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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

From binary to quinary: The rationale and development of GaInAsSbBi for mid- and long-wave infrared sensing applications

Given the added complexity in flux calibration and composition evaluation inherent to quinary alloy growth, what motivates compounding the challenges of III–V-Bi growth with the goal of producing a quinary alloy of GaInAsSbBi for mid- and long-wave infrared sensing applications? Each elemental constituent provides some additional design freedom to achieve the ultimate goal of producing a lattice-matched, bulk random alloy mid-wave infrared III–V material with smooth surface morphology and high optoelectronic quality to enable high performance elevated operating temperatures. Here, this paper reviews the evolution of Bi-containing semiconductor research, focusing on mid- and long-wave infrared materials and highlighting key research findings that motivated the decisions to accept the added complexity in going from binaries like InAs or InSb, to InAsBi, to InAsSbBi, and, finally, to GaInAsSbBi to meet the performance demands of advanced infrared sensing applications.

Webster, Preston T. [Air Force Research Laboratory↗
DOE OSTI2026

Carbon ore, rare earth, and critical minerals (core-cm) assessment of san juan and raton coal basins: what is the future potential of coal in the san juan and raton basins, new mexico and colorado

This report summarizes results from the CORE-CM project in the San Juan and Raton basins of New Mexico and Colorado and ultimately begins to address what is the future of coal in the San Juan and Raton basins. The objective of this project was to determine the nonfuel carbon-based products (CBP), critical minerals, and rare earth elements (REE) potential in coal and related stratigraphic units in the San Juan and Raton basins and adjacent areas. This project delineated favorable geologic terrains and priority areas containing potential CBP, critical minerals, and REE deposits for the DOE mandate, which also is a priority of the NMBGMR and state of New Mexico. This project is important to the state because CBP, critical minerals, and REE resources must be identified before land use decisions are made by government officials. Future mining of CBP, critical minerals, and REE will directly benefit the economy of New Mexico. Furthermore, it is crucial to re-establish a domestic source of critical minerals and REE in the U.S. to help secure the nation’s clean energy future, to reduce the vulnerability of the U.S. to material shortages related to national defense, and to maintain our global technical and economic competitiveness. In addition to these benefits, students at New Mexico Institute of Mining and Technology (NMT) and San

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Zero-Emissions Roadmap for Oakland County

This document outlines a strategic pathway for Oakland County, Michigan to achieve zero emissions by 2050 under the Clean Energy to Communities (C2C) Program. The report encompasses analyses and high-level modeling to guide Oakland County in its emission reduction goals. Key methods include establishing an emissions inventory baseline with ongoing evaluation of future projects’ emissions impacts. Core elements include decommissioning old infrastructure, enhancing energy efficiency, deploying hybrid and ground-source heat pumps, and transitioning to electric fleets. It is proposed to structure the planning process into 5-year strategic plans to make the decarbonization process manageable. The document also emphasizes the need for reassessment of goals and periodic updates to remain adaptive to technological advancements and funding considerations. A matrixed approach for evaluating projects by cost and emissions savings is suggested to optimize decision-making given finite resources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Update on Parallel Process Execution in the Next Generation System Analysis Model (NGSAM)

As of the end of 2022, it is estimated that over 90,000 metric tons of heavy metal (MTHM) of spent nuclear fuel (SNF) were stored at various commercial nuclear power reactor sites (both operating and shutdown) across the United States [1]. The Office of Storage and Transportation within the U.S. Department of Energy’s Office of Nuclear Energy is planning for the transportation, storage, and eventual disposal of SNF and high-level radioactive waste (HLW). To aid in this effort and inform decision-makers about the backend of the spent fuel cycle, systems analysis tools capable of analyzing the various options with respect to SNF and HLW management are being used as well as continuously improved to meet the evolving needs of the program. System analysts typically use these tools to vary underlying assumptions (shipping rates, available facilities, start dates, interim storage capacity, etc.) and study the associated system implications such as timing for clearing sites of SNF, various cost elements, transportation infrastructure acquisition needs, etc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

End-To-End Decentralized Transmission Line Protection in IBR-Dominated Weak Grids Using Interpretable Data-Driven Methods

Traditional transmission line protection relies on predictable synchronous-based fault signatures, which frequently fail under the non-standard, current-limited fault characteristics of Inverter-Based Resources (IBRs). This study investigates how to achieve secure, communication-free fault isolation in IBR-dominated weak grids without relying on opaque, computationally heavy "black-box" machine learning algorithms. To address this, we propose a novel, standalone, and inherently interpretable data-driven protection framework. Unlike centralized methods requiring multi-terminal communication, this decentralized approach relies solely on local measurements using a hierarchical linear-kernel Support Vector Machine (SVM). The methodology decomposes the protection task into four sequential stages that mimic traditional protection elements: fault detection and fault direction identification, fault type classification, zone classification, and location estimation. This multi-stage architecture allows for specialized feature engineering at each stage, combining high computational efficiency with logic traceability. The framework's end-to-end performance was validated via C-code and PSCAD/EMTDC co-simulation, utilizing a real-world utility network and an OEM black-box IBR model. The proposed relay achieves 97.2% overall accuracy and provides a reliable trip decision within a 2.5-cycle window. The results confirm 100% accuracy in fundamental fault detection, reliable zone selectivity across low to moderate fault resistances, and robust security against non-fault transients, proving its immediate viability for integration into commercial numerical relays.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Effects of Material Selection on the Remanufacturability of a Swashplate in an Axial Piston Pump

A swashplate is a critical component in an axial piston pump for motion transformation that undergoes cyclic loading. Traditionally, swashplates are not designed to have multiple lives of operation. According to industry experts, a remanufacturability analysis of swashplates suggests that the scrap rate is high. Among the primary reasons for this high scrap rate is insufficient material on the running surface, especially for subtractive recovery. Therefore, the selection of the proper material and its amount plays a significant role in the fatigue behavior, the remanufacturability of the swashplate, as well as its cost. Analyses addressing fatigue life, remanufacturability, and cost of the swashplate were carried out in this paper through a comparative study utilizing various materials. Recommendations on the material selection that balance the failure consequences, remanufacturability, and cost are provided to guide designers in making informed decisions for alternative design options.

42 ENGINEERING↗
DOE OSTI2024

Hydropower Flexibility and Environmental Tradeoffs Analysis

The importance of hydropower increases as the power grid evolves with the higher variable renewable contribution. As conventional thermal power plants are retired, the importance of hydropower contribution increases to balance the variability of solar and wind generation. However, reservoir water resources are constrained by multiple constraints, and variability of water inflow to the reservoirs creates limitations to dam water releases for power grid needs. Coordinating multiple tools, including water resources, ecological, and technical and economic power grid modeling, informs dam water releases. The case study, the Columbia River Basin multipurpose reservoir project, is operated for hydropower production and many other purposes considering the aquatic habitat of the river basin. Specifically, the river basin fish population is a vital element for the tribal community of the river basin. We integrated a production cost model, a water resource model, and decades of tribal knowledge to analyze the fish-friendly way of operating Columbia hydropower scheduling and grid impacts. We measure power grid impacts for various water resources planning scenarios in terms of total system operating cost, system reliability indicators, changes in wind and solar generation and curtailments, local marginal prices, and revenue for hydropower producers. The study results inform reservoir operating rules decisions from hydropower power producers, system operators, other water users, tribes, environmentalists, and other stakeholders.

Columbia River↗
DOE OSTI2025

Replace Human Intelligence with Fast and Smart Geometric Reasoning and Graph Neural Network to Accelerate Next Gen ModSim Workflows

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Closing the Loop between In Situ Stress Complexity and EGS Fracture Complexity

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

42 ENGINEERING↗
DOE OSTI2026

Development of Biofuel and Bioenergy Processes for Photosynthetic CO 2 Assimilation (CRADA Final Report)

In order to fully exploit algae carbon assimilation for fuels, a preqrequisite is high photosynthetic efficiency and carbon conversion to fuel precursors. In the context of this collaborative project between NLR and EMRE we aim to address aspects of both the biological constraints around photosynthesis-driven carbon assimilation flux as well as elements that bridge the gap between laboratory cultivation and meaningful outdoor deployment, building on the unique capabilities of NLR and EMRE’s algae bioengineering teams. The goal of this work is to improve our understanding of key cellular biochemistry, mass cultivation, and biomass conversion constraints that presently limit the potential bio-oil yield. The proposed first phase of this work will focus on biomass growth improvements by testing hypotheses for alleviating identified metabolic and photophysiological bottlenecks. The results of this work could inform decisions by stakeholders (e.g., industry, community, investors) on the design and deployment of a sustainable biofuel supply chain from algae.

09 BIOMASS FUELS↗
DOE OSTI2025

Strong Proton‐Phonon Coupling Drives Fast Ion Transport in Perovskites

Conduction of protons in solids is a cooperative process propelled by phonons, with molecular details obscured by the irregular movements in the thermal bath. It is shown that substitution with Y forms an imaginary phonon mode, instrumental for the function as proton conductor and effectively lowering the activation barrier for proton transport. To untangle the interplay in the exemplary proton conductor BaSn 0.9 Y 0.1 O 3 , its crystallographic structure is determined with high resolution neutron diffractometry and its phonon density of states with density functional theory calculations, experimentally validated by element specific nuclear resonant vibration spectroscopy. Based on phonon analysis, a quantitative transport model is present, which predicts the activation energy and performance by the ratio of ionic radii. Rather than individual vibrational modes, it is the oxygen sub-lattice which exerts its momentum on the protons. The extent of this momentum transfer is governed by the ratio of ionic radii. This model extends the transition state theory by the phonon-phonon interaction and complements the previously proposed idea that lattice dynamics is decisive for proton transport and specifies which properties of the material exactly define the vibration properties.

activation barriers↗
DOE OSTI2025

ON THE LANGUAGE OF RELIABILITY: A SYSTEM ENGINEER PERSPECTIVE

In its classical definition, risk is defined by three elements: what can go wrong, what are its consequences and how likely is it to occur. While this definition makes sense in a regulatory based framework to estimate risk associated to power plants (in terms of core damage frequency and large early release frequency), this approach does not provide a useful snapshot of the health of the plant. A possible alternate path can start by redefining the word “risk” to a broader meaning that better reflects the needs of a system health and asset management decision making process. Rather than asking how likely an event can occur (in probabilistic terms), we can ask how far this event is from occurring. We will show how, given the data available from plant equipment reliability and monitoring/diagnostic/prognostic centers, a margin can be described and determined for all type of maintenance approaches (e.g., corrective or predictive maintenance). We will show how to link SSC margin-based reliability models to system reliability models (i.e., fault trees) in order to assess system/plant health and how to perform margin-based system calculations. These calculations are not solved using classical probabilistic calculations applied to sets (as performed by any PRA code) but, instead, through metric spaces operations (i.e., distance/margin based approach).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Electronic Waste (E-Waste) Recycling: Barriers and Opportunities for State, Local, and Tribal Governments

Electronic waste, or e-waste, encompasses end-of-life electrical and electronic equipment, including computers, monitors, televisions, printers, cell phones, household appliances with electronic components, and small consumer devices containing batteries or circuitry. E-waste is one of the fastest-growing components of the U.S. waste stream, with nearly 8 million tons generated in 2022. E-waste presents two related public-interest considerations. First, e-waste contains economically and strategically important materials: base metals (copper, aluminum, iron, steel), precious metals (gold, silver, platinum group metals), and critical materials such as rare earth elements, gallium, and indium that appear on the U.S. Geological Survey's (USGS) 2025 List of Critical Minerals. Second, many electronic devices contain hazardous constituents - including lead, mercury, cadmium, and brominated flame retardants - as well as rechargeable batteries that can pose fire risks during handling. Effective management of these constituents helps protect workers, communities, and the environment. In the United States, it is estimated that less than 20% of e-waste is formally collected and recycled, leaving over 6 million tons landfilled or otherwise unrecovered. This fact sheet provides state and local decision-makers an overview of (1) e-waste composition and recoverable materials, (2) technology pathways used to recover those materials, and (3) examples of operational and partnership structures used to provide e-waste recycling capacity in the United States. It is intended to complement existing collection-program guidance available through U.S. Environmental Protection Agency (EPA) and other sources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

INTEGRATION OF DATA ANALYTICS WITH SYSTEM HEALTH PROGRAMS

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry developed and regulatory programs. However, these programs have proven to be labor intensive and expensive. There is an opportunity to significantly enhance the collection, analysis, and use of this information to provide more cost-effective plant operation. Additionally, there is an acute industry need to leverage advanced technology to reduce costs and improve operational effectiveness. The goal of this paper is to provide effective and efficient analytical methods and tools to support risk-informed decisions for the equipment reliability and asset management programs at nuclear power plants. This is accomplished by creating a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). Here we are supporting typical system engineer decisions regarding maintenance activity scheduling and component ageing management. This is performed in a risk-informed context where herein the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow. A challenge is that the structure of this workflow strongly depends on the decision that needs to be made, the type of data available, and the constraints that need to be considered. Current methods are designed to provide specific answers to specific problems; however, these methods might prove to be inadequate even when problem settings slightly change (e.g., different types of requirements, additional dependencies between system reliability and economics). We tackled this challenge by designing framework in a flexible and modular fashion such that the user can assemble and customize his/her own workflow that integrates SSC economic lifecycle models (e.g., maintenance and replacement costs), system reliability models, and optimization methods.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Hydrogen Sustainable Infrastructure Guidelines (H2SIG)

Infrastructure interacts with major global challenges inclusive of climate change, resilience, equity and social justice, environmental protection and biodiversity, public health, and economic recovery. This effort directly addresses how to apply sustainability assessments to the unique aspects of hydrogen (H2) infrastructure projects using the Envision® sustainability framework developed by the Institute for Sustainable Infrastructure (ISI). Envision is a flexible system of criteria and performance objectives to aid decision makers and help project teams identify sustainable approaches during planning, design and construction of infrastructure projects that will continue throughout the project’s operations, maintenance, and end-of-life phases. The goal of this work is to support those interested in conducting sustainability assessments for hydrogen infrastructure projects. Through this work the team has developed hydrogen-specific guidelines and best practices to assist project developers, investors and regulators in straightforward application of the Envision framework to systematically enhance clarity and increase objectivity across hydrogen projects. Subject matter experts from 20 different organizations (industry, non-profits, municipalities, emissions regulators, national labs) were engaged through 7 focus groups to discuss the H2-prioritized Envision requirements and elements to be included in the guidelines. In addition to these guidelines, the team conducted case studies as a way of demonstrating and informing the guidelines and providing examples or ideas for implementing sustainability in future projects. Through this study, the authors found that hydrogen infrastructure projects can incorporate many sustainable practices including reducing GHG emissions affecting climate change, reducing air pollutant emissions affecting the health of communities, synergistically handling waste byproducts, integrating into existing infrastructure, incorporating renewable energy, and addressing equity and environmental justice. Additionally, hydrogen infrastructure projects could benefit from 2-way communication engagement and collaborative planning with stakeholders, educational awareness of hydrogen technology, tracking and reporting on water use and water quality, and including monetized environmental and social benefits in life-cycle cost estimates. This document is the final technical report for the Hydrogen Sustainability Assessment Methods for Project Development project. While the main focus of the report is to provide guidelines for applying sustainability to hydrogen infrastructure, there are sections within the appendix providing completed project tasks and methodology.

08 HYDROGEN↗
DOE OSTI2025

Leveraging System Dynamics to Predict the Commercialization Success of Emerging Energy Technologies: Lessons from Wind Energy

The United States urgently needs to tackle the climate crisis while enhancing energy security and resiliency. The complexity of the U.S. energy system, with its interconnected elements, makes predicting future states challenging, especially with the introduction of novel energy systems like wind, solar, clean hydrogen, and advanced nuclear technologies. Modern systems engineering methods and tools can provide deeper insights into these dynamics and future behaviors. This research aims to develop a comprehensive model that captures the main elements and behaviors of new energy technologies within the existing energy system. We hypothesized that the market uptake of novel energy systems is influenced by multiple diverse factors, such as technological learning, availability of resources, and economic incentives; examined the history of electricity generation using land-based wind technologies; and developed a system dynamics model to investigate the relationships between capacity growth and influencing factors, both internal and external. The developed model yielded outcomes that confirmed the hypothesized dynamics of wind energy system diffusion through a quantitative comparison of installed capacity and highlighted the significant influence of resource availability, federal incentives (production tax credits), and technological learning on capacity growth and cost reduction. This research aims to support informed decision-making for investments in novel energy systems and aid in developing effective policies for technology deployment.

17 WIND ENERGY↗
DOE OSTI2024

Simulative Prediction of Solar Illuminance and Application of the Du-Sharples Model in Estimating Adapted Daylighting Metrics for an Urban Environment

The practice of daylighting in indoor spaces can significantly reduce electricity consumption and carbon emissions, improve human productivity, and enhance mood and cognitive perception. This work discussed the recent developments in daylighting science and practice, computed the periodic variations in average diurnal daylight levels for each month, quantified in terms of global horizontal illuminance and diffuse horizontal illuminance, for Kolkata, India, a city with tropical wet and dry climate, with two empirical luminous efficacy models of estimating solar illuminance, and assessed daylighting metrics with the Du-Sharples model. A program was formulated that could compute and generate daylight data with monthly-hourly solar irradiation data and the Du-Sharples model was utilized to predict dirt-corrected daylighting metrics for three glazing transmittance values and five elemental carbon deposition levels on glazing material. The highest monthly average global horizontal illuminance is recorded in April (64.05 klx for Littlefair model and 66.82 klx for Muneer-Kinghorn model) and the highest monthly average diffuse horizontal illuminance is recorded in July (33.23 klx for Littlefair model and 30.63 klx for Muneer-Kinghorn model). Further, the computed yearly average global and diffuse horizontal illuminance levels agree well with a previous study that applied the Perez model. Yearly average horizontal work surface illuminance level remained >1.5 klx for window-towall area ratio >30 %. The approach adopted in this work and the temporal variation charts of computed exterior daylight level data may assist building service engineers, architects, and indoor lighting practitioners in making informed policy decisions at different stages of building planning.

Engineering↗
DOE OSTI2024

Introduction to Special Issue on the Early History of Nuclear Fusion

This introductory paper to the special issue of Fusion Science and Technology commemorates early research on fusion conducted at Los Alamos (the singular entity denoted Los Alamos Laboratory/Los Alamos Scientific Laboratory/Los Alamos National Laboratory at different times is designated “Los Alamos” in this paper) in support of the eventual H-bomb program. We survey the historical origins of the thermonuclear program, what was known of fusion reactions at the outbreak of the war, and the remarkable breakthroughs involving particularly the prospect of deuterium-tritium (DT) reactions conducted during the war, and we summarize the papers in this volume. Much of the nuclear fusion technical history presented herein has not been previously reported. Papers describe aspects of fusion science during these days, on shock hydrodynamics and on electron-radiation coupling, and on nuclear physics including the discoveries of resonances in both the DT cross section and in the lithium tritium-breeding cross section. Three papers follow our colleague Mark Paris’s finding Arthur Ruhlig’s 1938 paper on the first observation of DT fusion: one on how it influenced subsequent Manhattan Project research, another on a modern calculation of that historic experiment, and a third that has repeated the experiment using modern experimental capabilities. Other papers discuss how the first H-bomb test, Ivy Mike, led to the discovery of the new elements einsteinium and fermium and how the DT fusion processes played a key role in our universe’s development after the Big Bang. We also present a paper that analyzes the pioneering Cambridge University 1934 experiment by Marcus Oliphant, Paul Harteck, and Ernest Rutherford where deuterium-deuterium fusion was first observed and that describes how Ernest Lawrence missed identifying fusion in 1933. Finally, we present a summary of early concepts for controlled fusion energy that grew out of wartime discussions at Los Alamos. The papers show how J. Robert Oppenheimer played a leading technical role in the early developments of the H-bomb, before his later opposition—our first paper in this issue addresses the U.S. Department of Energy’s 2022 vacation of the earlier 1954 decision to revoke his security clearance.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗