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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
DOE OSTI2021

A market-oriented database design for critical material research

Material databases are important tools to provide and store information from material research. Rising concerns about supply-chain risks to raw materials presents a need to incorporate raw-material market and end-use application data, beyond basic chemical and physical properties, into a material database. One key challenge for researchers working on critical materials is information scarcity and inconsistency. This paper introduces, as a result of a two-year project, a critical-material commodity database (CMCD) incorporated with a low-code web-based platform that allows easy access for users and simple updates for the authors. The main goal of this project was to educate material scientists on the applications having the most impact on the supply chain and current industrial specifications/markets for each application. The objective was to provide material researchers with harmonized information so that they could gain a better understanding of the market, focus their technologies on an application with a high potential for commercialization, and better contribute to supply-chain risk reduction. While the goal was met with high receptivity, several limitations stemmed from query design, distribution platform, and quality of data source. To overcome some of these limitations and expand on CMCD's potential, we are building a public webpage with an improved interface, better data organization, and higher extensibility.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Progress of applied superconductivity research at Materials Research Laboratories, ITRI (Taiwan)

A status report based on the applied high temperature superconductivity (HTS) research at Materials Research Laboratories (MRL), Industrial Technology Research Institute (ITRI) is given. The aim is to develop fabrication technologies for the high-TC materials appropriate to the industrial application requirements. To date, the majorities of works have been undertaken in the areas of new materials, wires/tapes with long length, prototypes of magnets, large-area thin films, SQUID's and microwave applications.

Liu, R. S.↗
DOE OSTI2024

Developing and Evaluating Energy Justice Metrics for Early-Stage Materials Research

Materials science is a central component of early-stage research and development of virtually all clean energy technologies. But as much as material breakthroughs often hold the key to high efficiencies, long lifetimes, and high stability in eventual devices, early-stage choices about material types, structures, and processing can also serve to lock in long-term social and equity impacts of deployed energy technologies. Thus, to achieve a just and sustainable energy transition, tools to assess the energy justice impacts of early-stage materials research are critical. Here, we discuss development of the Justice Underpinning Science and Technology Research (JUST-R) metrics framework - a suite of metrics targeted at early-stage researchers to assess energy justice considerations in their work. The framework is evaluated for its appeal to researchers and effectiveness at promoting integration of energy justice into research through case studies, which reveal its ability to broaden researcher perspectives and key avenues for future improvement.

energy justice↗
NASA NTRS1990

NASA. Lewis Research Center materials research and technology: An overview

The Materials Division at the Lewis Research Center has a long record of contributions to both materials and process technology as well as to the understanding of key high-temperature phenomena. This paper overviews the division staff, facilities, past history, recent progress, and future interests.

Grisaffe, Salvatore J.↗
DOE OSTI2022

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A new capability facilitating nuclear materials research: the Activated Materials Laboratory at the Advanced Photon Source

The Activated Materials Laboratory (AML), located in the Long Beamline Building (LBB) of the Advanced Photon Source (APS) of Argonne National Laboratory (ANL), serves as a centralized radiological facility for preparing radioactive samples for APS beamline experiments. The AML is equipped to receive shipments, handle open-form radioactive materials, encapsulate samples, and transport samples to-and-from beamline end-stations. The AML works closely with users and the APS radiological safety committee to make sure the safe conduct of experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Artificial intelligence for materials research at extremes

Abstract Materials development is slow and expensive, taking decades from inception to fielding. For materials research at extremes, the situation is even more demanding, as the desired property combinations such as strength and oxidation resistance can have complex interactions. Here, we explore the role of AI and autonomous experimentation (AE) in the process of understanding and developing materials for extreme and coupled environments. AI is important in understanding materials under extremes due to the highly demanding and unique cases these environments represent. Materials are pushed to their limits in ways that, for example, equilibrium phase diagrams cannot describe. Often, multiple physical phenomena compete to determine the material response. Further, validation is often difficult or impossible. AI can help bridge these gaps, providing heuristic but valuable links between materials properties and performance under extreme conditions. We explore the potential advantages of AE along with decision strategies. In particular, we consider the problem of deciding between low-fidelity, inexpensive experiments and high-fidelity, expensive experiments. The cost of experiments is described in terms of the speed and throughput of automated experiments, contrasted with the human resources needed to execute manual experiments. We also consider the cost and benefits of modeling and simulation to further materials understanding, along with characterization of materials under extreme environments in the AE loop. Graphical abstract AI sequential decision-making methods for materials research: Active learning, which focuses on exploration by sampling uncertain regions, Bayesian and bandit optimization as well as reinforcement learning (RL), which trades off exploration of uncertain regions with exploitation of optimum function value. Bayesian and bandit optimization focus on finding the optimal value of the function at each step or cumulatively over the entire steps, respectively, whereas RL considers cumulative value of the labeling function, where the latter can change depending on the state of the system (blue, orange, or green).

36 MATERIALS SCIENCE↗
NASA NTRS1984

Encapsulation materials research

Encapsulation materials for solar cells were investigated. The different phases consisted of: (1) identification and development of low cost module encapsulation materials; (2) materials reliability examination; and (3) process sensitivity and process development. It is found that outdoor photothermal aging devices (OPT) are the best accelerated aging methods, simulate worst case field conditions, evaluate formulation and module performance and have a possibility for life assessment. Outdoor metallic copper exposure should be avoided, self priming formulations have good storage stability, stabilizers enhance performance, and soil resistance treatment is still effective.

Willis, P. B.↗
NASA NTRS1996

Computational Materials Research

Computational Materials aims to model and predict thermodynamic, mechanical, and transport properties of polymer matrix composites. This workshop, the second coordinated by NASA Langley, reports progress in measurements and modeling at a number of length scales: atomic, molecular, nano, and continuum. Assembled here are presentations on quantum calculations for force field development, molecular mechanics of interfaces, molecular weight effects on mechanical properties, molecular dynamics applied to poling of polymers for electrets, Monte Carlo simulation of aromatic thermoplastics, thermal pressure coefficients of liquids, ultrasonic elastic constants, group additivity predictions, bulk constitutive models, and viscoplasticity characterization.

Hinkley, Jeffrey A.↗
NASA NTRS1995

Rigid Tile Thermal Protection Materials Research and Space Shuttle Performance

The materials research activities and materials characterization capabilities of the Thermal Protection Materials and Systems Branch at Ames Research Center will be described. The Branch's activities involved with the development of several parts of the thermal protection system on the Space Shuttle and their performance will be reviewed. The status of materials research in rigid light weight insulations and the potential of a newer generation of thermal protection materials designated as Toughened Uni-Piece Fibrous Insulation (TUFI) used in protecting entry vehicles will be presented.

Leiser, Daniel B.↗
DOE OSTI2024

Are We on Track for 2050? A Materials Research & Sustainability Perspective

In commemoration of the Materials Research Society (MRS)'s 50th anniversary, the 2050 panel hosted a discussion to reflect on the past, present, and future of sustainability and the role of materials research and development. Three panelists discussed their views, based on their expertise, about future challenges and lessons from the past. Sustainable development is a broad topic; therefore, the discussion centered on their experience as material researchers and their efforts for a better and greener future. This work is developed in collaboration with the co-authors team, highlighting the need for accelerating research and development efforts, especially in materials science and applications, fostering interdisciplinary partnerships, and mobilizing collective action to address the complex and interconnected sustainability challenges that humanity is currently facing.

ENERGY PLANNING, POLICY, AND ECONOMY,ENVIRONMENTAL↗
NASA NTRS1987

Materials research and applications at NASA Lewis Research Center

The facilities and instruments of the Lewis Research Center specialized for materials research are discussed. The main objectives of the Center are to provide R & D relevant to main propulsion plants and auxiliary power systems for aeronautics, space, and energy conversion applications. The Center is concerned with microstructure-property relations and their effect on processing; intermetallic compounds and high temperature metal matrix composites; ceramics with improved reliability for use in heat engines; polymer matrix composites for aerospace applcations; understanding the high temperature corrosive attack in the hostile environments of aircraft, rockets, and other heat engines; high temperature lubrication and wear; and microgravity materials research. The various types of schemes and techniques, provided by the Center, for analyzing data are described.

Probst, H. B.↗