energy storage and conversion technologies. This class of MOF-related materials can be broadly categorized into two groups: pristine MOF-based materials and MOF-derived functional materials. Although the diversity in composition and structure leads to diverse and tunable functionalities of MOF-based materials, it appears that much more effort in this emerging field is devoted to synthesizing MOF-derived materials for electrochemical applications. This is in view of two main drawbacks of MOF-based materials: the low conductivity nature and the stability issue. On the contrary, MOF-derived synthesis strategies have substantial advantages in controlling the composition and structure of MOF-derived materials. From this perspective, we review some emerging applications of both groups of MOF-related materials as electrode materials for rechargeable batteries and electrochemical capacitors, efficient electrocatalysts, and even electrolytes for electrochemical devices. By highlighting the advantages and challenges of each class of materials for different applications, we hope to shed some light on the future development of this highly exciting area. PMID:29214220

Biomineralization-inspired synthesis of functional organic/inorganic hybrid materials: organic molecular control of self-organization of hybrids.

PubMed

Arakaki, Atsushi; Shimizu, Katsuhiko; Oda, Mayumi; Sakamoto, Takeshi; Nishimura, Tatsuya; Kato, Takashi

2015-01-28

Organisms produce various organic/inorganic hybrid materials, which are called biominerals. They form through the self-organization of organic molecules and inorganic elements under ambient conditions. Biominerals often have highly organized and hierarchical structures from nanometer to macroscopic length scales, resulting in their remarkable physical and chemical properties that cannot be obtained by simple accumulation of their organic and inorganic constituents. These observations motivate us to create novel functional materials exhibiting properties superior to conventional materials--both synthetic and natural. Herein, we introduce recent progress in understanding biomineralization processes at the molecular level and the development of organic/inorganic hybrid materials by these processes. We specifically outline fundamental molecular studies on silica, iron oxide, and calcium carbonate biomineralization and describe material synthesis based on these mechanisms. These approaches allow us to design a variety of advanced hybrid materials with desired morphologies, sizes, compositions, and structures through environmentally friendly synthetic routes using functions of organic molecules.

Aperiodic topological order in the domain configurations of functional materials

NASA Astrophysics Data System (ADS)

Huang, Fei-Ting; Cheong, Sang-Wook

2017-03-01

In numerous functional materials, such as steels, ferroelectrics and magnets, new functionalities can be achieved through the engineering of the domain structures, which are associated with the ordering of certain parameters within the material. The recent progress in technologies that enable imaging at atomic-scale spatial resolution has transformed our understanding of domain topology, revealing that, along with simple stripe-like or irregularly shaped domains, intriguing vortex-type topological domain configurations also exist. In this Review, we present a new classification scheme of 'Zm Zn domains with Zl vortices' for 2D macroscopic domain structures with m directional variants and n translational antiphases. This classification, together with the concepts of topological protection and topological charge conservation, can be applied to a wide range of materials, such as multiferroics, improper ferroelectrics, layered transition metal dichalcogenides and magnetic superconductors, as we discuss using selected examples. The resulting topological considerations provide a new basis for the understanding of the formation, kinetics, manipulation and property optimization of domains and domain boundaries in functional materials.

Topology-Scaling Identification of Layered Solids and Stable Exfoliated 2D Materials.

PubMed

Ashton, Michael; Paul, Joshua; Sinnott, Susan B; Hennig, Richard G

2017-03-10

The Materials Project crystal structure database has been searched for materials possessing layered motifs in their crystal structures using a topology-scaling algorithm. The algorithm identifies and measures the sizes of bonded atomic clusters in a structure's unit cell, and determines their scaling with cell size. The search yielded 826 stable layered materials that are considered as candidates for the formation of two-dimensional monolayers via exfoliation. Density-functional theory was used to calculate the exfoliation energy of each material and 680 monolayers emerge with exfoliation energies below those of already-existent two-dimensional materials. The crystal structures of these two-dimensional materials provide templates for future theoretical searches of stable two-dimensional materials. The optimized structures and other calculated data for all 826 monolayers are provided at our database (https://materialsweb.org).

Functionalization of graphene for efficient energy conversion and storage.

PubMed

Dai, Liming

2013-01-15

As global energy consumption accelerates at an alarming rate, the development of clean and renewable energy conversion and storage systems has become more important than ever. Although the efficiency of energy conversion and storage devices depends on a variety of factors, their overall performance strongly relies on the structure and properties of the component materials. Nanotechnology has opened up new frontiers in materials science and engineering to meet this challenge by creating new materials, particularly carbon nanomaterials, for efficient energy conversion and storage. As a building block for carbon materials of all other dimensionalities (such as 0D buckyball, 1D nanotube, 3D graphite), the two-dimensional (2D) single atomic carbon sheet of graphene has emerged as an attractive candidate for energy applications due to its unique structure and properties. Like other materials, however, a graphene-based material that possesses desirable bulk properties rarely features the surface characteristics required for certain specific applications. Therefore, surface functionalization is essential, and researchers have devised various covalent and noncovalent chemistries for making graphene materials with the bulk and surface properties needed for efficient energy conversion and storage. In this Account, I summarize some of our new ideas and strategies for the controlled functionalization of graphene for the development of efficient energy conversion and storage devices, such as solar cells, fuel cells, supercapacitors, and batteries. The dangling bonds at the edge of graphene can be used for the covalent attachment of various chemical moieties while the graphene basal plane can be modified via either covalent or noncovalent functionalization. The asymmetric functionalization of the two opposite surfaces of individual graphene sheets with different moieties can lead to the self-assembly of graphene sheets into hierarchically structured materials. Judicious application of these site-selective reactions to graphene sheets has opened up a rich field of graphene-based energy materials with enhanced performance in energy conversion and storage. These results reveal the versatility of surface functionalization for making sophisticated graphene materials for energy applications. Even though many covalent and noncovalent functionalization methods have already been reported, vast opportunities remain for developing novel graphene materials for highly efficient energy conversion and storage systems.

Design for cyclic loading endurance of composites

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Murthy, Pappu L. N.; Chamis, Christos C.; Liaw, Leslie D. G.

1993-01-01

The application of the computer code IPACS (Integrated Probabilistic Assessment of Composite Structures) to aircraft wing type structures is described. The code performs a complete probabilistic analysis for composites taking into account the uncertainties in geometry, boundary conditions, material properties, laminate lay-ups, and loads. Results of the analysis are presented in terms of cumulative distribution functions (CDF) and probability density function (PDF) of the fatigue life of a wing type composite structure under different hygrothermal environments subjected to the random pressure. The sensitivity of the fatigue life to a number of critical structural/material variables is also computed from the analysis.

Neural network approach for characterizing structural transformations by X-ray absorption fine structure

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

Timoshenko, Janis; Frenkel, Anatoly I.; Cintins, Arturs

The knowledge of coordination environment around various atomic species in many functional materials provides a key for explaining their properties and working mechanisms. Many structural motifs and their transformations are difficult to detect and quantify in the process of work (operando conditions), due to their local nature, small changes, low dimensionality of the material, and/or extreme conditions. Here we use artificial neural network approach to extract the information on the local structure and its in-situ changes directly from the X-ray absorption fine structure spectra. We illustrate this capability by extracting the radial distribution function (RDF) of atoms in ferritic andmore » austenitic phases of bulk iron across the temperature-induced transition. Integration of RDFs allows us to quantify the changes in the iron coordination and material density, and to observe the transition from body-centered to face-centered cubic arrangement of iron atoms. Furthermore, this method is attractive for a broad range of materials and experimental conditions« less

Neural network approach for characterizing structural transformations by X-ray absorption fine structure

DOE PAGES

Timoshenko, Janis; Frenkel, Anatoly I.; Cintins, Arturs; ...

2018-05-25

The knowledge of coordination environment around various atomic species in many functional materials provides a key for explaining their properties and working mechanisms. Many structural motifs and their transformations are difficult to detect and quantify in the process of work (operando conditions), due to their local nature, small changes, low dimensionality of the material, and/or extreme conditions. Here we use artificial neural network approach to extract the information on the local structure and its in-situ changes directly from the X-ray absorption fine structure spectra. We illustrate this capability by extracting the radial distribution function (RDF) of atoms in ferritic andmore » austenitic phases of bulk iron across the temperature-induced transition. Integration of RDFs allows us to quantify the changes in the iron coordination and material density, and to observe the transition from body-centered to face-centered cubic arrangement of iron atoms. Furthermore, this method is attractive for a broad range of materials and experimental conditions« less

Neural Network Approach for Characterizing Structural Transformations by X-Ray Absorption Fine Structure Spectroscopy

NASA Astrophysics Data System (ADS)

Timoshenko, Janis; Anspoks, Andris; Cintins, Arturs; Kuzmin, Alexei; Purans, Juris; Frenkel, Anatoly I.

2018-06-01

The knowledge of the coordination environment around various atomic species in many functional materials provides a key for explaining their properties and working mechanisms. Many structural motifs and their transformations are difficult to detect and quantify in the process of work (operando conditions), due to their local nature, small changes, low dimensionality of the material, and/or extreme conditions. Here we use an artificial neural network approach to extract the information on the local structure and its in situ changes directly from the x-ray absorption fine structure spectra. We illustrate this capability by extracting the radial distribution function (RDF) of atoms in ferritic and austenitic phases of bulk iron across the temperature-induced transition. Integration of RDFs allows us to quantify the changes in the iron coordination and material density, and to observe the transition from a body-centered to a face-centered cubic arrangement of iron atoms. This method is attractive for a broad range of materials and experimental conditions.

Chemical Changes in Layered Ferroelectric Semiconductors Induced by Helium Ion Beam

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

Belianinov, Alex; Burch, Matthew J.; Hysmith, Holland E.

Transitioning to multi-material systems as either interfaced 2D materials or 3D heterostructures can lead to the next generation multi-functional device architectures. Combined direct physical and chemical nanoscale control of these systems offers a new way to tailor material and device functionality as functional structures reach their physical limit. Transition metal thiophosphate (TPS), Cu 1-xIn 1+x/3P 2S 6, that have ferroelectric polarization behavior as layered crystals at room temperature and above make them attractive candidates for direct material sculpting of both chemical and functional properties. The bulk material exhibits stable ferroelectric polarization corroborated by domain structures, rewritable polarization, and hysteresis loops.more » Our previous studies have demonstrated that ferroic order persists on the surface and that spinoidal decomposition of ferroelectric and paraelectric phases occurs in non-stoichiometric Cu/In ratio formulations. Here, we elucidate the chemical changes induced through helium ion irradiation in the TPS family library with varying Cu/In ratio formulations using correlated AFM and ToF-SIMS imaging. We correlate nano- and micro- structures that scale, in area and volume, to the total dose of the helium ion beam, as well as the overall copper concentration in the sample. Furthermore, our ToF-SIMS results show that ion irradiation leads to oxygen penetration as a function of Cu concentration, and proceeds along the Cu domains to the stopping distance of the helium ions in the TPS material. These results opens up new opportunities to understand and implement ferroicly coupled van der Waal devices into an existing framework of 2D heterostructures by locally tuning material chemistry and functionality.« less

Chemical Changes in Layered Ferroelectric Semiconductors Induced by Helium Ion Beam

DOE PAGES

Belianinov, Alex; Burch, Matthew J.; Hysmith, Holland E.; ...

2017-11-30

Transitioning to multi-material systems as either interfaced 2D materials or 3D heterostructures can lead to the next generation multi-functional device architectures. Combined direct physical and chemical nanoscale control of these systems offers a new way to tailor material and device functionality as functional structures reach their physical limit. Transition metal thiophosphate (TPS), Cu 1-xIn 1+x/3P 2S 6, that have ferroelectric polarization behavior as layered crystals at room temperature and above make them attractive candidates for direct material sculpting of both chemical and functional properties. The bulk material exhibits stable ferroelectric polarization corroborated by domain structures, rewritable polarization, and hysteresis loops.more » Our previous studies have demonstrated that ferroic order persists on the surface and that spinoidal decomposition of ferroelectric and paraelectric phases occurs in non-stoichiometric Cu/In ratio formulations. Here, we elucidate the chemical changes induced through helium ion irradiation in the TPS family library with varying Cu/In ratio formulations using correlated AFM and ToF-SIMS imaging. We correlate nano- and micro- structures that scale, in area and volume, to the total dose of the helium ion beam, as well as the overall copper concentration in the sample. Furthermore, our ToF-SIMS results show that ion irradiation leads to oxygen penetration as a function of Cu concentration, and proceeds along the Cu domains to the stopping distance of the helium ions in the TPS material. These results opens up new opportunities to understand and implement ferroicly coupled van der Waal devices into an existing framework of 2D heterostructures by locally tuning material chemistry and functionality.« less

Materials and structures technology insertion into spacecraft systems: Successes and challenges

NASA Astrophysics Data System (ADS)

Rawal, Suraj

2018-05-01

Over the last 30 years, significant advancements have led to the use of multifunctional materials and structures technologies in spacecraft systems. This includes the integration of adaptive structures, advanced composites, nanotechnology, and additive manufacturing technologies. Development of multifunctional structures has been directly influenced by the implementation of processes and tools for adaptive structures pioneered by Prof. Paolo Santini. Multifunctional materials and structures incorporating non-structural engineering functions such as thermal, electrical, radiation shielding, power, and sensors have been investigated. The result has been an integrated structure that offers reduced mass, packaging volume, and ease of integration for spacecraft systems. Current technology development efforts are being conducted to develop innovative multifunctional materials and structures designs incorporating advanced composites, nanotechnology, and additive manufacturing. However, these efforts offer significant challenges in the qualification and acceptance into spacecraft systems. This paper presents a brief overview of the technology development and successful insertion of advanced material technologies into spacecraft structures. Finally, opportunities and challenges to develop and mature next generation advanced materials and structures are presented.

Functional materials based on nanocrystalline cellulose

NASA Astrophysics Data System (ADS)

Surov, O. V.; Voronova, M. I.; Zakharov, A. G.

2017-10-01

The data on the synthesis of functional materials based on nanocrystalline cellulose (NCC) published over the past 10 years are analyzed. The liquid-crystal properties of NCC suspensions, methods of investigation of NCC suspensions and films, conditions for preserving chiral nematic structure in the NCC films after removal of the solvent and features of templated sol-gel synthesis of functional materials based on NCC are considered. The bibliography includes 106 references.

Strain-engineering of Janus SiC monolayer functionalized with H and F atoms

NASA Astrophysics Data System (ADS)

Drissi, L. B.; Sadki, K.; Kourra, M.-H.; Bousmina, M.

2018-05-01

Based on ab initio density functional theory calculations, the structural, electronic, mechanical, acoustic, thermodynamic, and piezoelectric properties of (F,H) Janus SiC monolayers are studied. The new set of derivatives shows buckled structures and different band gap values. Under strain, the buckling changes and the structures pass from semiconducting to metallic. The elastic limits and the metastable regions are determined. The Young's modulus and Poisson ratio reveal stronger behavior for the modified conformers with respect to graphene. The values of the Debye temperature make the new materials suitable for thermal application. Moreover, all the conformers show in-plane and out-of-plane piezoelectric responses comparable with known two-dimensional materials. If engineered, such piezoelectric Janus structures may be promising materials for various nanoelectromechanical applications.

Materials Data on TiNi (SG:157) by Materials Project

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

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CdAu (SG:157) by Materials Project

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

Kristin Persson

2016-03-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP (SG:19) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PdC (SG:216) by Materials Project

DOE Data Explorer

Kristin Persson

2016-09-21

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PdC (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2016-09-21

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PuSe (SG:225) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TiRe (SG:221) by Materials Project

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

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca (SG:229) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TiC (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PuB (SG:225) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on HoP (SG:225) by Materials Project

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

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on HoP (SG:221) by Materials Project

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

Kristin Persson

2016-07-26

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YSb2 (SG:21) by Materials Project

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

Kristin Persson

2017-04-07

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TaN (SG:216) by Materials Project

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

Kristin Persson

2016-09-24

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TaN (SG:221) by Materials Project

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

Kristin Persson

2016-09-25

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KWO3 (SG:221) by Materials Project

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

Kristin Persson

2017-07-17

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CaAs (SG:189) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on InN (SG:186) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on SnPd (SG:62) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on SrO (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on DyTh (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on In (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on GdGe (SG:63) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CrO (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on MgPt (SG:198) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on USnPt (SG:216) by Materials Project

DOE Data Explorer

Kristin Persson

2015-03-19

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Be (SG:136) by Materials Project

DOE Data Explorer

Kristin Persson

2016-09-17

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Nd (SG:229) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on DyNi (SG:62) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on SbIr (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on BaSe (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on BaSe (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on BPS4 (SG:23) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on GaN (SG:216) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on GaN (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on GaN (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2016-09-15

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on GaN (SG:186) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TlBr (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TlBr (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TlBr (SG:63) by Materials Project

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

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on P (SG:12) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LuP (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on P (SG:64) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CoPSe (SG:61) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on P (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on P (SG:0) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on P (SG:13) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LuPPt (SG:187) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on NpP (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on P (SG:74) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on P (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on P (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on FeP (SG:62) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on P (SG:166) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CaPAu (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:59) by Materials Project

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

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:166) by Materials Project

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

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:1) by Materials Project

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

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:15) by Materials Project

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

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:227) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:63) by Materials Project

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

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:139) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:10) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:166) by Materials Project

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

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:12) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:74) by Materials Project

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

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:10) by Materials Project

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

Kristin Persson

2016-02-04

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:2) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:194) by Materials Project

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

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:62) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:136) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:11) by Materials Project

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

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:160) by Materials Project

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

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:87) by Materials Project

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

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:1) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on U (SG:136) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on U (SG:63) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on U (SG:229) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on U (SG:102) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on U (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2016-09-18

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CuS (SG:63) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CuS (SG:194) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CuS (SG:225) by Materials Project

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

Kristin Persson

2017-04-25

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on BiO (SG:160) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VO2 (SG:14) by Materials Project

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

Kristin Persson

2017-04-14

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on NaSi (SG:15) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VS2 (SG:2) by Materials Project

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

Kristin Persson

2016-02-04

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CoMo (SG:221) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on SiS (SG:53) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on P (SG:53) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on B (SG:1) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on B (SG:134) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on B (SG:166) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on BNCl2 (SG:146) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on B (SG:134) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on BAs (SG:216) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TiB (SG:216) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on B (SG:166) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CoW (SG:221) by Materials Project

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

Kristin Persson

2016-09-15

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Mg (SG:229) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Mg (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on RbS (SG:71) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on RbS (SG:189) by Materials Project

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

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CCl4 (SG:15) by Materials Project

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

Kristin Persson

2016-08-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PH3 (SG:1) by Materials Project

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

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on USb (SG:221) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on USb (SG:225) by Materials Project

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

Kristin Persson

2016-07-14

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on UN (SG:225) by Materials Project

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

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KSb2 (SG:12) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KTlO (SG:12) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ThC (SG:221) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ThC (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on IrN (SG:131) by Materials Project

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

Kristin Persson

2016-09-15

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TiH (SG:131) by Materials Project

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

Kristin Persson

2016-02-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PtO (SG:131) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PdN (SG:131) by Materials Project

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

Kristin Persson

2016-05-24

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on OsN (SG:131) by Materials Project

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

Kristin Persson

2016-05-24

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CuO (SG:131) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PbO (SG:131) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CrO (SG:131) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ReN (SG:131) by Materials Project

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

Kristin Persson

2016-09-03

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YCoC (SG:131) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TcN (SG:131) by Materials Project

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

Kristin Persson

2016-05-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ZrH (SG:131) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on USO (SG:129) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on AlSb (SG:63) by Materials Project

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

Kristin Persson

2017-04-28

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LaSn (SG:63) by Materials Project

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

Kristin Persson

2017-04-07

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CeRh (SG:63) by Materials Project

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

Kristin Persson

2017-04-07

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on AsS (SG:14) by Materials Project

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

Kristin Persson

2016-02-04

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on AsS (SG:1) by Materials Project

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

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on AsS (SG:15) by Materials Project

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

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on AsS (SG:14) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on K (SG:63) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on K (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2016-05-19

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on K (SG:64) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on K (SG:229) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on K (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on K (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on K (SG:15) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ScC (SG:216) by Materials Project

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

Kristin Persson

2016-09-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ScGe (SG:216) by Materials Project

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

Kristin Persson

2016-09-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ScSi (SG:216) by Materials Project

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

Kristin Persson

2016-09-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ScSn (SG:216) by Materials Project

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

Kristin Persson

2016-09-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Sb (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:14) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:70) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:58) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:19) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:13) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:148) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:15) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:29) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:15) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-04

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:4) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-04

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:99) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:154) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:14) by Materials Project

DOE Data Explorer

Kristin Persson

2016-07-14

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:143) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:143) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on S (SG:60) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on HoSe (SG:225) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on O2 (SG:69) by Materials Project

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

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on O2 (SG:166) by Materials Project

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

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on As (SG:166) by Materials Project

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

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on N2 (SG:194) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CdC (SG:216) by Materials Project

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

Kristin Persson

2016-09-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CdC (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2016-09-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CdIBr (SG:160) by Materials Project

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

Kristin Persson

2017-05-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CSNOF5 (SG:2) by Materials Project

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

Kristin Persson

2016-03-28

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CSNF5 (SG:62) by Materials Project

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

Kristin Persson

2016-03-28

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YP (SG:225) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LaAs (SG:225) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YP (SG:221) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LaP (SG:225) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YAs (SG:221) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YAs (SG:225) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ZrRh (SG:51) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on HfIr (SG:51) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VPt (SG:51) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TiMo (SG:74) by Materials Project

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

Kristin Persson

2016-09-03

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ZrC (SG:216) by Materials Project

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

Kristin Persson

2016-09-25

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ZrC (SG:225) by Materials Project

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

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ZrC (SG:194) by Materials Project

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

Kristin Persson

2016-12-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ZrC (SG:221) by Materials Project

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

Kristin Persson

2016-09-25

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on V (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on V (SG:229) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ErSF (SG:129) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on F (SG:64) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CuF (SG:216) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LiF (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TbSF (SG:129) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YSF (SG:129) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CF4 (SG:15) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YOF (SG:129) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on HoSF (SG:129) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on RbF (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Y (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Y (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on SO2 (SG:41) by Materials Project

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

Kristin Persson

2016-02-04

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on NaNO (SG:14) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LaS (SG:221) by Materials Project

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

Kristin Persson

2016-09-19

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VB2 (SG:191) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on UTe3 (SG:63) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Rb (SG:70) by Materials Project

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

Kristin Persson

2017-04-07

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:166) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:12) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:58) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:63) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-04

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:227) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:166) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:65) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2016-05-19

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:214) by Materials Project

DOE Data Explorer

Kristin Persson

2017-04-07

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:65) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:166) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:67) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-20

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:0) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:71) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:65) by Materials Project

DOE Data Explorer

Kristin Persson

2016-09-16

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:191) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:166) by Materials Project

DOE Data Explorer

Kristin Persson

2016-05-16

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2016-09-03

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:202) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:69) by Materials Project

DOE Data Explorer

Kristin Persson

2016-07-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:229) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:191) by Materials Project

DOE Data Explorer

Kristin Persson

2017-07-14

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:67) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2016-09-17

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:206) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on C (SG:191) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VS2 (SG:47) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Tb (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ReN (SG:216) by Materials Project

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

Kristin Persson

2016-07-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ReN (SG:225) by Materials Project

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

Kristin Persson

2016-09-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ReN (SG:221) by Materials Project

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

Kristin Persson

2016-07-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ReN (SG:221) by Materials Project

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

Kristin Persson

2017-04-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ReN (SG:194) by Materials Project

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

Kristin Persson

2016-09-03

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ReN (SG:187) by Materials Project

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

Kristin Persson

2016-09-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YSn2 (SG:63) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on VSn2 (SG:70) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on UAs (SG:221) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CoN (SG:216) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on BNF8 (SG:113) by Materials Project

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

Kristin Persson

2016-02-04

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on SnP (SG:107) by Materials Project

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

Kristin Persson

2016-07-14

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on SnP (SG:225) by Materials Project

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

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on UN2 (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on UO (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TlC (SG:225) by Materials Project

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

Kristin Persson

2016-07-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ErP (SG:225) by Materials Project

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

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ErP (SG:221) by Materials Project

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

Kristin Persson

2016-07-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ErS (SG:225) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CoN (SG:225) by Materials Project

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

Kristin Persson

2016-09-19

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CoN (SG:221) by Materials Project

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

Kristin Persson

2016-09-19

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TbAu (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TbSe (SG:186) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TbAl (SG:57) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TbRh (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Tb (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Tb (SG:229) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Tb (SG:166) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TbTe (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TbGa (SG:63) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Multi-scale predictive modeling of nano-material and realistic electron devices

NASA Astrophysics Data System (ADS)

Palaria, Amritanshu

Among the challenges faced in further miniaturization of electronic devices, heavy influence of the detailed atomic configuration of the material(s) involved, which often differs significantly from that of the bulk material(s), is prominent. Device design has therefore become highly interrelated with material engineering at the atomic level. This thesis aims at outlining, with examples, a multi-scale simulation procedure that allows one to integrate material and device aspects of nano-electronic design to predict behavior of novel devices with novel material. This is followed in four parts: (1) An approach that combines a higher time scale reactive force field analysis with density functional theory to predict structure of new material is demonstrated for the first time for nanowires. Novel stable structures for very small diameter silicon nanowires are predicted. (2) Density functional theory is used to show that the new nanowire structures derived in 1 above have properties different from diamond core wires even though the surface bonds in some may be similar to the surface of bulk silicon. (3) Electronic structure of relatively large-scale germanium sections of realistically strained Si/strained Ge/ strained Si nanowire heterostructures is computed using empirical tight binding and it is shown that the average non-homogeneous strain in these structures drives their interesting non-conventional electronic characteristics such as hole effective masses which decrease as the wire cross-section is reduced. (4) It is shown that tight binding, though empirical in nature, is not necessarily limited to the material and atomic structure for which the parameters have been empirically derived, but that simple changes may adapt the derived parameters to new bond environments. Si (100) surface electronic structure is obtained from bulk Si parameters.

Resolving the structure of Ti 3C 2T x MXenes through multilevel structural modeling of the atomic pair distribution function

DOE PAGES

Wesolowski, David J.; Wang, Hsiu -Wen; Page, Katharine L.; ...

2015-12-08

MXenes are a recently discovered family of two-dimensional (2D) early transition metal carbides and carbonitrides, which have already shown many attractive properties and great promise in energy storage and many other applications. But, a complex surface chemistry and small coherence length have been obstacles in some applications of MXenes, also limiting the accuracy of predictions of their properties. In this study, we describe and benchmark a novel way of modeling layered materials with real interfaces (diverse surface functional groups and stacking order between the adjacent monolayers) against experimental data. The structures of three kinds of Ti 3C 2T x MXenesmore » (T stands for surface terminating species, including O, OH, and F) produced under different synthesis conditions were resolved for the first time using atomic pair distribution function obtained by high-quality neutron total scattering. We present the true nature of the material can be easily captured with the sensitivity of neutron scattering to the surface species of interest and the detailed “third-generation” structure model. The modeling approach leads to new understanding of MXene structural properties and can replace the currently used idealized models in predictions of a variety of physical, chemical, and functional properties of Ti 3C 2-based MXenes. Moreover, the developed models can be employed to guide the design of new MXene materials with selected surface termination and controlled contact angle, catalytic, optical, electrochemical, and other properties. Finally, we suggest that the multilevel structural modeling should form the basis for a generalized methodology on modeling diffraction and pair distribution function data for 2D and layered materials.« less

Recent Progress in Biomimetic Additive Manufacturing Technology: From Materials to Functional Structures.

PubMed

Yang, Yang; Song, Xuan; Li, Xiangjia; Chen, Zeyu; Zhou, Chi; Zhou, Qifa; Chen, Yong

2018-06-19

Nature has developed high-performance materials and structures over millions of years of evolution and provides valuable sources of inspiration for the design of next-generation structural materials, given the variety of excellent mechanical, hydrodynamic, optical, and electrical properties. Biomimicry, by learning from nature's concepts and design principles, is driving a paradigm shift in modern materials science and technology. However, the complicated structural architectures in nature far exceed the capability of traditional design and fabrication technologies, which hinders the progress of biomimetic study and its usage in engineering systems. Additive manufacturing (three-dimensional (3D) printing) has created new opportunities for manipulating and mimicking the intrinsically multiscale, multimaterial, and multifunctional structures in nature. Here, an overview of recent developments in 3D printing of biomimetic reinforced mechanics, shape changing, and hydrodynamic structures, as well as optical and electrical devices is provided. The inspirations are from various creatures such as nacre, lobster claw, pine cone, flowers, octopus, butterfly wing, fly eye, etc., and various 3D-printing technologies are discussed. Future opportunities for the development of biomimetic 3D-printing technology to fabricate next-generation functional materials and structures in mechanical, electrical, optical, and biomedical engineering are also outlined. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Impact of interfacial imperfection on transverse wave in a functionally graded piezoelectric material structure with corrugated boundaries

NASA Astrophysics Data System (ADS)

Kumar Singh, Abhishek; Kumar, Santan; Kumari, Richa

2018-03-01

The propagation behavior of Love-type wave in a corrugated functionally graded piezoelectric material layered structure has been taken into account. Concretely, the layered structure incorporates a corrugated functionally graded piezoelectric material layer imperfectly bonded to a functionally graded piezoelectric material half-space. An analytical treatment has been employed to determine the dispersion relation for both cases of electrically open condition and electrically short condition. The phase velocity of the Love-type wave has been computed numerically and its dependence on the wave number has been depicted graphically for a specific type of corrugated boundary surfaces for both said conditions. The crux of the study lies in the fact that the imperfect bonding of the interface, the corrugated boundaries present in the layer, and the material properties of the layer and the half-space strongly influence the phase velocity of the Love-type wave. It can be remarkably noted that the imperfect bonding of the interface reduces the phase velocity of the Love-type wave significantly. As a special case of the problem, it is noticed that the procured dispersion relation for both cases of electrically open and electrically short conditions is in accordance with the classical Love wave equation.

Density Functional Theory and Beyond for Band-Gap Screening: Performance for Transition-Metal Oxides and Dichalcogenides.

PubMed

Li, Wenqing; Walther, Christian F J; Kuc, Agnieszka; Heine, Thomas

2013-07-09

The performance of a wide variety of commonly used density functionals, as well as two screened hybrid functionals (HSE06 and TB-mBJ), on predicting electronic structures of a large class of en vogue materials, such as metal oxides, chalcogenides, and nitrides, is discussed in terms of band gaps, band structures, and projected electronic densities of states. Contrary to GGA, hybrid functionals and GGA+U, both HSE06 and TB-mBJ are able to predict band gaps with an appreciable accuracy of 25% and thus allow the screening of various classes of transition-metal-based compounds, i.e., mixed or doped materials, at modest computational cost. The calculated electronic structures are largely unaffected by the choice of basis functions and software implementation, however, might be subject to the treatment of the core electrons.

Materials taking a lesson from nature.

PubMed

Tian, Liangfei; Croisier, Emmanuel; Frauenrath, Holger

2013-01-01

Structural biomaterials with their often extraordinary properties and versatile functions are typically constructed from very limited sets of building blocks and types of supramolecular interactions. In this review we discuss how, inspired by nature's design principles for protein-based materials, oligopeptide-modified polymers can be used as a versatile toolbox to program nanostructure and hierarchical structure formation in synthetic materials.

3D-printing and mechanics of bio-inspired articulated and multi-material structures.

PubMed

Porter, Michael M; Ravikumar, Nakul; Barthelat, Francois; Martini, Roberto

2017-09-01

3D-printing technologies allow researchers to build simplified physical models of complex biological systems to more easily investigate their mechanics. In recent years, a number of 3D-printed structures inspired by the dermal armors of various fishes have been developed to study their multiple mechanical functionalities, including flexible protection, improved hydrodynamics, body support, or tail prehensility. Natural fish armors are generally classified according to their shape, material and structural properties as elasmoid scales, ganoid scales, placoid scales, carapace scutes, or bony plates. Each type of dermal armor forms distinct articulation patterns that facilitate different functional advantages. In this paper, we highlight recent studies that developed 3D-printed structures not only to inform the design and application of some articulated and multi-material structures, but also to explain the mechanics of the natural biological systems they mimic. Copyright © 2017 Elsevier Ltd. All rights reserved.

Materials Data on Ba21Al40 (SG:157) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Tl6S (SG:157) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Zr5Sb3 (SG:193) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Zr5Sb4 (SG:193) by Materials Project

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

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP(HO2)2 (SG:9) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP(HO2)2 (SG:122) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP(HO2)2 (SG:82) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP(HO2)2 (SG:14) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP(HO2)2 (SG:13) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP(OF)2 (SG:62) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP(HO)2 (SG:15) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP(HO2)2 (SG:2) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP(HO2)2 (SG:43) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KP(HO2)2 (SG:19) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on H2SO4 (SG:14) by Materials Project

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

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on NaZn(HO)3 (SG:106) by Materials Project

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

Kristin Persson

2016-02-04

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ThB6 (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Mg2PHO5 (SG:62) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Mg2PHO5 (SG:157) by Materials Project

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

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CeSb(SBr)2 (SG:14) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Zn8Cu5 (SG:217) by Materials Project

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

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on La5Si3 (SG:140) by Materials Project

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

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LaSb(SBr)2 (SG:14) by Materials Project

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

Kristin Persson

2016-02-04

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(GeRh)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(BC)2 (SG:131) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(GePd)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(NiGe)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(MnGe)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(AlZn)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(NO3)2 (SG:205) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(BeN)2 (SG:140) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(NiP)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(BeGe)2 (SG:129) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(GeIr)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(ZnGe)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2015-03-24

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(BO2)2 (SG:60) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(BS2)2 (SG:205) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(BO2)2 (SG:205) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(PIr)2 (SG:154) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(MgBi)2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(GeRu)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(YS2)2 (SG:62) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(CoP)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(IO3)2 (SG:14) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(BIr)2 (SG:70) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-18

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(MnSb)2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(AlGe)2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(MnBi)2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-05

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ca(ZnSi)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ba(AsPd)2 (SG:123) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Sm(BO2)3 (SG:15) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KCd(NO2)3 (SG:146) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Pr(BO2)3 (SG:15) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on V2(OF)3 (SG:3) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LaCoO3 (SG:167) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LaCoO3 (SG:221) by Materials Project

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

Kristin Persson

2016-04-22

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LaCoO3 (SG:2) by Materials Project

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

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TmSb2 (SG:21) by Materials Project

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

Kristin Persson

2017-04-07

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ErSb2 (SG:21) by Materials Project

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

Kristin Persson

2017-04-07

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TbSb2 (SG:21) by Materials Project

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

Kristin Persson

2017-04-07

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on DySb2 (SG:21) by Materials Project

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

Kristin Persson

2017-04-07

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CeInIr (SG:189) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Si3H (SG:166) by Materials Project

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

Kristin Persson

2017-07-18

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on RbOsO3 (SG:221) by Materials Project

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

Kristin Persson

2017-07-18

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on MoWSeS3 (SG:156) by Materials Project

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

Kristin Persson

2017-05-25

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on NaMoO3 (SG:221) by Materials Project

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

Kristin Persson

2017-07-17

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on KMoO3 (SG:221) by Materials Project

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

Kristin Persson

2017-07-17

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TeMoSe (SG:156) by Materials Project

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

Kristin Persson

2017-05-25

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on NaOsO3 (SG:221) by Materials Project

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

Kristin Persson

2017-07-18

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TeMoWSe3 (SG:156) by Materials Project

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

Kristin Persson

2017-05-25

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LaSiIr (SG:198) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CsTiF4 (SG:129) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PbSO4 (SG:62) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CeInAu2 (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ZrSnRh (SG:190) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Al5Co2 (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on NdMg3 (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TbIr2 (SG:227) by Materials Project

DOE Data Explorer

Kristin Persson

2015-05-16

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Pb(CO2)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Pr3GaC (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CsIO3 (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TaMn2 (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on AgAuS2 (SG:49) by Materials Project

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

Kristin Persson

2016-02-10

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Tm(FeSi)2 (SG:139) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CaNiF5 (SG:15) by Materials Project

DOE Data Explorer

Kristin Persson

2014-09-30

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CaAs(HO)7 (SG:61) by Materials Project

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

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TaSe2 (SG:42) by Materials Project

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

Kristin Persson

2016-07-14

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on NbS2 (SG:42) by Materials Project

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

Kristin Persson

2016-07-14

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on CeSe2 (SG:42) by Materials Project

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

Kristin Persson

2017-07-17

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Pd(SCl3)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Nb(SeCl)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YCu(WO4)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2014-07-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Au(OF3)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2016-02-11

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ni(WO4)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Pt(SCl3)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2016-05-20

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Sb(IF3)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Co(WO4)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Rh(OF3)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Pr(WO4)2 (SG:2) by Materials Project

DOE Data Explorer

Kristin Persson

2016-04-23

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Li2Ca (SG:227) by Materials Project

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

Kristin Persson

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Er(NiGe)2 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ho2SO2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Na2BHO3 (SG:62) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Pu2Co (SG:189) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Dy2SO2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on SrSnP (SG:129) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ErNbO4 (SG:15) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ti2Be17 (SG:166) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Pr2SO2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Yb2SO2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TiCo2Sn (SG:225) by Materials Project

DOE Data Explorer

Kristin Persson

2015-02-09

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ni2P (SG:189) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PuCo3 (SG:166) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TbGaPd (SG:62) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on BaTiO3 (SG:123) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PrNbO4 (SG:15) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Er2SO2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on LuB6 (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Bi2O3 (SG:224) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Cd3In (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Lu2SO2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Mn3O4 (SG:141) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on FeClO (SG:59) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on U2Se3 (SG:62) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Tb2SO2 (SG:164) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on AlPt3 (SG:221) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Mn2Nb (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on TaBe12 (SG:139) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on FeS2 (SG:58) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ni12P5 (SG:87) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on ThRe2 (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on PuGe2 (SG:141) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on YCrO3 (SG:62) by Materials Project

DOE Data Explorer

Kristin Persson

2014-11-02

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

Materials Data on Ni3Sn (SG:194) by Materials Project

DOE Data Explorer

Kristin Persson

2015-01-27

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations