Search NASA⌕ Search

SEARCH · Search NASA

Results for “Assistive Technology”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

596 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Advancing Building Performance: Field Results of Thin-Glass Triple-Pane Window Demonstrations

To meet California and the nation's ambitious energy targets, energy use in the building sector must drop dramatically. Windows continue to be the lowest thermally performing envelope system in the nation's buildings, resulting in poor overall envelope performance and potential impacts to human health and comfort. Current best practice new window performance is typically met by double-pane low-solar-gain glazing. Thin-glass triple-pane windows are a highly promising next step forward in performance and have been deployed in two California multi-family sites to quantify field performance and building energy savings. The technology assessed offers the performance benefits of traditional triple-pane but with little increase in weight or cost, enabling incremental costs competitive with alternative energy reduction solutions for the building envelope. This paper covers a detailed investigation into the demonstration project and measured performance benefits of the windows after a full year of data collection.

Hart, Robert↗
DOE OSTI2025

Entanglement properties of SU(2) gauge theory

Understanding how isolated quantum systems thermalize is central to both fundamental physics and the development of quantum technologies. In this Perspective, we present recent and new results on thermalization in nonabelian gauge theory from exact real-time simulations of two-dimensional lattice models. We discuss tests of the eigenstate thermalization hypothesis, entanglement entropy dynamics, the absence of persistent non-thermal states, spectral signatures, and measures of quantum complexity. Our new results include a two-step thermalization process in localized regions and the role of higher gauge field representations. These findings suggest that thermalization in gauge theories may offer a test case for quantum advantage.

information theory and computation↗
DOE OSTI2025

Establishing model credibility for process-microstructure-property relationships in additive manufacturing using exascale computing

Additive Manufacturing (AM) of alloys holds significant promise as a disruptive technology in various industries, yet its adoption is often hindered by challenges in achieving consistent part quality. These issues are primarily due to the complex process-microstructure-property (PSP) relationships inherent to AM. Computational models can greatly aid in understanding these relationships, but their widespread impact and adoption has been limited by a lack of validated, open-source, and computationally efficient PSP modeling frameworks and hardware limitations. Here, this study leverages the ExaAM software suite and data from the AMBench-2018 series of laser powder bed fusion (LPBF) benchmark experiments to perform a comprehensive model assessment, including verification, validation, sensitivity analysis, and uncertainty quantification. The RADICAL-EnTK workflow manager was used to perform an ensemble of heat transport, solidification, and mechanical response simulations on the exascale computer Frontier, considering uncertainties in critical model inputs such as laser spot size and nucleation parameters, and consisting of 125 explicit grain structure simulations and 7875 crystal plasticity simulations. For a selected location within the Inconel 625 AMBench-2018 test artifact, sensitivity analysis and uncertainty quantification were performed using the predicted distributions of grain structure and mechanical properties. Qualitative agreement was found between the predicted grain size and texture and the observed AMBench-2018 microstructure, the mean predicted yield stress was within 5% of the experimental measurement mean, and the mean predicted engineering stress at 5% strain was within 10% of the experimental measurement mean. The insights gained from development and validation of the ExaAM PSP modeling framework will help guide future directions for enhancing the credibility and reliability of PSP models in AM, thereby accelerating the adoption of AM technologies in various industries.

Additive manufacturing↗
DOE OSTI2025

Unique Conductivity Behavior in Water-In-Salt Electrolytes Driven by Ion Clusters

Understanding and predicting ion transport in aqueous electrolytes are crucial for advanced energy storage and biophysics, and many emergent technologies yet remain elusive. Herein, we introduce a unified framework to quantitatively describe and predict electrolyte conductivity that shifts from conventional molar concentration-based metrics to a volume fraction-based approach. Through analyzing a variety of electrolyte solutions via this perspective, we observe a universal conductivity peak at a 37% volume fraction. Small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations reveal that nanometer-scale ion clusters drive this general behavior. Moreover, key geometric features of the ion transport pathwayssuch as pore size, tortuosity, and connectivityfollow a consistent dependence with respect to the volume fraction, reinforcing the argument for the universal conductivity trend. This paradigm shift opens new avenues for designing high-performance electrolytes and provides transformative insights for advancing studies in many fields, wherein molecular aggregates dictate transport properties.

Nguyen, Huong T. D.↗
DOE OSTI2026

STANDARD REFERENCE MATERIAL CHARPY TESTING FROM HIGH FLUENCE SURVEILLANCE CAPSULE

The Palisades Nuclear Generating Station included in its original surveillance program a surveillance capsule, designated A-60. The capsule was removed from its surveillance position in early 1995 and has been resident in the spent fuel pool since that time. It was harvested to perform characterization of surveillance specimens in this capsule in 2023. This capsule was irradiated to a fluence of 1.96x1020 n/cm2 (E> 1MeV) that is equivalent for more than 150 effective full power years for the current US reactor pressure vessel (RPV) fleet. This capsule contained several materials, including Charpy specimens of standard reference material (SRM) from Heavy-Section Steel Technology (HSST) A533-B Plate 01. To perform Charpy testing of this highly irradiated material, the new Charpy specimen transfer system was designed and implemented on Charpy impact testing machine in the hot cell to accommodate remote testing of these specimens. This new transfer system includes integrated environmental chamber to cool or heat Charpy specimens to the desired temperature. Testing of this highly irradiated material revealed very large shift of Charpy transition temperature, 188oC.

Sokolov, Mikhail [ORNL] (ORCID:0000000256373346)↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2024

Phase stability in the Hf-N and Zr-N systems

Hf and Zr nitrides are promising compounds for many technologically important areas, including high-temperature structural applications, quantum computing, and solar and optical applications. Here, this article reports on a comprehensive first-principles statistical mechanics study of phase stability in the Hf-N and Zr-N binary systems. A high solubility of nitrogen in the hcp forms of Hf and Zr is predicted. The rocksalt forms of HfN and ZrN can also tolerate a high degree of off-stoichiometry through the introduction of nitrogen and metal vacancies. The Hf-N binary favors a family of stacking faulted parent crystal structures at intermediate nitrogen concentrations that host a unique form of short-range order among nitrogen interstitials and vacancies. These phases can accommodate some degree of configurational entropy and remain ordered to temperatures as high as 1200 K.

Monte Carlo methods↗
DOE OSTI2024

System for controller area network payload decoding

A system for decoding an unknown automotive controller area network (“CAN”) message definitions. CAN data vehicle signal mappings are typically held in secret and varied by automotive model and year. Without knowledge of the mappings, the wealth of real-time vehicle data hidden in the automotive CAN packets is uninterpretable—impeding research, after-market tuning, efficiency and performance monitoring, fault diagnosis, and privacy-related technologies. This system can ascertain the CAN signals' boundaries (start bit and length), endianness (byte ordering), signedness (binary-to-integer encoding) from raw CAN data. This allows conversion of CAN data to time series. Interpreting the translated CAN data's physical meaning and finding a linear mapping to standard units (e.g., knowing the signal is speed and scaling values to represent units of miles per hour) can be achieved for many signals by leveraging diagnostic standards to obtain real-time measurements of in-vehicle systems. The system can be integrated into lightweight hardware enabling an OBD-II plugin for real-time in-vehicle CAN decoding or run on standard computers. The system can output a standard DBC file with the signal definition information.

Verma, Kiren E.↗
DOE OSTI2026

Atomic- and Molecular-Scale Interphase Engineering for High-Performance Solid-State Batteries

Solid-state batteries (SSBs) promise a decisive advance beyond conventional Li-ion systems, yet their development remains constrained by persistent solid–solid interfacial instabilities that degrade performance and durability. Interfaces between solid electrolytes and both cathodes and Li metal often exhibit poor wettability, limited physical contact, and high charge–transfer resistance, leading to chemical decomposition, mechanical failure, and impedance growth. Overcoming these limitations requires interphase engineering with atomic-scale precision—capabilities that conventional coating methods cannot reliably deliver. Atomic layer deposition (ALD) and molecular layer deposition (MLD) uniquely meet this need by enabling ultrathin, conformal, and composition-tunable films that stabilize reactive surfaces, suppress parasitic reactions, and regulate Li-metal morphology. Importantly, this Perspective highlights ALD/MLD systems that have already demonstrated effectiveness in liquid-electrolyte cells and discusses how these validated strategies can be deliberately translated to solid-state architectures. By grounding future directions in experimentally proven concepts rather than speculative hypotheses, we outline how atomic- and molecular-scale design principles can accelerate the development of robust, high-performance SSB technologies.

atomic and molecular layer deposition↗
DOE OSTI2025

POWER ELECTRONICS GRID TIED SYSTEM FINAL REPORT

Across the country, electric utilities are grappling with the persistent hurdles of integrating Distributed Energy Resources (DERs). Managing these assets safely and effectively is a complex endeavor, complicated by varying ownership structures, management philosophies, and the diversity of the technologies themselves. Consequently, the industry has seen a proliferation of bespoke system designs, control strategies, and communication frameworks—forcing utilities to spend significant time and resources developing one-off integration solutions. This project addressed these integration hurdles through a scalable demonstration of intelligent devices designed to coordinate and control diverse resources in low-voltage applications. This concept minimized the need for complex integration by transforming the separate DERs into a dispatchable virtual power plant (VPP) with integrated resiliency functions (called a Node). By collaborating with a utility partner, the project focused on developing rapidly implementable use cases that bridged the gap between theoretical control and real-world deployment

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Experimental observation and integrated modelling of proton-beryllium fusion in He and D plasmas at JET

Validated integrated modelling of JET ITER-like wall experiments in which fusion performance is driven by reactions between fast ions and intrinsically present metal wall impurities is presented. A steady-state L-mode plasma with dominant proton-beryllium fusion and neutron yields of up to ≈ 6·10 13 s -1 is developed in He and D, via radiofrequency heating of a H minority. The fusion drive is unambiguously confirmed by the neutral particle analyser, fast ion loss detector, and γ-ray diagnostics. Experiments are analysed via an integrated modelling framework, developed to model the two-stage proton beryllium-fusion chain and produce high-fidelity fusion product source terms. The modelling chain comprises TRANSP and JETTO for plasma core modelling, LOCUST for full orbit product tracking and collisional slowing-down, DRESS to resolve two- and three-body fusion kinematics, and MCNP for neutron transport calculations. Modelling shows that the primary 9 Be(p,n) 9 B reaction is the dominant neutron emitter at naturally present concentrations of beryllium in these experiments. The yield contribution of secondary reactions between fusion products and beryllium, 9 Be(d,n) 10 B and 9 Be(α,n) 12 C, is found to be negligible. The proton-deuteron knock-on effect in D plasmas is modelled, which is calculated to contribute ≈ 25% to the total neutron yield. For both He and D discharges the total computed neutron rates match fission chamber (FC) measurements within the combined experimental and computational uncertainty, with an average discrepancy of ≈ ± 20%. Realistic proton-beryllium neutron sources are propagated through JET’s MCNP neutron transport model which shows that 235 U FCs’ response is sensitive to p–Be source changes, with up to ≈ 10% variation compared to a D–D neutron source. We show that the high-energy tail of the fast proton minority can be studied with multi-foil neutron activation. The framework is also applied to the study of interactions between fast protons and boron impurities, of relevance to ITER. We calculate that in JET conditions a significant alpha source with DT-like energies could be generated through 11 B(p, α)2α fusion, and detected via γ-emission in secondary interactions between fast alphas and boron. The work represents an important step towards validating predictive integrated modelling capabilities for non-standard fusion reactions.

JET↗
DOE OSTI2026

Are CO2 batteries ready for the grid? A cross-cutting deployment checklist

Metal-CO2 batteries have attracted considerable research interest in the past decade due to the utilization of the greenhouse CO2 gas. The low cost and abundance of CO2 feedstocks, together with high specific capacity metal anodes, make this technology a promising candidate for electricity-demanding data centers and grids. However, nonstandard data reporting, ambiguous hardware designs, and questionable cycling parameters have emerged as the field has grown. A clear checklist and standardized reporting format for research and development are urgently needed. Here, after carefully re-analyzing 15 Na-CO2 and 9 Li-CO2 studies, we propose a general checklist and a flowchart for CO2 batteries and related gas conversion systems. Specific performance values from a deployment-oriented perspective, based on commercial lithium iron phosphate batteries, are integrated into the list. We frame research and development efforts around grid-relevant outputs, including areal rate and capacity, cyclability, gas utilization, and safety. While illustrated for Na- and Li-CO2 cells, this framework is directly transferable to other CO2 batteries and air/oxygen batteries, helping align benchtop demonstrations with systematic metrics that ultimately govern future deployment.

Wu, Wenda [ORNL] (ORCID:000900033307687X)↗
DOE OSTI2026

Heavy Element Spectroscopy in the Gas Phase

Actinides are inherently unstable and undergo nuclear decay processes with a concurrent release of energy. Consequently, they are used for nuclear power generation, nuclear weapons, and nuclear medicine. However, the radioactive decay processes also pose significant technological problems for the safe treatment and storage of spent nuclear materials. Cost-effective extraction of the actinides is the key first step in the remediation of nuclear waste, but the appropriate chemical means have yet to be determined. Our present understanding of the chemistry of actinides is limited, with the role of the 5f electrons posing a set of particularly challenging questions. The work reported here is focused on the use of electronic spectroscopy to probe the bonding of small molecules in the gas phase that contains thorium or uranium. Analyses of these data, carried out within the framework of ligand field theory, reveal clear evidence that the 5f electrons are spectators that retain their atomic metal ion character.

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

Integrated Approach to Post-Irradiation Examination of Nuclear Materials at Idaho National Laboratory

Idaho national Laboratory (INL) is the U.S. lead national laboratory for the Department of Energy’s Office of Nuclear Energy (DOE-NE), providing much of the nuclear research, development and demonstration capability needed to move nuclear innovation forward to deployment. INL’s Materials and Fuels Complex hosts a unique combination of personnel, facilities and infrastructure and offers the ability to perform post-irradiation examinations (PIE) of nuclear materials spanning multiple length scales. The ability to combine engineering-scale analysis and sub-microscopic characterization provides valuable insights into fuel and structural material behavior and degradation mechanisms. The holistic approach is used to accelerate these materials demonstration and deployment. Selected studies will be presented, highlighting the impact of these techniques on improving fuel reliability, safety, and efficiency, thereby advancing the development of sustainable and advanced nuclear energy technologies.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Adapting High-Resolution X-Ray Microcalorimeter Spectrometers to Transform MFE Plasma Diagnostics

The aim of this project was to begin the transformation of magnetic fusion energy (MFE) X-ray diagnostics by applying detector technology developed over the past several decades by the astrophysics community. We installed and operated an X-ray microcalorimeter detector system under fusion-relevant plasma conditions at the Madison Symmetric Torus (MST). X-ray microcalorimeter spectrometers combine the best characteristics of instrumentation currently available on fusion devices: the high spectral resolution of crystal spectrometers (2 eV) and broadband coverage provided by pulse-height analysis systems. These spectrometers have small port-access requirements, a key advantage for future MFE experiments. This new plasma diagnostic technique will satisfy the need for multispecies impurity ion data by providing absolute measurements of impurity core accumulation, and it will provide the core impurity ion temperature. This project was a joint effort between Lawrence Livermore National Laboratory (LLNL) and researchers at the Wisconsin Plasma Physics Laboratory (WiPPl) at the University of Wisconsin–Madison (UW–Madison). Megan E. Eckart is the principal investigator at LLNL, which is funded separately from UW–Madison. This final report fulfills the reporting obligation of the UW–Madison effort.

Den Hartog, Daniel J. [Department of Physics, Univ↗
DOE OSTI2026

A Probabilistic Approach to Load Modeling for Central HVAC Systems in Large Commercial Buildings for Retrofit Decisions Under Uncertainty

Retrofitting central HVAC systems in large commercial buildings with advanced technologies like heat recovery chillers (HRCs) offers a significant opportunity to enhance energy efficiency. However, analyzing these retrofits is challenging with traditional whole-building simulation tools, which require intensive calibration and struggle to model innovative system configurations and controls. To overcome these limitations, this study proposes a load profilebased retrofit analysis framework that provides better decisions under uncertainty. The main focus of this paper is the development of a probabilistic load profile model that can be used in the framework by using exploratory data analysis (EDA) of measured building data to properly quantify its inherent variability. A non-parametric Gaussian Process (GP) model was employed to capture the time- and weather-dependent characteristics of the heating load while explicitly modeling its uncertainty. The model's effectiveness is demonstrated through strong predictive performance on unseen data and physically interpretable insights into load behavior. This data-driven, probabilistic load profile serves as a robust and flexible input for subsequent system simulations, enabling a more confident and statistically sound analysis of retrofit potential.

Ham, S W↗
DOE OSTI2025

Maximizing Free Energy Gain

Maximizing the amount of work harvested from an environment is important for a wide variety of biological and technological processes, from energy-harvesting processes such as photosynthesis to energy storage systems such as fuels and batteries. Here, we consider the maximization of free energy—and by extension, the maximum extractable work—that can be gained by a classical or quantum system that undergoes driving by its environment. We consider how the free energy gain depends on the initial state of the system while also accounting for the cost of preparing the system. We provide simple necessary and sufficient conditions for increasing the gain of free energy by varying the initial state. We also derive simple formulae that relate the free energy gained using the optimal initial state rather than another suboptimal initial state. Finally, we demonstrate that the problem of finding the optimal initial state may have two distinct regimes, one easy and one difficult, depending on the temperatures used for preparation and work extraction. We illustrate our results on a simple model of an information engine.

Physics↗
DOE OSTI2026

High-Throughput Uniformity and Defect Monitoring in Low-Temperature Electrolysis Porous Transport Layers Using X-Ray Radiography

Effective quality control (QC) for manufacturing proton exchange membrane water electrolysis (PEMWE) components is critical to enabling widespread adoption of the technology for hydrogen generation. This study investigates X-ray radiography as a novel, high-throughput, potentially in-line QC technique for detecting defects and assessing material property distributions in titanium-based porous transport layers (PTLs) which constitute a crucial component of low temperature PEMWE stacks. We obtain radiographs of a set of fifteen PTLs and model their absorbance of the broadband radiation as a second-order polynomial to account for the non-monoenergetic radiation source used in this study. The resulting model serves as a basis for predicting the areal density and porosity distributions of the PTLs. We find radiography successful in detecting multiple instances of defects, including holes/depressions, cracks, and excess material on the surface or in the pores of the material, demonstrating its potential as a robust in-line QC tool for PTL manufacturing.

08 HYDROGEN↗