Rare Earth based Sol-Gel Materials: An Intra- and Inter- Collegiate Collaborative Research Project
NASA Astrophysics Data System (ADS)
Silversmith, Ann
2004-03-01
Sol-gel glasses containing rare earth (RE) impurities form an exciting class of new optical materials with potential uses as phosphors and solid state laser media. The low temperature glass synthesis based on the liquid organic precursor tetramethoxysilane allows incorporation of higher RE concentrations than in traditional melt glasses without compromising the amorphous character of the material. The synthesis and spectroscopic characterization of these materials have together formed the basis for a fruitful interdisciplinary and multi-institutional research collaboration. All materials used in this project are made by Hamilton College chemistry students; spectroscopy experiments are performed by students and faculty in the physics departments at Hamilton, Franklin and Marshall, and Davidson Colleges. In this talk results from two ongoing spectroscopic investigations will be presented, both connected to the long-term goal of improving the low fluorescence efficiency of these materials. The first is the chelation of the RE metal to create an enhanced fluorescence excitation path and to physically separate the RE from the sol-gel matrix. Chelating molecules absorb strongly in the uv, and subsequent energy transfer can produce intense visible emission from the RE. Results are presented for the chelating agent 2,6-pyridine-dicarboxylic acid (PDC) bound to europium ions and incorporated into gels. Red emission from europium follows excitation into the PDC absorption band below 300nm. The second investigation focuses on fluorescence quenching of blue emission from trivalent terbium. Two separate mechanisms -energy transfer from terbium to residual hydroxide ions and among terbium ions - lead to reduced intensity of the blue emission lines relative to other longer wavelength signals.
Rare Isotope Accelerator (RIA) Project
NASA Astrophysics Data System (ADS)
York, R. C.
2006-07-01
The proposed Rare Isotope Accelerator (RIA) Project will provide world-class intensities of radioactive beams created by any of the known production mechanisms. A driver linac will be used to accelerate any stable isotope from protons through uranium to energies of ⩾400 MeV/u and intensities of ⩾100 kW. Lighter elements will be used to produce radioactive ion beams by the isotope separation on line (ISOL) method. Typically heavier elements will be used to produce radioactive ion beams by the particle fragmentation (PF) method. A hybrid method of stopping radioactive ion beams produced by the PF method in a gas cell will also be employed. The RIA project has strong support from the nuclear science community as evidenced by RIA being the highest priority for major new construction in the most recent Nuclear Science Advisory Committee (NSAC) Long Range Plan [2002 NSAC Long-Range Plan: Opportunities in Nuclear Science, A long-range plan for the next decade, April 2002]. In addition, RIA is tied for third position for the near term priorities of the Department of Energy (DoE) 20-year plan [DOE Office of Science, Facilities for the future of science: a twenty-year outlook. http://www.sc.doe.gov/Sub/Facilities_for_future/facilities_future.htm]. The status of the RIA design is presented.
The rare isotope accelerator (RIA) facility project
Christoph Leemann
2000-08-01
The envisioned Rare-Isotope Accelerator (RIA) facility would add substantially to research opportunities for nuclear physics and astrophysics by combining increased intensities with a greatly expanded variety of high-quality rare-isotope beams. A flexible superconducting driver linac would provide 100 kW, 400 MeV/nucleon beams of any stable isotope from hydrogen to uranium onto production targets. Combinations of projectile fragmentation, target fragmentation, fission, and spallation would produce the needed broad assortment of short-lived secondary beams. This paper describes the project's background, purpose, and status, the envisioned facility, and the key subsystem, the driver linac. RIA's scientific purposes are to advance current theoretical models, reveal new manifestations of nuclear behavior, and probe the limits of nuclear existence [3]. Figures 1 and 2 show, respectively, examples of RIA research opportunities and the yields projected for pursuing them. Figure 3 outlines a conceptual approach for delivering the needed beams.
NASA Astrophysics Data System (ADS)
Aourag, H.
2008-09-01
In the past, the search for new and improved materials was characterized mostly by the use of empirical, trial- and-error methods. This picture of materials science has been changing as the knowledge and understanding of fundamental processes governing a material's properties and performance (namely, composition, structure, history, and environment) have increased. In a number of cases, it is now possible to predict a material's properties before it has even been manufactured thus greatly reducing the time spent on testing and development. The objective of modern materials science is to tailor a material (starting with its chemical composition, constituent phases, and microstructure) in order to obtain a desired set of properties suitable for a given application. In the short term, the traditional "empirical" methods for developing new materials will be complemented to a greater degree by theoretical predictions. In some areas, computer simulation is already used by industry to weed out costly or improbable synthesis routes. Can novel materials with optimized properties be designed by computers? Advances in modelling methods at the atomic level coupled with rapid increases in computer capabilities over the last decade have led scientists to answer this question with a resounding "yes'. The ability to design new materials from quantum mechanical principles with computers is currently one of the fastest growing and most exciting areas of theoretical research in the world. The methods allow scientists to evaluate and prescreen new materials "in silico" (in vitro), rather than through time consuming experimentation. The Materials Genome Project is to pursue the theory of large scale modeling as well as powerful methods to construct new materials, with optimized properties. Indeed, it is the intimate synergy between our ability to predict accurately from quantum theory how atoms can be assembled to form new materials and our capacity to synthesize novel materials atom
Red and brown muds are the secondary materials generated from the extraction of alumina from bauxite, an aluminum-containing sedimentary rock (Ref. 2). Phosphogypsum is the secondary material generated by the phosphorous fertilizer industry from phosphate-containing sedimentary ...
Material efficiency: rare and critical metals.
Ayres, Robert U; Peiró, Laura Talens
2013-03-13
In the last few decades, progress in electronics, especially, has resulted in important new uses for a number of geologically rare metals, some of which were mere curiosities in the past. Most of them are not mined for their own sake (gold, the platinum group metals and the rare Earth elements are exceptions) but are found mainly in the ores of the major industrial metals, such as aluminium, copper, zinc and nickel. We call these major metals 'attractors' and the rare accompanying metals 'hitch-hikers'. The key implication is that rising prices do not necessarily call forth greater output because that would normally require greater output of the attractor metal. We trace the geological relationships and the functional uses of these metals. Some of these metals appear to be irreplaceable in the sense that there are no known substitutes for them in their current functional uses. Recycling is going to be increasingly important, notwithstanding a number of barriers. PMID:23359734
Cryogenics for the Rare Isotope Accelerator project
J. R. Specht; W. C. Chronis
2002-05-10
With 600 meters of superconducting accelerator, the Rare Isotope Accelerator (RIA) facility will have an extensive cryogenic system operating at both 2.0 K and 4.4 K. Approximately 250 4.4 K resonators, 200 2.0 K resonators, 160 4.4 K magnets, and several 4.4 K bunchers will be used in a 1.4-GV superconducting CW driver linac. Ion beams ranging from protons (up to 900 MeV) to uranium (up to 400 MeV per nucleon) at beam powers up to 400 kW will be produced. The facility will also have a superconducting linac to accelerate short-lived rare isotopes produced by the driver. This post accelerator is composed of another 100 superconducting resonators and associated superconducting focusing magnets. Liquid helium will also be provided to a variety of experimental instruments including, for example, large superconducting magnetic spectrographs. Overall, the liquid helium refrigerator will need to provide approximately 8.6 kW of cooling at 2.0 K, 4.8 kW at 4.4 K, and 15.3 kW at 35 K for shield cooling. A review of the various loads, cryostats, distribution system, and refrigeration schemes will be presented along with some special needs for reliable operation.
Materials Project: A Materials Genome Approach
Ceder, Gerbrand [MIT; Persson, Kristin [LBNL
Technological innovation - faster computers, more efficient solar cells, more compact energy storage - is often enabled by materials advances. Yet, it takes an average of 18 years to move new materials discoveries from lab to market. This is largely because materials designers operate with very little information and must painstakingly tweak new materials in the lab. Computational materials science is now powerful enough that it can predict many properties of materials before those materials are ever synthesized in the lab. By scaling materials computations over supercomputing clusters, this project has computed some properties of over 80,000 materials and screened 25,000 of these for Li-ion batteries. The computations predicted several new battery materials which were made and tested in the lab and are now being patented. By computing properties of all known materials, the Materials Project aims to remove guesswork from materials design in a variety of applications. Experimental research can be targeted to the most promising compounds from computational data sets. Researchers will be able to data-mine scientific trends in materials properties. By providing materials researchers with the information they need to design better, the Materials Project aims to accelerate innovation in materials research.[copied from http://materialsproject.org/about] You will be asked to register to be granted free, full access.
New Trends in Cataloging Rare and Special Materials.
ERIC Educational Resources Information Center
Leslie, Deborah J.
2003-01-01
Reports on the American Library Association's efforts to update the Descriptive Cataloging of Rare Materials (DCRM). Describes topics of working groups that include transcription of early letter forms, rare book cataloging of machine-press books, collection-level cataloging, problems and lacunae, and varieties of editions and issues and when to…
Replacing critical rare earth materials in high energy density magnets
NASA Astrophysics Data System (ADS)
McCallum, R. William
2012-02-01
High energy density permanent magnets are crucial to the design of internal permanent magnet motors (IPM) for hybride and electric vehicles and direct drive wind generators. Current motor designs use rare earth permanent magnets which easily meet the performance goals, however, the rising concerns over cost and foreign control of the current supply of rare earth resources has motivated a search for non-rare earth based permanent magnets alloys with performance metrics which allow the design of permanent magnet motors and generators without rare earth magnets. This talk will discuss the state of non-rare-earth permanent magnets and efforts to both improve the current materials and find new materials. These efforts combine first principles calculations and meso-scale magnetic modeling with advance characterization and synthesis techniques in order to advance the state of the art in non rare earth permanent magnets. The use of genetic algorithms in first principle structural calculations, combinatorial synthesis in the experimental search for materials, atom probe microscopy to characterize grain boundaries on the atomic level, and other state of the art techniques will be discussed. In addition the possibility of replacing critical rare earth elements with the most abundant rare earth Ce will be discussed.
Assessment of material radiopurity for Rare Event experiments using Micromegas
NASA Astrophysics Data System (ADS)
Aznar, F.; Castel, J.; Cebrián, S.; Dafni, T.; Diago, A.; García, J. A.; Garza, J. G.; Gómez, H.; González-Díaz, D.; Herrera, D. C.; Iguaz, F. J.; Irastorza, I. G.; Luzón, G.; Mirallas, H.; Oliván, M. A.; Ortiz de, A.; Solórzano; Pons, P.; Rodríguez, A.; Ruiz, E.; Seguí, L.; Tomás, A.; Villar, J. A.
2013-11-01
Micromesh gas amplification structures (Micromegas) can be used as readout of Time Projection Chambers in the field of Rare Event searches dealing with dark matter, double beta decay or solar axions. The topological information of events offered by these gaseous detectors is a very powerful tool for signal identification and background rejection. However, in this kind of experiments the radiopurity of the detector components and surrounding materials must be thoroughly controlled in addition in order to keep the experimental background as low as possible. A screening program based mainly on gamma-ray spectrometry using an ultra-low background HPGe detector in the Canfranc Underground Laboratory is being developed for several years, with the aim to measure the activity levels of materials used in the Micromegas planes and also in other components involved in a plausible experimental set-up: gas vessel, field cage, electronic boards, calibration system or shielding. The techniques and equipment used in these measurements will be described and the main results will be presented and discussed. In particular, first results for the activity of Micromegas readouts of the microbulk type produced at CERN indicate that they are already comparable to the cleanest readout systems in low background experiments and it should be possible to further improve these levels after dedicated development.
Rare earth elements exploitation, geopolitical implications and raw materials trading
NASA Astrophysics Data System (ADS)
Chemin, Marie-Charlotte
2015-04-01
Rare earth elements (REE) correspond to seventeen elements of the periodic table. They are used in high technology, cracking, electric cars' magnet, metal alloy for batteries, and also in phone construction or ceramics for electronic card. REEs are an important resource for high technology. This project targets 16 years old students in the subject "personalized aid" and will last six weeks. The purpose of this project is to develop autonomy and research in groups for a transdisciplinary work. This project gathers knowledge in geology, geography and economics. During the first session students analyze the geology applications of the REE. They begin the analysis with learning the composition in different rocks such as basalt and diorite to make the link with crystallization. Then they compare it with adakite to understand the formation of these rocks. In the second session, they study REE exploitation. We can find them as oxides in many deposits. The principal concentrations of rare earth elements are associated with uncommon varieties of igneous rocks, such as carbonatites. They can use Qgis, to localize this high concentration. In the third session, they study the environmental costs of REE exploitation. Indeed, the exploitation produces thorium and carcinogenic toxins: sulphates, ammonia and hydrochloric acid. Processing one ton of rare earths produces 2,000 tons of toxic waste. This session focuses, first, on Baotou's region, and then on an example they are free to choose. In the fourth session, they study the geopolitical issues of REE with a focus on China. In fact this country is the largest producer of REE, and is providing 95% of the overall production. REE in China are at the center of a geopolitical strategy. In fact, China implements a sort of protectionism. Indeed, the export tax on REE is very high so, as a foreign company, it is financially attractive to establish a manufacturing subsidiary in China in order to use REE. As a matter of fact
Projection transparencies from printed material
NASA Technical Reports Server (NTRS)
Grunewald, L. S.; Nickerson, T. B.
1968-01-01
Method for preparing project transparencies, or view graphs, permits the use of almost any expendable printed material, pictures, charts, or text, in unlimited color or black and white. The method can be accomplished by either of two techniques, with a slight difference in materials.
Determination of rare and radioactive elements in mineral raw materials
NASA Astrophysics Data System (ADS)
Ostroumov, G. V.
Methods are presented for determining scandium, rare earths, zirconium, hafnium, niobium, tantalum, molybdenum, tungsten, rhenium, as well as uranium, radium, thorium, and their isotopes in mineral raw materials. Geological, mineralogical, and analytical characteristics are given for each of the above elements. The analytical methods discussed here include neutron activation analysis, spectrography, gravimetry, photometry, titration, and electrochemical analysis. Optimum regions are defined for each of these methods. No individual items are abstracted in this volume
Development of rare earth regenerator materials in fine wire form
Wong, T.; Seuntjens, J.M.
1997-06-01
The use of rare earth metals, both in the pure and alloyed state, have been examined for use as regenerators in cryocooler applications and as the working material in active magnetic refrigerators. In both applications there is a requirement for the rare earth material to have a constant and uniform cross section, an average size on the order of 50-200 microns in diameter, and low levels of impurities. Existing powder production methods have drawbacks such as oxygen contamination, non-uniform size, inconsistent cross sections, and low production yields. A novel approach for the production of rare earth metals and alloys in fine wire form has been developed. This is accomplished by assembling a copperjacket and niobium barrier around a RE ingot, extruding the assembly, and reducing it with standard wire drawing practices. Strand anneals are utilized between drawing passes when necessary in order to recrystallize the RE core and restore ductility. The copperjacket is removed by chemical means at final size, leaving the Nb barrier in place as a protective coating. This process has been applied to gadolinium, dysprosium and a GdDy alloy.
Accurate projected augmented wave (PAW) datasets for rare-earth elements (RE=La-Lu)
NASA Astrophysics Data System (ADS)
Topsakal, Mehmet; Wentzcovitch, Renata
2015-03-01
We provide accurate projected augmented wave (PAW) datasets for rare-earth (RE) elements with some suggested Hubbard U values allowing efficient plane-wave calculations. Solid state tests of generated datasets were performed on rare-earth nitrides. Through density of state (DOS) and equation of state (EoS) comparisons, generated datasets were shown to yield excellent results comparable to highly accurate all-electron full-potential linearized augmented plane-wave plus local orbital (FLAPW+LO) calculations. Hubbard U values for trivalent RE ions are determined according to hybrid functional calculations. We believe that these new and open-source PAW datasets will allow further studies on rare-earth materials. NSF/EAR 1319361
Large Time Projection Chambers for Rare Event Detection
Heffner, M
2009-11-03
The Time Projection Chamber (TPC) concept [add ref to TPC section] has been applied to many projects outside of particle physics and the accelerator based experiments where it was initially developed. TPCs in non-accelerator particle physics experiments are principally focused on rare event detection (e.g. neutrino and darkmater experiments) and the physics of these experiments can place dramatically different constraints on the TPC design (only extensions to the traditional TPCs are discussed here). The drift gas, or liquid, is usually the target or matter under observation and due to very low signal rates a TPC with the largest active mass is desired. The large mass complicates particle tracking of short and sometimes very low energy particles. Other special design issues include, efficient light collection, background rejection, internal triggering and optimal energy resolution. Backgrounds from gamma-rays and neutrons are significant design issues in the construction of these TPCs. They are generally placed deep underground to shield from cosmogenic particles and surrounded with shielding to reduce radiation from the local surroundings. The construction materials have to be carefully screened for radiopurity as they are in close contact with the active mass and can be a signification source of background events. The TPC excels in reducing this internal background because the mass inside the fieldcage forms one monolithic volume from which fiducial cuts can be made ex post facto to isolate quiet drift mass, and can be circulated and purified to a very high level. Self shielding in these large mass systems can be significant and the effect improves with density. The liquid phase TPC can obtain a high density at low pressure which results in very good self-shielding and compact installation with a lightweight containment. The down sides are the need for cryogenics, slower charge drift, tracks shorter than the typical electron diffusion, lower energy resolution (e
Material and Energy Requirement for Rare Earth Production
NASA Astrophysics Data System (ADS)
Talens Peiró, Laura; Villalba Méndez, Gara
2013-10-01
The use of rare earth metals (REMs) for new applications in renewable and communication technologies has increased concern about future supply as well as environmental burdens associated with the extraction, use, and disposal (losses) of these metals. Although there are several reports describing and quantifying the production and use of REM, there is still a lack of quantitative data about the material and energy requirements for their extraction and refining. Such information remains difficult to acquire as China is still supplying over 95% of the world REM supply. This article attempts to estimate the material and energy requirements for the production of REM based on the theoretical chemical reactions and thermodynamics. The results show the material and energy requirement varies greatly depending on the type of mineral ore, production facility, and beneficiation process selected. They also show that the greatest loss occurs during mining (25-50%) and beneficiation (10-30%) of RE minerals. We hope that the material and energy balances presented in this article will be of use in life cycle analysis, resource accounting, and other industrial ecology tools used to quantify the environmental consequences of meeting REM demand for new technology products.
Impurity-sensitized luminescence of rare earth-doped materials
Smentek, Lidia . E-mail: smentek1@aol.com
2005-02-15
The accuracy of the theoretical model of impurity-sensitized luminescence in rare earth-doped materials presented here is adjusted to the demands of precise modern experimental techniques. The description is formulated within the double perturbation theory, and it is based on the assumption that electrostatic interactions between the subsystems that take part in the luminescence process are the most important ones. The amplitude of the energy transfer is determined by the contributions that represent the perturbing influence of the crystal-field potential and also electron correlation effects taken into account within the rare earth ions. In this way, the model is defined beyond the standard free ionic system and single configuration approximations. The new contributions to the energy transfer amplitude are expressed in the terms of effective tensor operators, and they contain the perturbing influence of various excited configurations. In order to maintain the high accuracy of the model, the radial integrals of all effective operators are defined within the so-called perturbed function approach. This means that they are evaluated for the complete radial basis sets of one electron functions of given symmetry, including the continuum.
Rare earth elements materials production from apatite ores
NASA Astrophysics Data System (ADS)
Anufrieva, A. V.; Andrienko, O. S.; Buynovskiy, A. S.; Makaseev, Y. N.; Mazov, I. N.; Nefedov, R. A.; Sachkov, V. I.; Stepanova, O. B.; Valkov, A. V.
2016-01-01
The paper deals with the study of processing apatite ores with nitric acid and extraction of the rare earth elements. The rare earth elements can be successfully separated and recovered by extraction from the nitrate- phosphate solution, being an tributyl phosphate as extraction agent. The developed scheme of the processing apatite concentrate provides obtaining rare earth concentrates with high qualitative characteristics.
Effect of rare earth substitution in cobalt ferrite bulk materials
NASA Astrophysics Data System (ADS)
Bulai, G.; Diamandescu, L.; Dumitru, I.; Gurlui, S.; Feder, M.; Caltun, O. F.
2015-09-01
The study was focused on the influence of small amounts of rare earth (RE=La, Ce, Sm, Gd, Dy, Ho, Er, Yb) addition on the microstructure, phase content and magnetic properties of cobalt ferrite bulk materials. The X-Ray diffraction measurements confirmed the formation of the spinel structure but also the presence of secondary phases of RE oxides or orthoferrite in small percentages (up to 3%). Density measurements obtained by Archimedes method revealed a ~1 g cm-3 decrease for the RE doped cobalt ferrite samples compared with stoichiometric one. Both the Mössbauer and Fourier Transform Infrared Spectrocopy analysis results confirmed the formation of the spinel phase. The saturation magnetization and coercive field values of the doped samples obtained by Vibrating Sample Magnetometry were close to those of the pure cobalt ferrite. For magnetostrictive property studies the samples were analyzed using the strain gauge method. Higher maximum magnetostriction coefficients were found for the Ho, Ce, Sm and Yb doped cobalt ferrite bulk materials as related to the stoichiometric CoFe2O4 sample. Moreover, improved strain derivative was observed for these samples but at higher magnetic fields due to the low increase of the coercive field values for doped samples.
Recent developments of rare-earth-free hard-magnetic materials
NASA Astrophysics Data System (ADS)
Li, Da; Pan, DeSheng; Li, ShaoJie; Zhang, ZhiDong
2016-01-01
Recent advances in rare-earth-free hard-magnetic materials including magnetic bulk, thin films, nanocomposites and nanostructures are introduced. Since the costs of the rare-earth metals boosts up the price of the high-performance rare-earth permanent magnets, there is a much revived interest in various types of hard-magnetic materials based on rare-earth-free compounds. The 3d transition metals and their alloys with large coercivity and high Curie temperatures (working temperatures) are expected to overcome the disadvantages of rare-earth magnets. Making rare-earth-free magnets with a large energy product to meet tomorrow's energy needs is still a challenge.
CADMIUM-RARE EARTH BORATE GLASS AS REACTOR CONTROL MATERIAL
Ploetz, G.L.; Ray, W.E.
1958-11-01
A reactor control rod fabricated from a cadmiumrare earth-borate glass is presented. The rare earth component of this glass is selected from among those rare earths having large neutron capture cross sections, such as samarium, gadolinium or europium. Partlcles of this glass are then dispersed in a metal matrix by standard powder metallurgy techniques.
Rare earth-doped materials with enhanced thermoelectric figure of merit
Venkatasubramanian, Rama; Cook, Bruce Allen; Levin, Evgenii M.; Harringa, Joel Lee
2016-09-06
A thermoelectric material and a thermoelectric converter using this material. The thermoelectric material has a first component including a semiconductor material and a second component including a rare earth material included in the first component to thereby increase a figure of merit of a composite of the semiconductor material and the rare earth material relative to a figure of merit of the semiconductor material. The thermoelectric converter has a p-type thermoelectric material and a n-type thermoelectric material. At least one of the p-type thermoelectric material and the n-type thermoelectric material includes a rare earth material in at least one of the p-type thermoelectric material or the n-type thermoelectric material.
Independent Projects in a Materials Engineering Course
ERIC Educational Resources Information Center
Place, T. Alan
1976-01-01
Describes an advanced undergraduate materials science course in which each student conducts two independent laboratory projects and is required to submit a formal lab report at the end of each project. (MLH)
Rare isotope accelerator project in Korea and its application to high energy density sciences
NASA Astrophysics Data System (ADS)
Chung, M.; Chung, Y. S.; Kim, S. K.; Lee, B. J.; Hoffmann, D. H. H.
2014-01-01
As a national science project, the Korean government has recently established the Institute for Basic Science (IBS) with the goal of conducting world-class research in basic sciences. One of the core facilities for the IBS will be the rare isotope accelerator which can produce high-intensity rare isotope beams to investigate the fundamental properties of nature, and also to support a broad research program in material sciences, medical and biosciences, and future nuclear energy technologies. The construction of the accelerator is scheduled to be completed by approximately 2017. The design of the accelerator complex is optimized to deliver high average beam current on targets, and to maximize the production of rare isotope beams through the simultaneous use of Isotope Separation On-Line (ISOL) and In-Flight Fragmentation (IFF) methods. The proposed accelerator is, however, not optimal for high energy density science, which usually requires very high peak currents on the target. In this study, we present possible beam-plasma experiments that can be done within the scope of the current accelerator design, and we also investigate possible future extension paths that may enable high energy density science with intense pulsed heavy ion beams.
NEH Curriculum Integration Project: Selected Project Materials, 1981-1982.
ERIC Educational Resources Information Center
Arizona Univ., Tucson. Women's Studies Program.
Materials from a project to integrate the new research on women into the University of Arizona curriculum are divided into four sections. Section I, recruitment, contains a letter describing the project to prospective faculty participants and a list of questions used to interview faculty for participation in the project. Section II contains an…
Introductory Curriculum Materials, Project SCATE.
ERIC Educational Resources Information Center
Iowa State Dept. of Public Instruction, Des Moines. Div. of Curriculum.
The objective of Project SCATE (Students Concerned About Tomorrow's Environment) is for students to investigate environmental problems and the political processes involved in their solution. The four identified areas of concern are: (1) land use policy development; (2) air and water quality; (3) energy allocation and consumption; and (4) economic…
2012-01-01
REACT Project: The University of Alabama is developing new iron- and manganese-based composite materials for use in the electric motors of EVs and renewable power generators that will demonstrate magnetic properties superior to today’s best rare-earth-based magnets. Rare earths are difficult and expensive to refine. EVs and renewable power generators typically use rare earths to make their electric motors smaller and more powerful. The University of Alabama has the potential to improve upon the performance of current state-of-the-art rare-earth-based magnets using low-cost and more abundant materials such as manganese and iron. The ultimate goal of this project is to demonstrate improved performance in a full-size prototype magnet at reduced cost.
Methods and opportunities in the recycling of rare earth based materials
Ellis, T.W.; Schmidt, F.A.; Jones, L.L.
1994-10-01
Rare Earth based materials are increasingly being utilized in industrial and commercial practice. Large volume production of permanent magnet materials, Nd{sub 2}Fe{sub 14}B, SmCo{sub 5}, Sm{sub 2}Co{sub 17}, and rechargeable Ni/Metal Hydride batteries, LaNi{sub 5}, has increased the amount of rare earth based materials in the waste stream. Both for economic and environmental reasons, recycling and reuse of all materials is desirable. Unfortunately, the recycling methodology for these materials is in its infancy. In this paper the present {open_quotes}state of the art{close_quotes}, in recycling of rare earth based materials will be discussed. Additionally, new methods which alleviate many of the concerns of present aqueous based recycling technology will be presented.
Determination of contamination in rare earth materials by promptgamma activation analysis (PGAA)
Perry, D.L.; English, G.A.; Firestone, R.B.; Molnar, G.L.; Revay,Zs.
2004-11-09
Prompt gamma activation analysis (PGAA) has been used to detect and quantify impurities in the analyses of rare earth (RE) oxides. The analytical results are discussed with respect to the importance of having a thorough identification and understanding of contaminant elements in these compounds regarding the function of the materials in their various applications. Also, the importance of using PGAA to analyze materials in support of other physico-chemical studies of the materials is discussed, including the study of extremely low concentrations of ions such as the rare earth ions themselves in bulk material matrices.
Structural silicon nitride materials containing rare earth oxides
Andersson, Clarence A.
1980-01-01
A ceramic composition suitable for use as a high-temperature structural material, particularly for use in apparatus exposed to oxidizing atmospheres at temperatures of 400 to 1600.degree. C., is found within the triangular area ABCA of the Si.sub.3 N.sub.4 --SiO.sub.2 --M.sub.2 O.sub.3 ternary diagram depicted in FIG. 1. M is selected from the group of Yb, Dy, Er, Sc, and alloys having Yb, Y, Er, or Dy as one component and Sc, Al, Cr, Ti, (Mg +Zr) or (Ni+Zr) as a second component, said alloy having an effective ionic radius less than 0.89 A.
Rare Earth Element Fractionation During Evaporation of Chondritic Material
NASA Astrophysics Data System (ADS)
Wang, J.; Davis, A. M.; Clayton, R. N.
1993-07-01
Evaporation experiments suggest that enrichments in the heavy isotopes of oxygen, magnesium, and silicon in some CAIs are caused by kinetic effects during evaporation [1]. Volatility-fractionated REE patterns found in some CAIs have been modeled with some success using equilibrium thermodynamics [2,3], but little is known about kinetic effects on REE patterns. We have begun an investigation of REE fractionation under conditions where large isotope effects are produced by the kinetic isotope effect. We synthesized a starting material containing CI chondritic relative proportions of MgO, Al2O3, SiO2, CaO, TiO2, and FeO, and doped it with 100 ppm each of the REE. Samples of this material were evaporated in a vacuum furnace [4] at 10^-6 torr and 1800 or 2000 degrees C for periods of a few seconds to 5 hr. The mass fraction evaporated ranged from 7.6 to 95.4%. Most residues consist of olivine and glass. Chemical compositions of the residues were determined by electron and ion microprobe. Results for selected elements are shown in Fig. 1. There is no significant evaporation of Ca, Al, and Ti up to 95% mass loss; the evaporation behavior of Mg, Si, and Fe is similar to that found by Hashimoto [5]. There is no significant evaporation of most of the REE up to 95% mass loss. Ce is much more volatile than the other REE under these conditions: a tenfold negative Ce anomaly developed between 60 and 70% mass loss and the anomaly reached 5 X 10^-4 at 95% mass loss. A small Pr anomaly (50% Pr loss) also appeared in the highest-mass-loss residue. Thermodynamic calculations show that Ce has approximately the same volatility as other LREE under solar nebular oxygen fugacity, but is much more volatile than the other REE under oxidizing conditions [6]. We suspect that conditions in the residue in our vacuum evaporation experiments became oxidizing because evaporation reactions involving most major element oxides involve release of oxygen. The four known HAL-type hibonite
QA Activities on Two Large RARE Projects at the US EPA, RTP, NC ─ from Fish to Humans
Two RARE (Regional Applied Research Effort) projects are being managed by Janet Diliberto, Linda Birnbaum, and Thomas Hughes. Janet is the Project Officer, Linda is the science advisor and Thomas is the QA and Records Manager for these two RARE projects. These are high visibili...
Benedict, Lorin X.
2015-10-26
Hard permanent magnets in wide use typically involve expensive Rare Earth elements. In this effort, we investigated candidate permanent magnet materials which contain no Rare Earths, while simultaneously exploring improvements in theoretical methodology which enable the better prediction of magnetic properties relevant for the future design and optimization of permanent magnets. This included a detailed study of magnetocrystalline anisotropy energies, and the use of advanced simulation tools to better describe magnetic properties at elevated temperatures.
A Guide to Available Project English Materials.
ERIC Educational Resources Information Center
Butler, Donna, Ed.; O'Donnell, Bernard, Ed.
This guide is a collection of abstracts--most of them selected from English Curriculum Study and Demonstration Centers of the USOE English Program (Project English). It is intended to ease the announcement and distribution problems of the Centers by directing readers to the materials available from commercial or university publishers and from the…
Counterproliferation of nuclear raw materials. Study project
Sanders, R.L.
1996-02-26
In light of the ongoing INF and START I agreements and the pending ratification of the START II agreement, the quantities of nuclear-weapon-usable `fissile` materials from the former USSR will expand drastically. Some newly rich rogue oil states and terrorist groups with anti-U.S. sentiments may attempt to procure fissile materials in order to manufacture nuclear weapons. This project will explore the scope of the fissile material proliferation problem, describe a number of recent cases where fissile material was illegally diverted, and discuss the U.S. policies, methods and means available to halt or reduce the spread of weapons-usable nuclear material. Finally, it provides recommendations for improvements in the U.S. program and for areas meriting further study.
ERIC Educational Resources Information Center
Bouche, Nicole
This paper reports on a project that involved the digitization of manuscripts from the Boswell Collection (i.e., personal papers of James Boswell) by the Beinecke Rare Book and Manuscript Library at Yale University (Connecticut). In this case, the digitization process was designed to serve a group of scholars already at work on a publication…
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
NASA Astrophysics Data System (ADS)
Jain, Anubhav; Ong, Shyue Ping; Hautier, Geoffroy; Chen, Wei; Richards, William Davidson; Dacek, Stephen; Cholia, Shreyas; Gunter, Dan; Skinner, David; Ceder, Gerbrand; Persson, Kristin A.
2013-07-01
Accelerating the discovery of advanced materials is essential for human welfare and sustainable, clean energy. In this paper, we introduce the Materials Project (www.materialsproject.org), a core program of the Materials Genome Initiative that uses high-throughput computing to uncover the properties of all known inorganic materials. This open dataset can be accessed through multiple channels for both interactive exploration and data mining. The Materials Project also seeks to create open-source platforms for developing robust, sophisticated materials analyses. Future efforts will enable users to perform ``rapid-prototyping'' of new materials in silico, and provide researchers with new avenues for cost-effective, data-driven materials design.
PREFACE: IUMRS-ICA 2008 Symposium 'AA. Rare-Earth Related Material Processing and Functions'
NASA Astrophysics Data System (ADS)
Komatsu, Takayuki; Sato, Tsugio; Machida, Ken-ichi; Fukunaga, Hirotoshi
2009-02-01
Rare-earth related materials have been widely used in various advanced technologies and devices because of their novel functions such as excellent magnetic and optical properties. For the fabrication of the next generation of new rare-earth related materials with novel functions, it is necessary to design a wide range of materials from nano-scale to macro-scale and to develop novel techniques realizing such designs. Indeed, there has been great progress in the preparation, processing and characterization of new rare-earth materials covering magnetic alloys, inorganic and organic fluorescence materials. In the International Union of Materials Research Societies International Conference in Asia 2008 (IUMRS-ICA2008) (9-13 December, Nagoya, Japan), the symposium on 'AA: Rare-Earth Related Material Processing and Functions' was organized to provide an interdisciplinary forum for the discussion of recent advances in fabrication processing and applications of rare-earth related materials with various scaled and unique morphologies. Many papers were presented in the symposium, and some papers were accepted to be published in this proceeding after review. Editors: Takayuki KOMATSU (Nagaoka University of Technology, Japan) Tsugio SATO (Tohoku University, Japan) Ken-ichi MACHIDA (Osaka University, Japan) Hirotoshi FUKUNAGA (Nagasaki University, Japan) Jiro YAMASAKI (Kyushu Institute of Technology, Japan) Honjie ZHANG (Chinese Academy of Sciences, China) Chun Hua YAN (Peking University, China) Jianrong QIU (Zhejiang University, China) Jong HEO (Pohang University, Korea) Setsuhisa TANABE (Kyoto University, Japan) Hiroshi TATEWAKI (Nagoya City University, Japan) Tomokatsu HAYAKAWA (Nagoya Institute of Technology, Japan) Yasufumi FUJIWARA (Osaka University, Japan)
Legacy material work-off project
Sloan, T.J.; Baker, D.H. IV
1999-01-25
Los Alamos National Laboratory (LANL) and its subcontractors recently completed a nine-month legacy material clean-up effort. Legacy materials were defined as chemicals, hazardous, non-hazardous, and both hazardous and radioactive (mixed), that no longer served a programmatic use and had no identified individual owner within the Laboratory. Once personnel identified the legacy materials, the items were transferred to Solid Waste Operation`s (EM-SWO) control. Upon completing this process, the responsible division-level manager was required to certify that all non-radioactive hazardous and non-hazardous materials and acceptable mixed legacy materials had been identified and transferred to EM-SWO for proper handling or disposal. The major expense in this project was the cost of actual chemical and radiological analysis. This expense was the result of items not having an identified individual owner. The major benefit of this project is that LANL is now in an excellent position to implement its Integrated Safety Management (ISM) Plan, which requires the implementation of safe work practices, including requirements for removing unused items when vacating workspaces. Effective implementation of ISM will go a long way toward ensuring that legacy materials are no longer an issue at the Laboratory.
Mirror symmetric optics design for charge-stripping section in Rare Isotope Science Project
NASA Astrophysics Data System (ADS)
Kim, Hye-Jin; Kim, Hyung-Jin; Jeon, Dong-O.; Hwang, Ji-Gwang; Kim, Eun-San
2013-12-01
The main aim of the Rare Isotope Science Project is to construct a high power heavy-ion accelerator based on the superconducting linear accelerator (SCL). The heavy ion accelerator is a key research facility that will allow ground-breaking research into numerous facets of basic science, such as nuclear physics, astrophysics, atomic physics, life science, medicine and material science. The machine will provide a beam power of 400 kW with a 238U79+ beam of 8 pμA and 200 MeV/u. One of the critical components in the SCL is the charge stripper between the two segments, SCL1 and SCL2, of the SCL. The charge stripper removes electrons from the ion beams to enhance the acceleration efficiency in the subsequent SCL2. To improve the efficiency of acceleration and power in SCL2, the optimal energy of stripped ions in a solid carbon foil stripper was estimated using the code LISE++. The thickness of the solid carbon foil was 300 μg/m2. The charge stripping efficiency of the solid carbon stripper in the present study was approximately 87%. For charge selection from the ions produced by the solid carbon stripper, a dispersive section is needed down-stream of the foil. The designed optics for the dispersive section is based on the mirror-symmetric optics to minimize the effect of high-order aberrations.
2012-01-01
REACT Project: Northeastern University will develop bulk quantities of rare-earth-free permanent magnets with an iron-nickel crystal structure for use in the electric motors of renewable power generators and EVs. These materials could offer magnetic properties that are equivalent to today’s best commercial magnets, but with a significant cost reduction and diminished environmental impact. This iron-nickel crystal structure, which is only found naturally in meteorites and developed over billions of years in space, will be artificially synthesized by the Northeastern University team. Its material structure will be replicated with the assistance of alloying elements introduced to help it achieve superior magnetic properties. The ultimate goal of this project is to demonstrate bulk magnetic properties that can be fabricated at the industrial scale.
Liang, Jinsheng; Zhu, Dongbin; Meng, Junping; Wang, Lijuan; Li, Fenping; Liu, Zhiguo; Ding, Yan; Liu, Lihua; Liang, Guangchuan
2008-03-01
Rare earth mineral composite materials were prepared using tourmaline and cerous nitrate as raw materials. Through characterization by scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, dynamic contact angle meter and tensiometer, and Fourier transform infrared spectroscopy, it was found that the composite materials had a better far infrared emitting performance than tourmaline, which depended on many factors such as material composition, microstructure, and surface free energy. Based on the results of the flue gas analyzer and the water boiling test, it was found that the rare earth mineral composite materials could accelerate the combustion of liquefied petroleum gas and diesel oil. The results showed that the addition of Ce led to the improvement of far infrared emitting performance of tourmaline due to the decrease of cell volume caused by the oxidation of more Fe2+ ions and the increase of surface free energy. The application of rare earth mineral composite materials to diesel oil led to a decrease in surface tension and flash point, and the fuel saving ratio could reach 4.5%. When applied to liquefied petroleum gas, the composite materials led to the enhanced combustion, improved fuel consumption by 6.8%, and decreased concentration of CO and O2 in exhaust gases by 59.7% and 16.2%, respectively; but the temperature inside the flue increased by 10.3%. PMID:18468124
Catalytic Graphitization of Coal-Based Carbon Materials with Light Rare Earth Elements.
Wang, Rongyan; Lu, Guimin; Qiao, Wenming; Yu, Jianguo
2016-08-30
The catalytic graphitization mechanism of coal-based carbon materials with light rare earth elements was investigated using X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, selected-area electron diffraction, and high-resolution transmission electron microscopy. The interface between light rare earth elements and carbon materials was carefully observed, and two routes of rare earth elements catalyzing the carbon materials were found: dissolution-precipitation and carbide formation-decomposition. These two simultaneous processes certainly accelerate the catalytic graphitization of carbon materials, and light rare earth elements exert significant influence on the microstructure and thermal conductivity of graphite. Moreover, by virtue of praseodymium (Pr), it was found that a highly crystallographic orientation of graphite was induced and formed, which was reasonably attributed to the similar arrangements of the planes perpendicular to (001) in both graphite and Pr crystals. The interface between Pr and carbon was found to be an important factor for the orientation of graphite structure. PMID:27482724
Computational search for rare-earth free hard-magnetic materials
NASA Astrophysics Data System (ADS)
Flores Livas, José A.; Sharma, Sangeeta; Dewhurst, John Kay; Gross, Eberhard; MagMat Team
2015-03-01
It is difficult to over state the importance of hard magnets for human life in modern times; they enter every walk of our life from medical equipments (NMR) to transport (trains, planes, cars, etc) to electronic appliances (for house hold use to computers). All the known hard magnets in use today contain rare-earth elements, extraction of which is expensive and environmentally harmful. Rare-earths are also instrumental in tipping the balance of world economy as most of them are mined in limited specific parts of the world. Hence it would be ideal to have similar characteristics as a hard magnet but without or at least with reduced amount of rare-earths. This is the main goal of our work: search for rare-earth-free magnets. To do so we employ a combination of density functional theory and crystal prediction methods. The quantities which define a hard magnet are magnetic anisotropy energy (MAE) and saturation magnetization (Ms), which are the quantities we maximize in search for an ideal magnet. In my talk I will present details of the computation search algorithm together with some potential newly discovered rare-earth free hard magnet. J.A.F.L. acknowledge financial support from EU's 7th Framework Marie-Curie scholarship program within the ``ExMaMa'' Project (329386).
Application of far infrared rare earth mineral composite materials to liquefied petroleum gas.
Zhu, Dongbin; Liang, Jinsheng; Ding, Yan; Xu, Anping
2010-03-01
Far infrared rare earth mineral composite materials were prepared by the coprecipitation method using tourmaline, cerium acetate, and lanthanum acetate as raw materials. The results of Fourier transform infrared spectroscopy show that tourmaline modified with the rare earths La and Ce has a better far infrared emitting performance. Through XRD analysis, we attribute the improved far infrared emission properties of the tourmaline to the unit cell shrinkage of the tourmaline arising from La enhancing the redox properties of nano-CeO2. The effect of the composite materials on the combustion of liquefied petroleum gas (LPG) was studied by the flue gas analysis and water boiling test. Based on the results, it was found that the composite materials could accelerate the combustion of LPG, and that the higher the emissivity of the rare earth mineral composite materials, the better the effects on combustion of LPG. In all activation styles, both air and LPG to be activated has a best effect, indicating the activations having a cumulative effect. PMID:20355556
The LUCIFER project and production issues for crystals needed in rare events physics experiments
NASA Astrophysics Data System (ADS)
Dafinei, I.
2014-05-01
The detection of elusive particles and in general the construction of detectors with high sensitivity for applications in the physics of rare events requires the use of new high quality crystals with enhanced characteristics. The production of such materials often depends upon the application of dedicated methods for the entire production process from synthesis of raw materials up to the storage and transport of the finished product ready for use for the construction of the particle detector. Cryogenic bolometers and the more sophisticated scintillating bolometers are among the most promising detectors used in rare event physics, particularly in Neutrinoless Double Beta Decay (0νDBD) experiments. Operated at extremely low temperatures (≈10 mK) such devices need high purity crystals with a very high crystal perfection and low level of intrinsic radioactivity. Moreover, in the case of 0νDBD application, the crystal requires the presence of the nuclide of interest in a sufficient amount i.e. isotope enriched materials are employed. The current work reviews scientific and technological aspects related to the crystal production for rare events physics experiments, particularly for bolometric application. In the case of enriched isotopes used in 0νDBD experiments, the problems related to a maximum production yield are stressed. The discussion is illustrated with results obtained in the activities connected to the procurement of ZnSe crystals for the experiment Low-background Underground Cryogenic Installation For Elusive Rates (LUCIFER).
Materials dispersion and biodynamics project research
NASA Technical Reports Server (NTRS)
Lewis, Marian L.
1992-01-01
The Materials Dispersion and Biodynamics Project (MDBP) focuses on dispersion and mixing of various biological materials and the dynamics of cell-to-cell communication and intracellular molecular trafficking in microgravity. Research activities encompass biomedical applications, basic cell biology, biotechnology (products from cells), protein crystal development, ecological life support systems (involving algae and bacteria), drug delivery (microencapsulation), biofilm deposition by living organisms, and hardware development to support living cells on Space Station Freedom (SSF). Project goals are to expand the existing microgravity science database through experiments on sounding rockets, the Shuttle, and COMET program orbiters and to evolve,through current database acquisition and feasibility testing, to more mature and larger-scale commercial operations on SSF. Maximized utilization of SSF for these science applications will mean that service companies will have a role in providing equipment for use by a number of different customers. An example of a potential forerunner of such a service for SSF is the Materials Dispersion Apparatus (MDA) 'mini lab' of Instrumentation Technology Associates, Inc. (ITA) in use on the Shuttle for the Commercial MDAITA Experiments (CMIX) Project. The MDA wells provide the capability for a number of investigators to perform mixing and bioprocessing experiments in space. In the area of human adaptation to microgravity, a significant database has been obtained over the past three decades. Some low-g effects are similar to Earth-based disorders (anemia, osteoporosis, neuromuscular diseases, and immune system disorders). As new information targets potential profit-making processes, services and products from microgravity, commercial space ventures are expected to expand accordingly. Cooperative CCDS research in the above mentioned areas is essential for maturing SSF biotechnology and to ensure U.S. leadership in space technology
Pamela M. Kinsey
2015-09-30
The work evaluates, develops and demonstrates flexible, scalable mineral extraction technology for geothermal brines based upon solid phase sorbent materials with a specific focus upon rare earth elements (REEs). The selected organic and inorganic sorbent materials demonstrated high performance for collection of trace REEs, precious and valuable metals. The nanostructured materials typically performed better than commercially available sorbents. Data contains organic and inorganic sorbent removal efficiency, Sharkey Hot Springs (Idaho) water chemsitry analysis, and rare earth removal efficiency from select sorbents.
Rare earth-iron magnetostrictive materials and devices using these materials
Savage, Howard T.; Clark, Arthur E.; McMasters, O. Dale
1981-12-29
Grain-oriented polycrystalline or single crystal magnetostrictive materials n the general formula Tb.sub.x Dy.sub.1-x Fe.sub.2-w, Tb.sub.x Ho.sub.1-x Fe.sub.2-w, Sm.sub.x Dy.sub.1-x Fe.sub.x-w, Sm.sub.x Ho.sub.1-x Fe.sub.2-w, Tb.sub.x Ho.sub.y Dy.sub.z Fe.sub.2-w, or Sm.sub.x Ho.sub.y Dy.sub.z Fe.sub.2-w, wherein O.ltoreq.w.ltoreq.0.20, and x+y+z=1. X, y, and z are selected to maximize the magnetostrictive effect and the magnetomechanical coupling coefficient K.sub.33. These material may be used in magnetostrictive transducers, delay lines, variable frequency resonators, and filters.
Giant magnetostrain based on strong single ion anisotropy of rare earth materials
NASA Astrophysics Data System (ADS)
Doerr, M.; Raasch, S.; Rotter, M.; Frontzek, M.; Meyer, D. C.; Leisegang, T.; Zschintzsch, M.; Svoboda, P.; Loewenhaupt, M.
2008-05-01
The volume, shape and microstructure of solids can be influenced by magnetic fields. Much effort is focused on magnetic shape memory (MSM) materials. Recently, the MSM effect has been discovered to occur also in the paramagnetic state, e.g. in RCu2 compounds (R = rare earth). RMSM materials distinguish themselves from conventional MSM materials by the new origin of the magnetoic anisotropy: the strong rare-earth single ion anisotropy. Due to the pseudo-hexagonal symmetry of RCu2, three orientational variants exists, each of them rotated by about 60 deg with respect to the others. Switching these variants by an external field results in a change of the macroscopic shape. The strain is in the order of one percent (= Giant MagnetoStrain). The variant's fraction remains unchanged when ramping down the field. The virgin state can be recovered by heating or by a perpendicularly directed field. We present temperature and field dependent measurements of magnetostrain and magentization at the model substance Tb0.5Dy0.5Cu2. The macroscopic characterization of the sample is complemented by a detailed microscopic analysis done by elastic neutron scattering. Although the GMS effect of RCu2 was worked out at single crystals, the principle of this magneto-mechanical coupling phenomenon is also useful for polycrystalline or microscaled applications. The existence of this structural irreversibility shows the potential to construct field controlled actuators or switches.
Panday, V.K.; Hoppstock, K.; Becker, J.S.; Dietze, H.J.
1996-09-01
Despite the fact that rare earth elements (REE) have found increasing use in modern technology only few data are available on their concentrations in biological and environmental samples. Inductively coupled plasma mass spectrometry (ICP-MS) has been employed to study the concentration of rare earth elements (REE) in various environmental materials (e.g., pine needles, mussel tissue, apple leaves) available from National Institute of Standards and Technology (NIST), the Bureau of European Communities (BCR), and the German Environmental Specimens Bank. After the decomposition of the environmental samples with HNO{sub 3}, the REE (present mostly in the ng/g-range) were separated from the matrix and simultaneously preconcentrated using liquid-liquid extraction with bis(2-ethyl hexyl)-ortho-phosphoric acid (HDEHP) in toluene as a selective reagent at pH = 2 and subsequent back extraction of the elements into the aqueous by 6M HNO{sub 3}. Recoveries of better 90% were obtained for almost all REE. A Perkin Elmer/Sciex ELAN 5000 ICP-MS and HR-ICP-MS ELEMENT from Finnigan MAT were used for quantitative analysis (by external calibration and ID-ICP-MS) of REE. The results of determination of REE concentrations agree well with the data available on some of these materials. Further supplement information on the contents of various REE in these materials.
Lightweight Nonmetallic Thermal Protection Materials Technology (LNTPMT) Project
NASA Technical Reports Server (NTRS)
Flynn, Kevin; Gubert, Michael
2005-01-01
Contents include the following: Exploration systems research and technology program structure. Project objective. Overview of project. Candidate thermal protection system (PS) materials. Definition of reference missions and space environments. Technical performance metrics (TPMs).Testing (types of tests). Conclusion.
Materials Data on HI (SG:15) by Materials Project
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 W (SG:225) by Materials Project
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 WS2 (SG:194) by Materials Project
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 WBr5 (SG:12) by Materials Project
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 W (SG:223) by Materials Project
Kristin Persson
2015-03-09
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 WCl5 (SG:12) by Materials Project
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 WCl3 (SG:148) by Materials Project
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 PW (SG:62) by Materials Project
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 UWC2 (SG:62) by Materials Project
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 WSCl4 (SG:2) by Materials Project
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 UNCl (SG:129) by Materials Project
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 BRh2 (SG:62) by Materials Project
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 UIN (SG:129) by Materials Project
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 Ce (SG:194) by Materials Project
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 Hf (SG:194) by Materials Project
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 Be (SG:229) by Materials Project
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 UPCl10 (SG:2) by Materials Project
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 UO3 (SG:221) by Materials Project
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 Rb (SG:225) by Materials Project
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 HBr (SG:19) by Materials Project
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 HBr (SG:36) by Materials Project
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 HBr (SG:69) by Materials Project
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 HBr (SG:225) by Materials Project
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 US (SG:225) by Materials Project
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 USn3 (SG:221) by Materials Project
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 UGe2 (SG:63) by Materials Project
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 UGe3 (SG:221) by Materials Project
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 UAl3 (SG:221) by Materials Project
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 UGa2 (SG:191) by Materials Project
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 UIr2 (SG:227) by Materials Project
Kristin Persson
2015-03-09
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:229) by Materials Project
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 Sr (SG:191) by Materials Project
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 Sb (SG:225) by Materials Project
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 Sb (SG:221) by Materials Project
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 Sb (SG:139) by Materials Project
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 Ga (SG:64) by Materials Project
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 Ga (SG:63) by Materials Project
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 Ga (SG:139) by Materials Project
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
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 USb (SG:221) by Materials Project
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:166) by Materials Project
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:166) by Materials Project
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:71) by Materials Project
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:166) by Materials Project
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:65) by Materials Project
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:0) by Materials Project
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:229) by Materials Project
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
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:65) by Materials Project
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
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:191) by Materials Project
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:67) by Materials Project
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
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:58) by Materials Project
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 UN (SG:225) by Materials Project
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 IF5 (SG:15) by Materials Project
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:194) by Materials Project
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 C (SG:194) by Materials Project
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 YGa (SG:63) by Materials Project
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 Ce (SG:229) by Materials Project
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 Lu (SG:229) by Materials Project
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 La (SG:229) by Materials Project
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 Tm (SG:194) by Materials Project
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 Y (SG:194) by Materials Project
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 YMg2 (SG:194) by Materials Project
Kristin Persson
2015-03-10
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 WO2 (SG:166) by Materials Project
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:227) by Materials Project
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 WC (SG:225) by Materials Project
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 BW2 (SG:140) by Materials Project
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 Pa (SG:225) by Materials Project
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:139) by Materials Project
Kristin Persson
2014-11-14
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 VO2 (SG:62) by Materials Project
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
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 PCl3 (SG:62) by Materials Project
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 PHN2 (SG:24) by Materials Project
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 PNO (SG:1) by Materials Project
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 PBr3 (SG:62) by Materials Project
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:166) by Materials Project
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 YSn2 (SG:63) by Materials Project
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 BPO4 (SG:82) by Materials Project
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 Tl (SG:225) by Materials Project
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 YGe2 (SG:141) by Materials Project
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 YBi (SG:225) by Materials Project
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 VRh3 (SG:221) by Materials Project
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 Mg (SG:194) by Materials Project
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:205) by Materials Project
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 WO3 (SG:14) by Materials Project
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 VSi2 (SG:180) by Materials Project
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 UAl2 (SG:227) by Materials Project
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 Np (SG:229) by Materials Project
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 VIr3 (SG:221) by Materials Project
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 Cl2 (SG:64) by Materials Project
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 Br (SG:64) by Materials Project
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
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 Nd (SG:229) by Materials Project
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 VO (SG:225) by Materials Project
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 Se (SG:152) by Materials Project
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 Mo (SG:229) by Materials Project
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 YFe5 (SG:191) by Materials Project
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 UB2 (SG:191) by Materials Project
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 Nd (SG:225) by Materials Project
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 HRh (SG:225) by Materials Project
Kristin Persson
2015-04-29
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Materials Data on UH3 (SG:223) by Materials Project
Kristin Persson
2015-04-29
Computed materials data using density functional theory calculations. These calculations determine the 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
Kristin Persson
2015-03-07
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 YH3 (SG:194) by Materials Project
Kristin Persson
2015-04-29
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Materials Data on UBr5 (SG:2) by Materials Project
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 Bi (SG:51) by Materials Project
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 WO3 (SG:51) by Materials Project
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 Te (SG:51) by Materials Project
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 KB6 (SG:221) by Materials Project
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 HCl (SG:225) by Materials Project
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 YH3 (SG:165) by Materials Project
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 YCd3 (SG:63) by Materials Project
Kristin Persson
2015-03-09
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 YIr2 (SG:227) by Materials Project
Kristin Persson
2015-03-09
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 UAs (SG:221) by Materials Project
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 VIr (SG:123) by Materials Project
Kristin Persson
2015-03-09
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 VSO5 (SG:85) by Materials Project
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 Na (SG:194) by Materials Project
Kristin Persson
2016-05-26
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 Na (SG:166) by Materials Project
Kristin Persson
2016-08-28
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 Na (SG:139) by Materials Project
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 Na (SG:194) by Materials Project
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 Na (SG:194) by Materials Project
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 Na (SG:229) by Materials Project
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 Na (SG:225) by Materials Project
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 Na (SG:220) by Materials Project
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 UGe2 (SG:65) by Materials Project
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 USi3 (SG:221) by Materials Project
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 UOs2 (SG:227) by Materials Project
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 VTc (SG:221) by Materials Project
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 YB6 (SG:221) by Materials Project
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 KI (SG:225) by Materials Project
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 KI (SG:221) by Materials Project
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 YCI (SG:12) by Materials Project
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 IO2 (SG:14) by Materials Project
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 BI3 (SG:176) by Materials Project
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 I (SG:64) by Materials Project
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 VOs (SG:221) by Materials Project
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 BF3 (SG:2) by Materials Project
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
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 BF2 (SG:14) by Materials Project
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 BPt (SG:194) by Materials Project
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 BPd3 (SG:62) by Materials Project
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 BMo2 (SG:140) by Materials Project
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 BN (SG:9) by Materials Project
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 VH2 (SG:225) by Materials Project
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 PPd6 (SG:14) by Materials Project
Kristin Persson
2015-01-21
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 SF4 (SG:121) by Materials Project
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 PHF4 (SG:14) by Materials Project
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 KBF4 (SG:62) by Materials Project
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 UF4 (SG:15) by Materials Project
Kristin Persson
2015-03-07
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 KC10 (SG:204) by Materials Project
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 KC60 (SG:58) by Materials Project
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
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 Sb (SG:166) by Materials Project
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 PNO (SG:145) by Materials Project
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 PI3 (SG:173) by Materials Project
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:2) by Materials Project
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
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:12) by Materials Project
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 PBr5 (SG:57) by Materials Project
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
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 KGe (SG:218) by Materials Project
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 KTe (SG:194) by Materials Project
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 KO2 (SG:139) by Materials Project
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 KPb2 (SG:194) by Materials Project
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 KGa3 (SG:119) by Materials Project
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 KO2 (SG:15) by Materials Project
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 Cu (SG:225) by Materials Project
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 As (SG:64) by Materials Project
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 UB12 (SG:225) by Materials Project
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 SN (SG:14) by Materials Project
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 UBr3 (SG:176) by Materials Project
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 UCl4 (SG:141) by Materials Project
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 Cr (SG:223) by Materials Project
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 UNi2 (SG:194) by Materials Project
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 Tc (SG:194) by Materials Project
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 YHSO5 (SG:14) by Materials Project
Kristin Persson
2014-10-02
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 YAl2 (SG:227) by Materials Project
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 Sc (SG:225) by Materials Project
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 US3 (SG:11) by Materials Project
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 WCl6 (SG:164) by Materials Project
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 WO2 (SG:136) by Materials Project
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 WSe2 (SG:194) by Materials Project
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 Ge (SG:148) by Materials Project
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 K (SG:229) by Materials Project
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:64) by Materials Project
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
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:194) by Materials Project
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 KC (SG:142) by Materials Project
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 CS2 (SG:64) by Materials Project
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 UO3 (SG:141) by Materials Project
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 UF5 (SG:122) by Materials Project
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 WO3 (SG:130) by Materials Project
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 HCl (SG:36) by Materials Project
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 YAl (SG:63) by Materials Project
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 Hg (SG:191) by Materials Project
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