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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 OSTI2025

Evaluation of U10Mo Fuel Plate Performance Modeling Over Hot Isostatic Press and Hydraulic Bending for MURR DDE Plates

The United States High Performance Research Reactor Program’s objective is to reduce the amount of highly enriched uranium currently implemented in research reactors. The conversion of these research reactors requires designing a monolithic U10Mo plate fuel, with the fuel plate geometry being dependent on each research reactor. The process of forming the plates includes a hot isostatic pressing (HIP) to manufacture a prototypic plate. In the case of the Missouri University Research Reactor (MURR) design demonstration element (DDE) plate manufacture, plates that have been through HIP are then curved using dies and a hydraulic press to impart the desired curvature. Both fabrication processes impart residual stresses into each fuel plate region, with the curvature of the plates taking some regions of the fuel plate up to their material yield stresses, accompanied by plastic strain. The amount of plastic strain and stress imparted onto each MURR DDE plate is determined by the radius of curvature, thickness of each region, and overall width of the fuel plates. Furthermore, this work aims to predict the yield stresses and strain using ABAQUS to simulate the proposed fabrication process of the MURR DDE plates, accompanied by discussion over the stresses and strains as to their relation to nuclear fuel performance and the impact they will have during early irradiation.

ABAQUS↗
DOE OSTI2026

Maintenance strategy, structural design, and site layout of the ST-E1 fusion power plant

An effective fusion reactor maintenance scheme enables safe operations and short downtimes. This in turn leads to high availability, which is critical to the commercial viability of a power-producing plant. In tokamak-based fusion power plants, the chosen maintenance approach has a significant impact on the spatial design of the tokamak, as well as the surrounding infrastructure, and therefore needs to be considered from the outset. Tokamak Energy has developed a pre-concept design of a fusion power plant, ST-E1. This work describes the major drivers and constraints that have been considered, presents the tokamak architecture and chosen maintenance regime, and discusses how this enables the plant’s two-phased approach to demonstrating commercial operations. It also shows the implications for the design of other systems areas, in particular the machine structural arrangement and bioshield and hot cell layout. The reactor core segmentation and removal scheme replaces entire toroidal segments radially through a large vacuum port, along a single axis only. The result is a change-tolerant machine and plant layout that can accommodate the evolving designs of the tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Structure–Property Linkage in Alloys Using Graph Neural Network and Explainable Artificial Intelligence

Deep learning tools have recently shown significant potential for accelerating the prediction of microstructure–property linkage in materials. While deep neural networks like convolution neural networks (CNNs) can extract physics information from 3D microstructure images, they often require a large network architecture and substantial training time. In this research, we trained a graph neural network (GNN) using phase field generated microstructures of Ni-Al alloys to predict the evolution of mechanical properties. We found that a single GNN is capable of accurately predicting the strengthening of Ni-Al alloys with microstructures of varying sizes and dimensions, which cannot otherwise be done with a CNN. Additionally, GNN requires significantly less GPU utilization than CNN and offers more interpretable explanation of predictions using saliency analysis as features are manually defined in the graph. We also utilize explainable artificial intelligence tool Bayesian Inference to determine the coefficients in the power law equation that governs coarsening of precipitates. Overall, our work demonstrates the ability of the GNN to accurately and efficiently extract relevant information from material microstructures without having restrictions on microstructure size or dimension and offers an interpretable explanation.

Chemistry↗
DOE OSTI2026

Challenges for Megawatt-Scale Artificial Intelligence Rack Infrastructure

As artificial intelligence (AI) computing densities continue to increase, industry is pursuing megawatt-scale rack architectures that require tightly coordinated advances in electrical power delivery, thermal management, operations, and infrastructure integration. This document summarizes the primary technical challenges for achieving this target.

Nawaz, Kashif [ORNL] (ORCID:0000000251612491)↗
DOE OSTI2026

Few is different: deciphering many-body dynamics in mesoscopic quantum gases

Emergent macroscopic descriptions of matter, such as hydrodynamics, are central to our description of complex physical systems across a wide spectrum of energy scales. The conventional understanding of these many-body phenomena has recently been shaken by a number of experimental findings. Collective behavior of matter has been observed in mesoscopic systems, such as high-energy hadron–hadron collisions, or ultracold gases with only a few strongly interacting fermions. In such systems, the separation of scales between macroscopic and microscopic dynamics (at the heart of any effective theory) is inapplicable. To address the conceptual challenges that arise from these observations and explore the universality of emergent descriptions of matter, the EMMI Rapid Reaction Task Force was assembled. This document summarizes the RRTF discussions on recent theoretical and experimental advances in this rapidly developing field. Leveraging technological breakthroughs in the control of quantum systems, we can now quantitatively explore what it means for a system to exhibit behavior beyond the sum of its individual parts. In particular, the report highlights how the (in)applicability of hydrodynamics and other effective theories can be probed across three principal frontiers: the size frontier, the equilibrium frontier, and the interaction frontier.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Dust Survival in Galactic Winds

This repository contains three-dimensional volumetric data from an Eulerian hydrodynamical simulation (conducted on a uniform Cartesian grid) generated by the Cholla hydrodynamics code. The datasets contain snapshots (full-grid, projections, and slices) in the HDF5 format of a multi-phase medium in which a hot, diffuse, dust-free background wind accelerates a cool, dense cloud of gas and dust. This scenario is intended to represent a supernova-driven galactic outflow, in which hot supernova winds are thought to accelerate cool interstellar medium material out of the galactic disk into the surrounding circumgalactic medium. There are three separate datasets for simulations corresponding to three cloud evolutionary scenarios: long-term cloud survival (surv), marginal cloud survival (disr), and cloud destruction (dest). Projection and slice images of the simulations are also included in this repository.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Search for New Physics via Low-Energy Electron Recoils with a 4.2 Tonne-Year Exposure from the LZ Experiment

We report results from searches for new physics models through electron recoils using data collected by the LUX-ZEPLIN experiment during its first two science runs, with a total exposure of 4.2 tonne−years. The observed data are consistent with a background-only hypothesis. Constraints are derived for electromagnetic interactions of solar neutrinos, solar axionlike particles (ALPs), mirror dark matter, and the absorption of bosonic dark matter candidates. The inverse Primakoff process for 57 Fe deexcitation solar ALPs is considered for the first time. These results represent the most stringent constraints to date on keV-scale Primakoff and 57 Fe solar ALPs, bosonic dark matter, mirror dark matter, and neutrino millicharge, while remaining competitive for the other signal models investigated.

Axion-like particles↗
DOE OSTI2023

Surface analysis insight note: Illustrating the effect of adventitious contamination on Pt photoemission peak intensities

Adventitious carbon contaminations are not only omnipresent and used for charge referencing of XPS spectra but also can alter the apparent presence of the element peaks that span over the large spectral window of binding energies. This Insight note describes the effect of an adventitious contamination layer on Pt and presents, in brief, the approach whereby the component spectra are derived for ion beam cleaned Pt samples that can then utilize linear mathematics to peak fit said spectra thus quantifying the amount of each component including that assigned to the contamination itself of Pt metal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A strong and ductile Super Kovar alloy via fully coherent nanoprecipitates

Emerging high-precision technologies demand materials with exceptional dimensional stability and mechanical robustness, as even microscopic thermomechanical deformation can cause functional failure. However, a fundamental trilemma exists: High strength, ductility, and low thermal expansion are mutually exclusive, as strengthening-induced lattice distortions compromise the spin-lattice coupling, which is essential for low thermal expansion. Here, we overcome this trilemma by designing “Super Kovar,” an Fe-Ni-Co-Al-Ta alloy, featuring fully coherent nanoprecipitates. It unifies a 1.0-gigapascal ultimate tensile strength and ∼39% elongation with a Kovar-grade thermal expansion of 3.81 × 10−6 K−1 (100 to 410 K). The key is a dense dispersion of L12 nanoprecipitates that form an almost strain-free coherent interface with the ferromagnetic matrix. Beyond providing precipitation strengthening, these coherent interfaces suppress intrinsic phonons of nanoprecipitates via elastic coupling while avoiding magnetic domain pinning to preserve the Invar effect of the matrix. This reduces the thermal expansion of the precipitates by 56% and achieves a fourfold enhancement in the strength-ductility product, establishing a paradigm for dimensionally stable, ultrastrong alloys.

Yu, Chengyi [University of Science and Technology ↗
DOE OSTI2024

Converting Second‐Order Saddle Points to Transition States: New Principles for the Design of 4π Photoswitches

Abstract Molecular photoswitches have demonstrated potential for storing solar energy at the molecular level, with power densities comparable to commercial batteries and hydroelectric energy storage. However, development of efficient photoswitches is hindered by limitations in cyclability and optical properties of existing materials. We here demonstrate that certain limitations in photoswitches based on electrocyclizations stem from the issue of controlling competition between Woodward‐Hoffmann allowed and forbidden pathways. Our approach moves beyond the traditional view of activation barriers and reveals that second‐order saddle points are crucial in dictating the competition between disrotatory and conrotatory pathways. These insights suggest new opportunities to manipulate the competition between these pathways through geometric constraints, fundamentally altering the connectivity of the potential energy surface. Our study also emphasizes the necessity of multi‐reference methods and the need to conduct higher‐dimensional explorations for competing pathways beyond photoswitch design.

Chemistry↗
DOE OSTI2026

Nuclear Security Risks for HALEU Fuels

There is growing interest in high-assay low-enriched uranium (HALEU) for use in advanced nuclear reactors as a high-energy fuel source. The primary objectives of this report are to identify the security risks that directly result from HALEU and to identify the gaps and challenges it presents from a theft and sabotage perspective. This study focuses on HALEU security risks for the front end of the fuel cycle and includes a review of the supply chain, fuel fabrication, and transport for terrestrial reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Enhancement of Superconductivity in WP via Oxide-Assisted Chemical Vapor Transport

Tungsten monophosphide (WP) has been reported to superconduct below 0.8 K, and theoretical work has predicted an unconventional Cooper pairing mechanism. Here we present data for WP single crystals grown by means of chemical vapor transport (CVT) of WO3, P, and I2. In comparison to synthesis using WP powder as a starting material, this technique results in samples with substantially decreased low-temperature scattering and favors a more three-dimensional morphology. We also find that the resistive superconducting transitions in these samples begin above 1 K. Variation in Tc is often found in strongly correlated superconductors, and its presence in WP could be the result of influence from a competing order and/or a non-s-wave gap.

Chemistry↗
DOE OSTI2024

Hamiltonian switching control of noisy bipartite qubit systems

Abstract We develop a Hamiltonian switching ansatz for bipartite control that is inspired by the quantum approximate optimization algorithm, to mitigate environmental noise on qubits. We demonstrate the control for a central spin coupled to bath spins via isotropic Heisenberg interactions, and then make physical applications to the protection of quantum gates performed on superconducting transmon qubits coupling to environmental two-level-systems (TLSs) through dipole-dipole interactions, as well as on such qubits coupled to both TLSs and a Lindblad bath. The control field is classical and acts only on the system qubits. We use reinforcement learning with policy gradient to optimize the Hamiltonian switching control protocols, using a fidelity objective for specific target quantum gates. We use this approach to demonstrate effective suppression of both coherent and dissipative noise, with numerical studies achieving target gate implementations with fidelities over 0.9999 (four nines) in the majority of our test cases and showing improvement beyond this to values of 0.999 999 999 (nine nines) upon a subsequent optimization by GRadient Ascent Pulse Engineering (GRAPE). We analyze how the control depth, total evolution time, number of environmental TLS, and choice of optimization method affect the fidelity achieved by the optimal protocols and reveal some critical behaviors of bipartite control of quantum gates.

Physics↗
DOE OSTI2024

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

Chemistry↗
DOE OSTI2025

Modulation of thermal conductivity of iron-doped ß-Ga2O3 by helium-ion irradiation

This study examines the impact of helium-ion irradiation on the thermal conductivity of ß-Ga2O3. A laser-based spatial domain thermoreflectance technique is used to investigate thermal conductivity map for both un-irradiated and irradiated ß-Ga2O3, which are then validated against simulation results derived from density functional theory-based phonon transport simulations. Since helium bubble evolution was ob- served at the nanoscale using transmission electron microscopy, the simulation study was carried out on eight distinct helium-induced sites in ß-Ga2O3. Our findings indicate a reduction in thermal conductivity for the irradiated samples. Experimental results show a significant reduction in thermal conductivity in irradiated samples, with de- creases of approximately 25% along the [100] direction and 40% along [001] directions. Phonon transport simulations closely replicate these findings, particularly when helium occupying interstitial sites, predicting reductions of ˜53% along [100] and ˜50% along [001] directions. This work underscores the role of irradiation-induced microstructural changes in the heat transport properties of ß-Ga2O3 which is crucial for its application in sensor devices in extreme environments.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Long‐Life Lithium‐Metal Batteries with an Ultra‐High‐Nickel Cathode and Electrolytes with Bi‐Anion Activity

Abstract Anion chemistry in electrolytes can greatly dictate the nature and quality of passivation layers on both cathode and anode surfaces. This will be more significant when it comes to highly reactive Li‐metal anode and aggressive high‐nickel cathodes. Herein, a competitive bi‐anion activity is found in electrolytes with the co‐existence of two anions, which leads to a controlled Li‐salt decomposition kinetics and entirely favorable interphasial chemistry on both Li‐metal anode and ultrahigh‐nickel cathode. The proposed bi‐anion localized high‐concentration electrolytes are demonstrated to exhibit superior electrochemical compatibility toward Li metal and long‐term cycling stabilities under both 4.4 and 4.6 V in Li‐metal batteries with ultrahigh‐nickel cathode. This study sheds fresh light on dendrite‐free Li‐metal anodes and provides guidance to achieve high‐energy‐density batteries.

Chemistry↗
DOE OSTI2024

From wide to ultrawide-bandgap semiconductors for high power and high frequency electronic devices

Abstract Wide and ultrawide-bandgap (U/WBG) materials have garnered significant attention within the semiconductor device community due to their potential to enhance device performance through their substantial bandgap properties. These exceptional material characteristics can enable more robust and efficient devices, particularly in scenarios involving high power, high frequency, and extreme environmental conditions. Despite the promising outlook, the physics of UWBG materials remains inadequately understood, leading to a notable gap between theoretical predictions and experimental device behavior. To address this knowledge gap and pinpoint areas where further research can have the most significant impact, this review provides an overview of the progress and limitations in U/WBG materials. The review commences by discussing Gallium Nitride, a more mature WBG material that serves as a foundation for establishing fundamental concepts and addressing associated challenges. Subsequently, the focus shifts to the examination of various UWBG materials, including AlGaN/AlN, Diamond, and Ga 2 O 3 . For each of these materials, the review delves into their unique properties, growth methods, and current state-of-the-art devices, with a primary emphasis on their applications in power and radio-frequency electronics.

Materials Science↗
DOE OSTI2025

Multiscale aperture synthesis imager

Synthetic aperture imaging has enabled breakthrough observations from radar to astronomy. However, optical implementation remains challenging due to stringent wavefield synchronization requirements among multiple receivers. Here we present the multiscale aperture synthesis imager (MASI), which utilizes parallelism to break complex optical challenges into tractable sub-problems. MASI employs a distributed array of coded sensors that operate independently yet coherently to surpass the diffraction limit of single receiver. It combines the propagated wavefields from individual sensors through a computational phase synchronization scheme, eliminating the need for overlapping measurement regions to establish phase coherence. Light diffraction in MASI naturally expands the imaging field, generating phase-contrast visualizations that are substantially larger than sensor dimensions. Without using lenses, MASI resolves sub-micron features at ultralong working distances and reconstructs 3D shapes over centimeter-scale fields. MASI transforms the intractable optical synchronization problem into a computational one, enabling practical deployment of scalable synthetic aperture systems at optical wavelengths.

electrical and electronic engineering↗