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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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All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2026

Morgana Overview – NCERC Support for Dynamic Subcritical Experiments

The LANL Subcritical Experiments Program (SCE) recently executed the Morgana Subcritical Experiment at the NNSS. This was the first subcritical experiment executed by LANL for several years (since 2021). It was also notably the first that required SCE personnel to have FMH qualifications for a portion of the work conducted under nuclear criticality safety limits.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Development of Novel Combustion Codes for Supercritical CO2 Combustion: Cooperative Research and Development Final Report, CRADA Number CRD-20-17182

The Allam-Fetvedt Cycle, a novel supercritical CO2 (sCO2) power cycle developed by 8 Rivers Capital, LLC, generates low-cost power from fossil fuels while capturing combustion-CO2. This cycle employs high-temperature oxy-combustion using sCO2 as the working fluid, leading to a challenging environment for materials. The most critical component for reliable deployment of this technology is the combustor-turbine interface. In the proposed partnership between NREL and 8 Rivers, we will develop a simulation-based tool to provide key design inputs for defining the materials and geometries required in this critical area.

09 BIOMASS FUELS↗
DOE OSTI2026

A Compact Cryogenic Environment for In Situ Neutron Diffraction Under Mechanical Loading

Understanding the deformation mechanisms of materials at cryogenic temperatures is crucial for cryogenic engineering applications. In situ neutron diffraction is a powerful technique for probing such mechanisms under cryogenic conditions. In this study, we present the development of a compact cryogenic environment (CCE) designed to facil-itate in situ neutron diffraction experiments under mechanical loading at tempera-tures as low as 77 K. The CCE features a polystyrene foam cryogenic chamber, alumi-num blocks serving as neutron-transparent cold sinks, a liquid nitrogen dosing system for cryogen delivery, a nitrogen gas flow control system for thermal management, a process controller for temperature control, and a pair of thermally isolated grip adapt-ers for mechanical testing. The CCE achieves reliable temperature control with mini-mal neutron attenuation. Utilizing this setup, we conducted three in situ neutron dif-fraction tensile tests on a 316L stainless steel at 77 , 173 , and 298 K, respectively. The results highlight the pronounced effects of cryogenic temperatures on the material's deformation mechanisms, underscoring both the significance of cryogenic deformation studies and the effectiveness of the CCE.

Yu, Dunji [ORNL] (ORCID:0000000189467851)↗
DOE OSTI2025

High-Fidelity Building Emulator for Integrated Comfort and Energy Analysis using EnergyPlus and Radiance

The growing need for smart, energy-efficient, and occupant-centric buildings has created a demand for advanced control systems that can optimize building operations to balance energy savings, demand flexibility, and comfort. However, current building energy simulation tools, such as EnergyPlus, have limitations that hinder the development and evaluation of these complex control systems. To address this challenge, we introduce a high-fidelity building emulator that dynamically couples EnergyPlus with Radiance for enhanced daylight modeling. The introduced workflow allows researchers and practitioners to rapidly develop and evaluate innovative control solutions. An example study looking at a south-facing office zone revealed up to 67% deviation in predicted light levels, which can significantly impact building assessment.

Yu, Tammie↗
DOE OSTI2025

Geospatial modeling of near subsurface temperatures of the contiguous United States for assessment of materials degradation

Abstract Understanding subsurface temperature variations is crucial for assessing material degradation in underground structures. This study maps subsurface temperatures across the contiguous United States for depths from 50 to 3500 m, comparing linear interpolation, gradient boosting (LightGBM), neural networks, and a novel hybrid approach combining linear interpolation with LightGBM. Results reveal heterogeneous temperature patterns both horizontally and vertically. The hybrid model performed best achieving a root mean square error of 2.61 °C at shallow depths (50–350 m). Model performance generally decreased with depth, highlighting challenges in deep temperature prediction. State-level analyses emphasized the importance of considering local geological factors. This study provides valuable insights for designing efficient underground facilities and infrastructure, underscoring the need for depth-specific and region-specific modeling approaches in subsurface temperature assessment.

Science & Technology - Other Topics↗
DOE OSTI2026

Robust optimization of flexible diafiltration systems for critical mineral separations

This paper provides major contributions in expanding the literature for membrane process design with critical mineral recovery applications and showcasing the importance of robust design techniques for reducing risks of underperformance in such systems. Here, a membrane process flowsheet featuring PrOMMiS membrane models for recovering lithium/cobalt from spent batteries is showcased, uncertainty in membrane sieving and localized fouling are considered, and robust designs are obtained using the PyROS toolset. This paper is intended for a general audience of researchers working in critical minerals, membranes, and optimization related areas.

36 MATERIALS SCIENCE↗
DOE OSTI2024

In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back

Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving the Schrödinger equations and the increasing computational cost with the size of the molecular system. In response, there has been a surge of interest in leveraging artificial intelligence (AI) and machine learning (ML) techniques to in silico experiments. Integrating AI and ML into computational chemistry increases the scalability and speed of the exploration of chemical space. However, challenges remain, particularly regarding the reproducibility and transferability of ML models. This review highlights the evolution of ML in learning from, complementing, or replacing traditional computational chemistry for energy and property predictions. Starting from models trained entirely on numerical data, a journey set forth toward the ideal model incorporating or learning the physical laws of quantum mechanics. This paper also reviews existing computational methods and ML models and their intertwining, outlines a roadmap for future research, and identifies areas for improvement and innovation. Ultimately, the goal is to develop AI architectures capable of predicting accurate and transferable solutions to the Schrödinger equation, thereby revolutionizing in silico experiments within chemistry and materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Relithiation process for direct regeneration of cathode materials from spent lithium-ion batteries

A method for the regeneration of cathode material from spent lithium-ion batteries is provided. The method includes dissolving a lithium precursor in a polyhydric alcohol to form a solution. Degraded cathode material containing lithium metal oxides are dispersed into the solution under mechanical stirring, forming a mixture. The mixture is heat treated within a reactor vessel or microwave oven. During this heat treatment, lithium is intercalated into the degraded cathode material. The relithiated electrode material is collected by filtration, washing with solvents, and drying. The relithiated electrode material is then ground with a lithium precursor and thermally treated at a relatively low temperature for a predetermined time period to obtain regenerated cathode material.

Belharouak, Ilias↗
DOE OSTI2023

Photoelectrochemical materials for solar energy conversion

Research and development on semiconductors for applications in solar energy conversion has witnessed rapid growth over the past several decades. With the aim of producing chemical fuels from sunlight, intense research efforts have focused on the discovery of semiconductors with crystalline structures and chemical compositions that have the potential to satisfy the complex set of required photoelectrochemical properties. This chapter focuses on the foundational structure-property relationships of selected oxide and nitride semiconductors relevant to their uses as n-/p-type photoelectrodes and as photocatalysts. Their solid-state structures and compositions are described, with a special emphasis on strategies proven effective at targeting suitable band gaps with strong visible-light absorption, efficient charge separation and diffusion of charge carriers, and optimal band edge energies for driving surface redox reactions for water splitting.

O’Donnell, Shaun↗