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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Computational synthesis of 2D materials: A high-throughput approach to materials design

2D materials find promising applications in next-generation devices, however, large-scale, low-defect, and reproducible synthesis of 2D materials remains a challenging task. Here, to assist in the selection of suitable substrates for the synthesis of as-yet hypothetical 2D materials, we have developed an open-source high-throughput workflow package, Hetero2d, that searches for low-lattice mismatched substrate surfaces for any 2D material and determines the stability of these 2D-substrate heterostructures using density functional theory (DFT) simulations. Hetero2d automates the generation of 2D-substrate heterostructures, the creation of DFT input files, the submission and monitoring of computational jobs on supercomputing facilities, and the storage of relevant parameters alongside the post-processed results in a MongoDB database. We demonstrate the capability of Hetero2d in identifying stable 2D-substrate heterostructures for four 2D materials, namely 2H-MoS 2 , 1T- and 2H-NbO 2 , and hexagonal-ZnTe, considering 50 cubic elemental substrates. We find Cu, Hf, Mn, Nd, Ni, Pd, Re, Rh, Sc, Ta, Ti, V, W, Y, and Zr substrates sufficiently stabilize the formation energies of these 2D materials, with binding energies in the range of ~0.1–0.6 eV/atom. Upon examining the z-separation, the charge transfer, and the electronic density of states at the 2D-substrate interface, we find a covalent type bonding at the interface which suggests that these substrates can be used as contact materials for the 2D materials. Hetero2d is available on GitHub as an open-source package under the GNU license.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The northeast materials database for magnetic materials

The discovery of magnetic materials with high operating temperature ranges and optimized performance is essential for advanced applications. Current data-driven approaches are limited by the lack of accurate, comprehensive, and feature-rich databases. This study aims to address this challenge by using Large Language Models (LLMs) to create a comprehensive, experiment-based, magnetic materials database named the Northeast Materials Database (NEMAD), which consists of 67,573 magnetic materials entries (www.nemad.org). The database incorporates chemical composition, magnetic phase transition temperatures, structural details, and magnetic properties. Enabled by NEMAD, we trained machine learning models to classify materials and predict transition temperatures. Our classification model achieved an accuracy of 90% in categorizing materials as ferromagnetic (FM), antiferromagnetic (AFM), and non-magnetic (NM). The regression models predict Curie (Néel) temperature with a coefficient of determination (R 2 ) of 0.87 (0.83) and a mean absolute error (MAE) of 56K (38K). These models identified 25 (13) FM (AFM) candidates with a predicted Curie (Néel) temperature above 500K (100K) from the Materials Project. This work shows the feasibility of combining LLMs for automated data extraction and machine learning models to accelerate the discovery of magnetic materials.

Ferromagnetism↗
DOE OSTI2023

Predicting the synthesizability of crystalline inorganic materials from the data of known material compositions

Abstract Reliably identifying synthesizable inorganic crystalline materials is an unsolved challenge required for realizing autonomous materials discovery. In this work, we develop a deep learning synthesizability model ( SynthNN ) that leverages the entire space of synthesized inorganic chemical compositions. By reformulating material discovery as a synthesizability classification task, SynthNN identifies synthesizable materials with 7× higher precision than with DFT-calculated formation energies. In a head-to-head material discovery comparison against 20 expert material scientists, SynthNN outperforms all experts, achieves 1.5× higher precision and completes the task five orders of magnitude faster than the best human expert. Remarkably, without any prior chemical knowledge, our experiments indicate that SynthNN learns the chemical principles of charge-balancing, chemical family relationships and ionicity, and utilizes these principles to generate synthesizability predictions. The development of SynthNN will allow for synthesizability constraints to be seamlessly integrated into computational material screening workflows to increase their reliability for identifying synthetically accessible materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Advanced Modeling and Simulation Methods for Evaluation of Thermal Neutron Scattering Materials

With the rise of interest in thermal neutron scattering data for advanced reactor, criticality safety, and shielding applications, new experimental data are required for evaluation of new materials or for re-evaluation (or validations) of previously evaluated materials. New experimental data are evaluated in a three-step process: (1) computing the phonon characteristics, (2) computing the dynamic structure factor (DSF) from the data, and (3) using the experimental setup to simulate the experimental data. All three steps have challenges, ranging from the need for a sufficiently general material simulation code—a processing code that can compute the corresponding DSF—to having a detailed layout of the instrument/beamline/facility where the data were measured. Whereas phonon characteristics of materials can be computed using various methods (molecular dynamics, density functional theory, etc.), a high-fidelity computation of the DSF and the simulation of the experiment based on the DSF is vital to the accuracy of the evaluation. The latter two steps can be achieved by using the two corresponding code systems developed by instrument scientists at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory: (1) OCLIMAX, a program that calculates the dynamic structure factor from DFT and MD simulation results, and (2) MCViNE, a Monte Carlo neutron ray-tracing program designed to simulate neutron scattering experiments. Recently, polyethylene and yttrium hydride were measured at the Wide Angular-Range Chopper (ARCS) and SEQUOIA instrument stations of the SNS. These experiments are simulated using the density functional theory code, the Cambridge Serial Total Energy Package (CASTEP), to compute its phonon characteristics (eigenvalues/vectors and PDOS), which is then processed using OCLIMAX to yield the DSF, and finally the data at each instrument station are simulated by the MCViNE for comparison to the measured data for evaluation. For comparison to conventional evaluation methods, the scattering data processed from OCLIMAX are compared against those processed from the LEAPR module of NJOY, and the results from MCViNE simulations are compared against previously used simplified beamline models implemented in the Monte Carlo N-Particle (MCNP) code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Conceptual Design and Performance Considerations for Superconducting Magnets in the Material Plasma Exposure eXperiment

An important step toward the advent of nuclear fusion as a future power source is the development of plasmafacing materials that can function as designed for a long period of time. While ITER and other devices including Wendelstein 7-X and the Joint European Torus will provide insight into divertor and first wall performance, a dedicated device to advance the understanding of material performance in the representative plasma environments is needed. The Material Plasma Exposure eXperiment has been proposed as a linear plasma device to generate and to direct fusion reactor-like plasma energy and particle flux at the target materials with electron temperatures of 1-15 eV and electron densities of 10 20 -10 21 m -3 . Given that the requirements for radio frequency (RF) heating on-axis field are no greater than 2.5 T and the warm bore diameters must be between 60 cm and 1.5 m, the conceptual design was developed for the experiments on a set of superconducting magnets carried out using commercially available NbTi superconductors. This conceptual design evaluated the cryogenic heat loads, mechanical loads, and quench protection to ensure that the current design is compatible with current technologies. In addition, an alternative evaluation of this design relative to ReBCO high-temperature superconducting magnets determined the conditions under which these technologies could be advantageous.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Addressing Critical Problems in Materials Science Through Multiscale and Multimode Characterization (Project 1); Characterization and Optimization of Novel Triple-Conducting Oxide Materials for Energy Applications (Project 2) (CRADA Final Report)

PROJECT 1: Address critical problems in materials science and simultaneously advance the state-of-the-art in multiscale and multimode characterization using the combined advanced analytical capabilities and expertise of Colorado School of Mines (CSM) and the National Renewable Energy Laboratory (NREL). The primary effort of the Phase I of this CRADA is to establish the International Center for Multiscale Characterization using shared resources at both NREL and CSM. Phase II will focus on capability development and marketing, choosing candidate materials science issues in the areas of structure imaging, chemical composition mapping, and correlating properties and performance of materials for impact in energy-related, environmental and critical materials areas. The CRADA will be modified to include specific topics of concern in materials science to industry member partners. Advanced analytical capabilities and expertise at CSM and NREL will be used to advance materials understanding and performance through characterization of multiscale phenomena including structural imaging, chemical composition mapping, and other techniques correlating properties and performance of materials. PROJECT 2: As part of the International Center for Materials Characterization, work under Modification #1 will be led by Colorado School of Mines (CSM), working in collaboration with NREL staff to mentor and advise CSM postdoctoral researchers on set up of diffusion annealing experiments. The purpose of the modification is to provide for NREL staff to mentor and advise CSM postdoctoral researchers on set up of diffusion annealing experiments, including mentoring and advising the CSM-NREL team on proper Secondary Ion Mass Spectrometry (SIMS) data analysis as needed. SIMS measurements of 10-20 samples will be performed at NREL during the project duration.

08 HYDROGEN↗
DOE OSTI2020

Highly Enhanced Curie Temperature in Ga-Implanted Fe3GeTe2 van der Waals Material

Among many efforts in the research of van der Waals (vdW) magnetic materials, increasing the Curie temperature above room temperature has been at the center of research in developing spintronics technology using vdW materials. Here an effective and reliable method of increasing the Curie temperature of ferromagnetic Fe3GeTe2 vdW materials by Ga implantation is reported. It is found that implanting Ga into Fe3GeTe2 by the amount of 10-3 Ga Å-3 could greatly enhance the Fe3GeTe2 Curie temperature by almost 100%. Spatially resolved microdiffraction and element-resolved X-ray absorption spectroscopy show little changes in the Fe3GeTe2 crystal structure and Fe valence state. In addition, the Ga implantation changes the Fe3GeTe2 magnetization from out-of-plane direction at low temperature to in-plane direction at high temperature. The result opens a new opportunity for tailoring the magnetic properties of vdW materials beyond room temperature.

Yang, M↗
DOE OSTI2020

Uncovering Uranium Isotopic Heterogeneity of Fuel Pellets from the Fifth Collaborative Materials Exercise of the Nuclear Forensics International Technical Working Group

In 2017, the Nuclear Forensics International Technical Working Group (ITWG) organized their fifth 37 Collaborative Materials Exercise (CMX-5). The exercise samples were two uranium dioxide fuel pellets 38 manufactured from the same starting materials by different processes to have similar bulk isotopic 39 composition, but different spatial uranium isotopic distributions. Sets of identical materials were sent to 40 all participating laboratories, who then utilized their existing nuclear forensic capabilities to 41 independently analyse fuel pellets and identify similarities and differences of the materials’ 42 characteristics. The analytical methods used to probe the fuel pellets included ex situ, such as sectioning 43 or breaking up the pellets and analyzing dissolved pieces using inductively coupled plasma mass 44 spectrometry (ICP-MS), analyzing particles collected from intact or fragmented pellets by secondary ion 45 mass spectrometry (SIMS), as well as in situ methods, such as laser ablation coupled with ICP-MS, 46 autoradiography and nanoSIMS. In this paper we present the results of these independent analyses and 47 compare the capabilities of those nuclear forensic analytical methods to uncover details of the isotopic 48 heterogeneity of uranium fuel pellets.

Nuclear Forensic Analysis of Uranium Fuel Pellets,↗
DOE OSTI2025

Primary material supply configurations and domestic recycling for cost-effective battery material production in the US

Battery cathode active material costs hinge on regionally concentrated, price-volatile metal supply. Here. we construct a regional facility-level cost model based on over 80 global lithium, cobalt, and nickel mines, refineries, and battery-grade material plants. Our model yields aggregated lithium, nickel, manganese, and cobalt production material costs from 392 region-based supply configurations for five different cathode active materials. Focusing on the United States, all-domestic supply is 9–34% costlier than global average, increasing by cobalt content, while these shortfalls can be overcome by selective low-cost material imports. Furthermore, we analyze costs of two U.S.-based recycling facilities from primary data and techno-economic modelling and compare resulting cathode active material-level costs to primary supply. Although it is still significantly higher on cathode active material cost-level, rising end-of-life flows and lowered black-mass prices will, however, make secondary supply cost-competitive to domestic and foreign primary supply cost floors. Facility-level benchmarks reveal targeted import, scaling, and production cost optimization as levers for a resilient, cost-effective U.S. battery-material supply chain.

Energy↗
NASA NTRS1993

Materials And Processes Technical Information System (MAPTIS) LDEF materials data base

A preliminary Long Duration Exposure Facility (LDEF) Materials Data Base was developed by the LDEF Materials Special Investigation Group (MSIG). The LDEF Materials Data Base is envisioned to eventually contain the wide variety and vast quantity of materials data generated from LDEF. The data is searchable by optical, thermal, and mechanical properties, exposure parameters (such as atomic oxygen flux) and author(s) or principal investigator(s). Tne LDEF Materials Data Base was incorporated into the Materials and Processes Technical Information System (MAPTIS). MAPTIS is a collection of materials data which has been computerized and is available to engineers, designers, and researchers in the aerospace community involved in the design and development of spacecraft and related hardware. The LDEF Materials Data Base is described and step-by-step example searches using the data base are included. Information on how to become an authorized user of the system is included.

Funk, Joan G.↗
NASA NTRS1993

Fluorescence observations of LDEF exposed materials as an indicator of induced material reactions

Observations and measurements of induced changes in the fluorescent emission of materials exposed to the space environment on the Long Duration Exposure Facility (LDEF) have revealed systematic patterns of material-dependent behavior. These results have been supplemented by inspection of similar materials exposed on previous Space Shuttle Missions and in laboratory testing. The space environmental factors affecting the fluorescence of exposed materials have been found to include (but are not necessarily limited to) solar ultraviolet (UV) radiation, atomic oxygen (AO), thermal vacuum exposure, and synergistic combinations of these factors. Observed changes in material fluorescent behavior include stimulation, quenching, and spectral band shifts of emission. For example, the intrinsic yellow fluorescence of zinc oxide pigmented thermal control coatings undergoes quenching as a result of exposure, while coloration is stimulated in the fluorescent emission of several polyurethane coating materials. The changes in fluorescent behavior of these materials are shown to be a revealing indicator of induced material reactions as a result of space environmental exposure.

Linton, Roger C.↗
NASA NTRS1994

Application of materials database (MAT.DB.) to materials education

Finding the right material for the job is an important aspect of engineering. Sometimes the choice is as fundamental as selecting between steel and aluminum. Other times, the choice may be between different compositions in an alloy. Discovering and compiling materials data is a demanding task, but it leads to accurate models for analysis and successful materials application. Mat. DB. is a database management system designed for maintaining information on the properties and processing of engineered materials, including metals, plastics, composites, and ceramics. It was developed by the Center for Materials Data of American Society for Metals (ASM) International. The ASM Center for Materials Data collects and reviews material property data for publication in books, reports, and electronic database. Mat. DB was developed to aid the data management and material applications.

Liu, Ping↗
DOE OSTI2021

Corrosion resistive materials, systems, and methods of forming and using the materials and systems

A method to reduce corrosion rates of materials at high temperatures may include heating a mixture and applying the heated mixture to a material to be rendered thermodynamically noble. The mixture may include carbon monoxide and carbon dioxide and the material rendered thermodynamically noble may include copper or other material having similar physical properties. The copper or other similar material may be applied to a structural material and provide a surface interfacing with the mixture of carbon monoxide and carbon dioxide to prevent corrosion of the structural material. In some cases, the structural material may form a heat exchanger defining passageways for a working fluid of a power system and/or may form other passageways of the power system. The copper may be applied to the passageways as a protective coating and then made thermodynamically noble at high temperatures after interactions with the mixture of carbon monoxide and carbon dioxide.

Anderson, Mark↗
DOE OSTI2023

Solid-state crystallization of metal organic frameworks within mesoporous materials methods and hybrid materials thereof

A method, comprising i) contacting an aqueous solution of an organic ligand salt of the formula A X (L −X ) with a mesoporous material (MPM) to form an impregnated mesoporous salt material of the formula A X (L −X )/MPM, ii) treating the impregnated mesoporous salt material with an aqueous acidic solution to form an impregnated mesoporous acid material of the formula H X (L −X )/MPM, iii) contacting an aqueous solution of a metal precursor of the formula M +y (B)y with the impregnated mesoporous acid material to form an impregnated mesoporous metal organic framework precursor of the formula [M +y (B) y ][H x (L −x )]/MPM, and iv) at least one of 1) heating the impregnated mesoporous metal organic framework precursor in the absence of a solvent or 2) exposing the impregnated mesoporous metal organic framework precursor to a volatile vapor in the absence of a solvent such that the heating or the exposing forms a hybrid material of the formula (M +y L −x )/MPM, wherein the hybrid material comprises a nano-crystalline metal organic framework (MOF) embedded within the mesoporous material.

Minguez, Ignacio Luz↗
DOE OSTI2020

Comparative Studies of Optoelectrical Properties of Prominent PV Materials: Halide Perovskite, CdTe, and GaAs

We compare three representative high performance PV materials: halide perovskite MAPbI3, CdTe, and GaAs, in terms of photoluminescence (PL) efficiency, PL lineshape, carrier diffusion, and surface recombination and passivation, over multiple orders of photo-excitation density or carrier density appropriate for different applications. An analytic model is used to describe the excitation density dependence of PL intensity and extract the internal PL efficiency and multiple pertinent recombination parameters. A PL imaging technique is used to obtain carrier diffusion length without using a PL quencher, thus, free of unintended influence beyond pure diffusion. Our results show that perovskite samples tend to exhibit lower Shockley-Read-Hall (SRH) recombination rate in both bulk and surface, thus higher PL efficiency than the inorganic counterparts, particularly under low excitation density, even with no or preliminary surface passivation. PL lineshape and diffusion analysis indicate that there is considerable structural disordering in the perovskite materials, and thus photo-generated carriers are not in global thermal equilibrium, which in turn suppresses the nonradiative recombination. This study suggests that relatively low point-defect density, less detrimental surface recombination, and moderate structural disordering contribute to the high PV efficiency in the perovskite. This comparative photovoltaics study provides more insights into the fundamental material science and the search for optimal device designs by learning from different technologies.

14 SOLAR ENERGY↗
DOE OSTI2022

Conservative remapping of material-dependent fields between possibly misaligned material regions

In this work, we propose an interpolation or remapping algorithm of material-dependent fields on polyhedral meshes where any source or target cell contains only one material. It is conservative and it preserves sharp material boundaries on the target mesh, even if the source and target regions delineating the same material are slightly misaligned. If those material regions are aligned, then the algorithm is also linearity-preserving and bounds-preserving. For a given material, it consists of a conservative field reconstruction on a target mesh part from a source mesh part associated with that material, followed by a repair step in case of misaligned boundaries. No assumption is made regarding the topology of the input meshes

36 MATERIALS SCIENCE↗
DOE OSTI2025

Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry

Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry. Built on top of the popular Deep Graph Library (DGL) and Python Materials Genomics (Pymatgen) packages, MatGL is designed to be an extensible “batteries-included” library for developing advanced model architectures for materials property predictions and interatomic potentials. At present, MatGL has efficient implementations for both invariant and equivariant graph deep learning models, including the Materials 3-body Graph Network (M3GNet), MatErials Graph Network (MEGNet), Crystal Hamiltonian Graph Network (CHGNet), TensorNet and SO3Net architectures. MatGL also provides several pre-trained foundation potentials (FPs) with coverage of the entire periodic table, and property prediction models for out-of-box usage, benchmarking and fine-tuning. Finally, MatGL integrates with PyTorch Lightning to enable efficient model training.

chemistry↗