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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Data mining the missing ordered phases of Li/Na metal oxides

Data-driven discovery of Li-ion and Na-ion battery materials has been pioneered by generic materials data platforms such as the Materials Project. After decades of progress, it is timely to ask whether there remain underexplored compositional spaces. Here, in this work, we present a systematic data-mining effort to uncover missing ordered binary, ternary and quaternary Li/Na-containing metal oxides using high-throughput density functional theory (DFT). Building on 19,120 stable and metastable oxides entries from the Materials Project, we performed 13,245 additional calculations through isovalent substitutions of known ground states, experimentally reported compounds, and specific prototype structures. Our study identifies 36 new ground states within the GGA/GGA + U convex hull and 45 within the r 2 SCAN convex hull. Additionally, we identified 840 metastable compounds from GGA/GGA + U and 979 from r 2 SCAN that are absent in the present Materials Project databases. Moreover, we have tripled the metastable materials in compositional spaces with a molar ratio of cation/anion >1, highlighting the overlooked opportunities in this compositional space.

25 ENERGY STORAGE↗
DOE OSTI2025

Low-symmetry polymorph of GaP upends bonding paradigms of metallic high-pressure III–V compounds

Here, the pressure-induced polymorphism of binary octet compounds has long been considered a settled problem although the possible atomic disordering of some phases remains a puzzling observation. Taking GaP as a case study, we conclude, through x-ray microdiffraction and first-principles calculations, that its high-pressure metallic phase (previously reported as being disordered) adopts in fact an ordered base-centered monoclinic structure previously unknown in this class of compounds. The formation of layered patterns with variable degrees of interlayer dimerization, as observed in GaP, marks a paradigm shift of our understanding of ordering in octet high-pressure phases which calls for a more extensive re-examination. A rich polymorphism with fine tuning of chemical and physical properties can be envisioned.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Synergistic learning with multi-task DeepONet for efficient PDE problem solving

Multi-task learning (MTL) is an inductive transfer mechanism designed to leverage useful information from multiple tasks to improve generalization performance compared to single-task learning. It has been extensively explored in traditional machine learning to address issues such as data sparsity and overfitting in neural networks. In this work, we apply MTL to problems in science and engineering governed by partial differential equations (PDEs). However, implementing MTL in this context is complex, as it requires task-specific modifications to accommodate various scenarios representing different physical processes. To this end, we present a multi-task deep operator network (MT-DeepONet) to learn solutions across various functional forms of source terms in a PDE and multiple geometries in a single concurrent training session. We introduce modifications in the branch network of the vanilla DeepONet to account for various functional forms of a parameterized coefficient in a PDE. Additionally, we handle parameterized geometries by introducing a binary mask in the branch network and incorporating it into the loss term to improve convergence and generalization to new geometry tasks. Our approach is demonstrated on three benchmark problems: (1) learning different functional forms of the source term in the Fisher equation; (2) learning multiple geometries in a 2D Darcy Flow problem and showcasing better transfer learning capabilities to new geometries; and (3) learning 3D parameterized geometries for a heat transfer problem and demonstrate the ability to predict on new but similar geometries. Finally, our MT-DeepONet framework offers a novel approach to solving PDE problems in engineering and science under a unified umbrella based on synergistic learning that reduces the overall training cost for neural operators.

42 ENGINEERING↗
DOE OSTI2025

Design of novel refractory equiatomic multi-principal elemental alloys based on Mo-Nb-Ti system for Gen IV reactor applications

Excellent irradiation damage resistance demonstrated by multi-principal elemental alloys (MPEAs) has sparked significant interest among researchers, prompting exploration into their vast compositional space, to validate their suitability for nuclear applications. A combined approach of thermodynamic and empirical parameters calculations alongside CALPHAD (CALculation of PHAse Diagrams) for phase formation predictions enable high-throughput material selection for sophisticated applications like nuclear, overcoming laborious and time-consuming experiments. Key thermodynamic and empirical parameters for eight novel equiatomic MPEAs, based on seven low thermal neutron cross section refractory elements, for predicting phase formation were calculated, and equilibrium and non-equilibrium simulations in CALPHAD were employed to comprehensively model the systems. Pseudo binary phase diagram simulations showed that Zr, V or equiatomic CrV additions to the base MoNbTi alloy (MoNbTi-Zr, MoNbTi-V and MoNbTi-CrV alloys) favor the formation of isomorphous body-centered cubic (BCC) phase at high temperatures, while Cr, Al, equiatomic ZrV, or equiatomic CrAl additions (MoNbTi-Cr, MoNbTi-Al, MoNbTi-ZrV or MoNbTi-CrAl alloys) limit the solubility of them. Equilibrium CALPHAD simulations at 750 oC were consistent with XRD results on MoNbTi, MoNbTiZr and MoNbTiCr alloys, and partially for others. Notably, elemental segregation observed in the backscattered electron (BSE) scanning electron microscopy (SEM) images of the alloys was accurately simulated through non-equilibrium Scheil solidification calculations in CALPHAD, further verified by experiments. The precipitation of TiCr2 Laves phase in Cr containing MoNbTiCr and MoNbTiCrAl was accurately predicted while discrepancies were noted in MoNbTiCrV. The equilibrium simulations also provided insights into phase compositions at specific temperatures offering a pathway for tailoring the desired microstructure and properties of these systems. Empirical parameters calculations successfully predicted random solid solution in the base MoNbTi alloy, and with an exception in MoNbTiV and MoNbTiAl, predicted intermetallic precipitation in the rest, especially, Laves phase precipitation in Cr containing alloys.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Quantifying uncertainties in α -nucleus reaction dynamics informed from first principles

The ab initio symmetry-adapted no-core shell model is a microscopic many-body method which naturally describes challenging collective and clustering features of atomic nuclei. Wave functions and observables computed with realistic nucleon-nucleon forces in this framework are tied to first principles, and are hence well-suited for rigorous uncertainty quantification. We discuss α-deuteron and α- 12 C cluster potentials informed by symmetry-adapted calculations, and propagate uncertainties in the effective binary cluster method as well as those in the nuclear interaction to reaction observables, namely scattering phase shifts, cross sections, partial widths and resonance energies. Here, we find that the overall uncertainties are dominated by those originating in the underlying nuclear force, speaking to the need for tighter constraints on realistic nucleon-nucleon interactions.

Ab initio↗
DOE OSTI2026

59 Co(p,X) spallation reaction cross sections for 250 MeV to 2 GeV protons

Cobalt is an advantageous target for probing the physics of nuclear spallation, because it is a naturally mono-isotopic element ( 59 Co), and its per-nucleon binding energy (BE/A = 8.768 MeV) is near the maximum value for all nuclei. We measured nuclear spallation cross sections for the 59 Co(p,X) reaction at five kinetic energies ranging from 250 MeV to 2 GeV. Cross sections for the production of 58 Co, 57 Co, 57 Mn, 56 Co, 56 Mn, 56 Cr, 55 Fe, 53 Fe, 54 Mn, 52 Mn, 51 Cr, 49 Cr, 48 V, 47 Sc, 46 Sc, 44 Sc, and 44 Scm are reported. Where comparable data exist in the EXFOR reaction database, we find that our measured cross sections generally agree. In many cases, we provide data for reactions or energies not currently reported in EXFOR. Our cross sections also provide evidence for the presence of α-clusters within the 59 Co nucleus, a surprising result given the asymmetry in Z (27) and N (32) for this nucleus. Finally, we use our measurements to evaluate the accuracy of spallation cross section simulations from GEANT4-based radiation transport toolkit, performed with the INCLXX-, Bertini-, and Binary-ion-cascade (BIC) based physics lists. This benchmarking activity revealed that the simulations overestimated the cross sections by a factor of ∼2–4 on average, and that the INCL-XX physics list provides the most reliable results. This evaluation informs the selection of the GEANT4 physics lists used for the analysis of data from NASA’s Psyche mission, which will measure γ rays and neutrons resulting from spallation reactions occurring on the surface of an asteroid whose surface is thought to be rich in iron-nickel metal.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Do we owe our existence to gravitational waves?

Two heavy elements essential to human biology are thought to have been produced by the astrophysical r-process, which occurs in neutron-rich environments: iodine is a constituent of thyroid hormones that affect many physiological processes including growth and development, body temperature and heart rate, and bromine is essential for tissue development and architecture. Collisions of neutron stars (kilonovae) have been identified as sources of r-process elements including tellurium, which is adjacent to iodine in the periodic table, and lanthanides. Neutron-star collisions arise from energy loss due to gravitational-wave emission from binary systems, leading us to suggest that gravitational waves have played a key role in enabling human life by producing iodine and bromine. We propose probing this proposal by searching in lunar material for live 129 I deposited by a recent nearby kilonova explosion.

Human biochemistry↗
DOE OSTI2024

The influence of cloud cover on the reliability of satellite-based solar resource data

Satellite-based solar resource data are often developed and validated by using binary cloudiness categories: clear sky or overcast cloudy sky. To investigate the reliability of solar resource data in partially cloudy conditions, we estimate cloud fraction using two distinct algorithms: a physical retrieval model using surface observed global horizontal irradiance (GHI) and direct normal irradiance (DNI) and a temporal average of cloud mask data estimated by the observed DNI. Our analysis reveals a significant presence of scattered clouds, broken clouds, and mismatches between satellite- and surface-based cloud data at 17 surface sites across the contiguous United States, though confidently clear and cloudy conditions collectively account for more than 70 % of the data. Solar radiation is computed using the National Solar Radiation Database (NSRDB) algorithm and validated using surface observations. Here, our findings suggest that, in the presence of scattered clouds, NSRDB data for clear-sky conditions can be subject to significant overestimation. In cloudy-sky conditions classified by satellite data, DNI computed by the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) can be underestimated when limited clouds are detected by surface observations. The bias observed in several cloudiness categories indicates that the NSRDB is exceptionally accurate in confidently clear conditions. However, clear-sky conditions with scattered clouds and mismatched cloud data contribute significantly to the overall uncertainties in the NSRDB. Therefore, future improvements in solar resource data should involve development and implementation of satellite-derived cloud fraction and should consider a novel radiative transfer model accounting for amplified cloud reflection. The evaluation within cloudiness categories also provides a physical rationale for the superior performance of FARMS-DNI compared to the Direct Insolation Simulation Code (DISC) in both cloudy-sky and all-sky conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Analysis of correlations between intrinsic ductility and electronic density of states in refractory alloys

High entropy alloys (HEAs) correspond to a new and emerging class of materials that allows us to explore a large composition space to tune mechanical strength and thermal stability. Therefore, to design better alloys, it is important to scan the high-dimensional space of chemistry, composition and temperature. Here, to facilitate this search, we present a method to screen intrinsically ductile body centered cubic (BCC) refractory alloys from electronic structure calculations by using the density of states (DOS) at the Fermi level, g(μ F ). This correlation between intrinsic ductility and g(μ F ) is tested by analyzing group V (V, Nb, Ta) and VI (Mo, W) refractory metals, binary alloys, such as W-Nb, W-V, Mo-Nb and Mo-V, and refractory alloys for which experimental stress-strain measurements are available. In addition, we perform a high-throughput exploration of the entire composition space of a recently proposed alloy system, CrMoNbV, and identify compositions that exhibit high intrinsic ductility.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A reversible solvent segregation transition at grain boundaries in gold-platinum alloys

Solute segregation to grain boundaries in polycrystalline metals and ceramics is a well-known phenomenon that reduces the total energy of the material. In this letter, the segregation of the solvent (Au) to grain boundaries in a binary Au 1-x Pt x (x = 0.15 to 0.18) alloy is demonstrated. After heating in the range of 500 °C to 600 °C and quenching to room temperature, grain boundaries in the alloy are enriched in Au at a mean level of ∼ 4 atoms/nm 2 . When the alloy is annealed at 300 °C and quenched, the mean grain boundary composition is closer to the bulk composition. When the alloy is reheated to 500 °C, the segregation is reestablished, demonstrating that the transformation from the strongly segregated complexion to the weakly segregated complexion is reversible. The driving force for the solvent segregation is likely the lower grain boundary energy of Au in comparison to Pt.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management

Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

A unified large language model–based framework for heterogeneous PV image diagnosis

With advances in imaging technologies, modern photovoltaic (PV) systems generate large volumes of heterogeneous image data, including visible, electroluminescence (EL), and infrared (IR) images. Existing PV image analysis models, particularly deep learning approaches, are typically task-specific and lack cross-modality generalization. To address this limitation, this paper proposes an open-source large language model (LLM)–based unified framework for heterogeneous PV image diagnostics. Through task-aware diagnostic prompting, the framework enables analysis of visible, EL, and IR images within a single pipeline, supporting both zero-shot and few-shot inference and binary and multiclass classification. It is compatible with state-of-the-art multimodal LLMs, including ChatGPT, Gemini, Claude, Qwen, and CLIP. The framework is evaluated on PV module condition classification (clean, soiling, snow, hail, and bird droppings) using visible images, cell crack detection using EL images, and hotspot detection using IR images. GPT-5.1 in few-shot mode achieves the best performance, with classification accuracy exceeding 97.3%. Open-source models such as Qwen and CLIP also deliver competitive results on visible images (around 90% accuracy), though their performance is more limited on EL and IR modalities. On the full ELPV dataset, the framework achieves 83.5% zero-shot accuracy, within 2.8% of the supervised CNN baseline, confirming scalability to larger benchmarks. Practical aspects such as reproducibility, response latency, and confidence estimation are systematically analyzed. The framework operates across PV image modalities without modality- or task-specific training, making it well suited as a rapid pre-screening tool to support downstream detailed diagnostics. A benchmark dataset of diverse labeled PV images is also released.

Li, Baojie↗
DOE OSTI2025

Synthesis and characterization of rhenium chalcogenides for nuclear waste management

A new synthetic approach to binary rhenium (Re) chalcogenides was investigated to aid in the preparation of analogous technetium (Tc) compounds for Tc waste management efforts. The Boron-Chalcogen Mixture (BCM) method was utilized for the first time to prepare polycrystalline powders of ReS 2 , ReSe 2 , and Re 2 Te 5 using a perrhenate, NaReO4, as a rhenium source. Single crystals of ReS 2 were also synthesized using the combined BCM and molten flux methods by adding a K 2 CO 3 flux to the reagent mixture. Thermal analysis using TGA/DSC revealed negligible changes from ambient temperature up to ∼300 °C followed by the oxidation of the Re chalcogenides. High Temperature PXRD was used to investigate the crystallinity of ReS 2 at various temperatures revealing an increase in crystallinity up to 275 °C followed by a decrease in crystallinity due to oxidation. The research presented herein demonstrates a significant step towards technetium waste treatment efforts.

Boron chalcogen mixture (BCM) method↗
DOE OSTI2025

High-throughput multimodal exploration of a nanocrystalline Cu-Ag library

Sputter-deposited, nanocrystalline Cu-Ag thin films produced across a broad compositional and deposition-parameter space were evaluated to unravel the process-structure-property relationships important for creating hard, conductive electrical contacts and coatings. Combinatorial deposition involving pulsed direct current magnetron sputtering of elemental targets enabled swift examination of nearly the full range of alloy compositions and a relevant portion of deposition atomistics. Several high-throughput characterization modalities were employed to evaluate the chemistry, structure, and properties of the films. The resultant hardness, modulus, film density, crystal texture, and resistivity were analyzed in terms of key deposition characteristics (incident atom kinetic energy and incidence angle) predicted by binary-collision, kinematic Monte Carlo simulations. The study revealed improved hardness, parabolic resistivity dependence on composition, and compositional and process dependencies of film tarnishing. The results are discussed in the context of variations in microstructure and film density. Transmission electron microscopy and X-ray diffraction demonstrate several forms of compositional variation including solute segregation to grain boundaries as well as periodic, intragranular compositional modulations. Annealing of a Cu-rich alloy film exhibiting grain boundary segregation showed that this as-deposited, compositional variation is not stable above 100 °C. Finally, the Cu-Ag system is shown to have potential for hard, conductive, tarnish-resistant and room temperature-stable nanocrystalline thin films across the composition space.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Impulse-driven release of gas-encapsulated drops

Gas-encapsulated drops, much like antibubbles, are drops enclosed in a bubble within a liquid. They show potential as payload carriers in fluid transport and mixing techniques where sound waves can be leveraged to induce the collapse of the gas core and the subsequent release of the drop. Here, the interaction of millimetre-sized gas-encapsulated drops with impulsive laser-induced shock waves is investigated to gain fundamental insights into the release process. Experimental synchrotron X-ray phase contrast imaging, which allows the drop dynamics to be visualised inside the encapsulating bubble, is complemented by numerical simulations to study the intricate physics at play. Three drop dynamical release regimes are discovered, namely the drop impact , partial deposition and jet impact regimes. The regime type is mainly dependent on the shape of the bubble interface impacting the drop and the associated Weber and Reynolds numbers. The drop dynamics of the drop impact and partial deposition regimes show similarities with the canonical configuration of drops impacting flat liquid surfaces, whereas the jet impact regime resembles binary drop collisions, which allows existing scaling laws to be applied to describe the underlying processes. The release of the drop is investigated numerically. The time evolution of the drop dissemination within the surrounding liquid discloses enhanced mixing for dynamics involving high Weber and Reynolds numbers such as the drop impact and jet impact regimes.

42 ENGINEERING↗
DOE OSTI2025

Accurate models of the added mass force of a uniform random distribution of spherical particles or bubbles

The added mass force resulting from the acceleration of a body in a fluid is of fundamental and practical interest in dispersed multiphase flows. Euler–Lagrange (EL) and Euler–Euler (EE) simulations require closure terms for the added mass force in order to accurately couple the conserved variables between phases. Presently, a more thorough understanding of the added mass force in a multi-particle system is developed based on potential flow resulting in a resistance matrix formulation analogous to Stokesian dynamics. This formulation is then used to generate a dataset of added mass resistance matrices for large systems of randomly generated particles. This methodology is used to create a volume fraction corrected binary model for predicting the added mass force in large systems as well as generate statistics of the added mass force in such systems. This work provides clarification to the theory of the added mass force for particle clouds, and modelling options that may be implemented in existing EL and EE codes.

42 ENGINEERING↗
DOE OSTI2026

Scalable slot-die coating of phyllosilicate membranes for selective ion separations

Abstract Two-dimensional (2D) materials have recently drawn attention as candidate materials for molecular-scale membrane separations due to their tunable nanoscale interlayer properties. Phyllosilicates, a broad class of naturally abundant 2D clay minerals, offer significant advantages over synthetic 2D materials, including low cost, stability, and environmental compatibility. While these properties make phyllosilicates attractive for industrial-scale nanofiltration applications, phyllosilicate-based membranes have, to date, only been fabricated at the lab scale via vacuum filtration. Scalable fabrication methods are essential to advance the technical maturity of phyllosilicate membranes and bring these promising materials closer to large-scale adoption. Herein, we have successfully scaled up phyllosilicate (vermiculite) membrane fabrication via slot-die coating and roll-to-roll coating of an ethylenediamine–vermiculite (EDAVM) mixture onto nylon. The coated membranes are 1–2 μm $ \unicode{x03BC} \mathrm{m} $ mu m in thickness and exhibit similar structure and performance to vacuum-filtered EDAVM membranes. The membranes also show selectivity for monovalent ions over multivalent ions in binary salt mixtures. This work represents a major step toward scaling up phyllosilicate membranes for industrial ion separation applications such as resource recovery from water.

Booth, Austin [Princeton University]↗
DOE OSTI2024

Fundamental Thermodynamic, Kinetic, and Mechanical Properties of Lithium and Its Alloys

Lithium alloying reactions are beneficial in promoting uniform plating and stripping of lithium metal in all-solid-state batteries. First-principles calculations are performed to predict thermodynamic, kinetic, and mechanical properties of lithium and several important Li–M alloys (M = Mg, Ag, Zn, Al, Ga, In, Sn, Sb, and Bi). While the Li–Mg binary system forms a solid solution, most other lithium–metal alloys prefer stoichiometric intermetallic compounds with common local motifs that enable fast Li diffusion. Lithium and Li-rich alloys exhibit an unusually flat energy landscape along paths that connect BCC to close-packed structures like FCC and HCP, with important implications for mechanical properties. Very low migration barriers for Li diffusion that rival those of superion conductors are predicted, both in pure Li and in Li–M intermetallics. However, vacancy concentration, which is crucial for substitutional diffusion, is predicted to be low in metallic Li and most Li–M intermetallics. Compounds such as B32 LiAl and LiGa as well as D0 3 Li 3 Sb and Li 3 Bi exhibit structural vacancies at higher ends of their voltage windows, which together with low migration barriers leads to exceptionally high Li mobilities. In the Li–Mg solid solution, the addition of Mg is found to decrease the vacancy tracer diffusion coefficient by an order of magnitude.

36 MATERIALS SCIENCE↗