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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice and snow, and other materials: The USGS tricorder algorithm

One of the challenges of Imaging Spectroscopy is the identification, mapping and abundance determination of materials, whether mineral, vegetable, or liquid, given enough spectral range, spectral resolution, signal to noise, and spatial resolution. Many materials show diagnostic absorption features in the visual and near infrared region (0.4 to 2.5 micrometers) of the spectrum. This region is covered by the modern imaging spectrometers such as AVIRIS. The challenge is to identify the materials from absorption bands in their spectra, and determine what specific analyses must be done to derive particular parameters of interest, ranging from simply identifying its presence to deriving its abundance, or determining specific chemistry of the material. Recently, a new analysis algorithm was developed that uses a digital spectral library of known materials and a fast, modified-least-squares method of determining if a single spectral feature for a given material is present. Clark et al. made another advance in the mapping algorithm: simultaneously mapping multiple minerals using multiple spectral features. This was done by a modified-least-squares fit of spectral features, from data in a digital spectral library, to corresponding spectral features in the image data. This version has now been superseded by a more comprehensive spectral analysis system called Tricorder.

Clark, Roger N.↗
NASA NTRS2026

Computational Materials for Qualification and Certification (CM4QC) Strategy Document: Maturation of Computational Materials Methods for Aviation-Focused Qualification and Certification of Metal Additive Manufacturing (as an Example of Process-Intensive Materials)

Although considerable scientific and technological advances have been made in recent years in additive manufacturing (AM) processes, these advances have not translated into significant market penetration of AM parts within the aviation industry. It is broadly acknowledged that using traditional qualification and certification (Q&C) approaches for AM components is one of the most significant barriers to broader adoption of AM, resulting in high costs, long product development and certification timelines, and complex design iterations during the product development cycle. A new approach is urgently needed. This document lays out a vision for a new Q&C paradigm with increased use of computational materials (CM) methods aimed at decreasing the time and cost of Q&C of process-intensive material (PIM) approaches in the aviation industry, with AM as the immediate use case. This vision was developed with substantial input from industry, regulatory agencies, government research organizations, and academia.

Edward H Glaessgen↗
DOE OSTI2025

Accelerated data-driven materials science with the Materials Project

The Materials Project was launched formally in 2011 to drive materials discovery forwards through high-throughput computation and open data. More than a decade later, the Materials Project has become an indispensable tool used by more than 600,000 materials researchers around the world. This Perspective describes how the Materials Project, as a data platform and a software ecosystem, has helped to shape research in data-driven materials science. We cover how sustainable software and computational methods have accelerated materials design while becoming more open source and collaborative in nature. Next, we present cases where the Materials Project was used to understand and discover functional materials. We then describe our efforts to meet the needs of an expanding user base, through technical infrastructure updates ranging from data architecture and cloud resources to interactive web applications. Finally, we discuss opportunities to better aid the research community, with the vision that more accessible and easy-to-understand materials data will result in democratized materials knowledge and an increasingly collaborative community.

Horton, Matthew K↗
DOE OSTI2026

The U.S. Fusion Materials Community Roadmap: Near-term research priorities for the development of plasma-facing and structural materials for fusion power plants

In response to the needs of a rapidly growing private fusion industry, the U.S. Fusion Materials Coordinating Committee (FMCC) and the broader U.S. fusion materials research community undertook an extensive effort to create a comprehensive roadmap for fusion materials development. The result of this effort was the U.S. Fusion Materials Community Roadmap (US-FMCR), which describes the steps needed to advance the technical maturity of leading candidates for plasma-facing materials and structural materials for fusion power plants from laboratory-scale experiments to a point of sufficient technological readiness for industrial adoption and implementation. However, researchers face significant resource constraints as well as very aggressive pilot plant development timelines. Thus, the research strategies detailed in the US-FMCR require further assessment to downselect the specific tasks that must be prioritized within the next two to three years, in order to make the most efficient use of funding, human resources, and experimental facilities. This paper presents an overview of the US-FMCR and its development process. We also present the subset of research objectives that the FMCC identified as the most urgent research priorities for the U.S. fusion materials research community. The state-of-the-art of materials research is also highlighted for each class of materials considered in the US-FMCR. The recommendations presented here integrate an extensive evaluation of the current status of fusion materials research with a broad cross-section of opinion from the wider U.S. fusion community.

Ferry, Sara [Massachusetts Institute of Technology↗
NASA NTRS1990

Quantitative characterization of spatial distribution of particles in materials: Application to materials processing

Most engineering materials contain second phase particles or fibers which serve to reinforce the matrix phase. The effect of reinforcements on material properties is usually analyzed in terms of the average volume fraction and spacing of reinforcements, quantities which are global microstructural characteristics. However, material properties can also depend on local microstructural characteristics; for example, on how uniformly the reinforcing phase is distributed in the material. The analysis method will then be applied to a materials processing problem to discover how processing parameters can be selected to maximize redistribution of the reinforcing phase during processing. Several mathematical analysis methods could be adapted to the problem of characterizing the distribution of particles in materials. A tessellation-based method was selected. In the first phase of the investigation, a software package was written to automate the analysis. Typical results are shown. The analysis technique allows the degree to which particles are clustered together, the size and spacing of particle clusters, and the particle density in clusters to be found. The analysis methods were applied to computer-generated distributions and to a few real particle-containing materials. Methods for analyzing a nonuniform particle distribution in a material can be applied to two broad classes of materials science problems: understanding how the resulting particle distribution affects properties. The analysis method described is applied to a materials processing problem: how to select extrusion conditions to maximize the redistribution of reinforcing particles that are initially nonuniformly distributed. In addition, the tessellation-based method to analyze star distributions in spiral galaxies was adapted, illustrating the diverse types of problems to which the analysis method can be applied.

Parse, J. B.↗
DOE OSTI2025

Materials laboratories of the future for alloys, amorphous, and composite materials

In alignment with the Materials Genome Initiative and as the product of a workshop sponsored by the US National Science Foundation, we define a vision for materials laboratories of the future in alloys, amorphous materials, and composite materials; chart a roadmap for realizing this vision; identify technical bottlenecks and barriers to access; and propose pathways to equitable and democratic access to integrated toolsets in a manner that addresses urgent societal needs, accelerates technological innovation, and enhances manufacturing competitiveness. Spanning three important materials classes, this article summarizes the areas of alignment and unifying themes, distinctive needs of different materials research communities, key science drivers that cannot be accomplished within the capabilities of current materials laboratories, and open questions that need further community input. Here, we provide a broader context for the workshop, synopsize the salient findings, outline a shared vision for democratizing access and accelerating materials discovery, highlight some case studies across the three different materials classes, and identify significant issues that need further discussion.

36 MATERIALS SCIENCE↗
NASA NTRS1996

What Drives Spacecraft Cost: A Look Into How Material Characteristics Relate to the Material Complexity Multipliers

Today a variety of engineered materials are used to build the space vehicles and satellites that NASA, DOD and the aerospace community will use in future projects. These materials can be a significant part of the cost when designing and building these systems. Current cost models such as NASCOM, SEER-H and PRICE allow the cost analysis to select materials requirements during the development of the cost model. It should be noted however that some of these models do not always give the most detailed information with respect to material specifications for the given cost model. Instead the materials are defined within broad classification, giving questionable data with regard to specific material cost. It is the objective of this paper to present a summary of basic information on materials to assist the cost analyst in the development of their models. Specifically, this paper will compare materials and their complexity multipliers to some specific material properties.

Rosmait, Russell L.↗
DOE OSTI2025

Prioritizing Nuclear Materials for SAM-3 Neutron Irradiation Campaign: Structural and Cladding Materials Candidates

This report outlines a framework for selecting structural and cladding materials for the Nuclear Science User Facilities (NSUF) SAM-3 neutron irradiation campaign to support the advancement of nuclear energy technologies. The document begins with an introduction that provides background context, highlights the motivations for launching a new irradiation campaign, and defines the overall objectives. The core of the report describes the design considerations for the irradiation campaign, including capsule configurations, irradiation temperature ranges, and target dose levels (defined by displacements per atom, or dpa). The material recommendation was guided by the Specimen Identification and Prioritization (SIP) Working Group, a multidisciplinary team of experts representing national laboratories, academia, industry, federal government and agency. This group played a central role in identifying candidate materials, evaluating technical justifications, and ensuring alignment with boarder programmatic goals. A detailed set of criteria for material prioritization is then presented, taking into account reactor relevance, performance gaps, advanced manufacturing methods, and emerging material classes. Based on the input of SIP working group, specific materials were selected and justified for inclusion in the irradiation campaign by the NSUF leadership and its U.S. Department of Energy (DOE)-Office of Nuclear Energy (NE) management. The final section provides recommended capsule designs, summarizing critical parameters such as material type, fabrication method, sample geometry, irradiation conditions, and specimen quantities. This report serves as a foundation for executing a focused and high-impact neutron irradiation campaign aimed at addressing key materials challenges for both existing and advanced nuclear reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

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 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 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↗
NASA NTRS1988

Electronic materials high-T(sub c) superconductivity polymers and composites structural materials surface science and catalysts industry participation

The fifth year of the Center for Advanced Materials was marked primarily by the significant scientific accomplishments of the research programs. The Electronics Materials program continued its work on the growth and characterization of gallium arsenide crystals, and the development of theories to understand the nature and distribution of defects in the crystals. The High Tc Superconductivity Program continued to make significant contributions to the field in theoretical and experimental work on both bulk materials and thin films and devices. The Ceramic Processing group developed a new technique for cladding YBCO superconductors for high current applications in work with the Electric Power Research Institute. The Polymers and Composites program published a number of important studies involving atomistic simulations of polymer surfaces with excellent correlations to experimental results. The new Enzymatic Synthesis of Materials project produced its first fluorinated polymers and successfully began engineering enzymes designed for materials synthesis. The structural Materials Program continued work on novel alloys, development of processing methods for advanced ceramics, and characterization of mechanical properties of these materials, including the newly documented characterization of cyclic fatigue crack propagation behavior in toughened ceramics. Finally, the Surface Science and Catalysis program made significant contributions to the understanding of microporous catalysts and the nature of surface structures and interface compounds.

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