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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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600 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Virtual Growth of SRF Materials

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Fermilab]↗
DOE OSTI2026

Machine learning approach for vibronically renormalized electronic band structures

Here, we present a machine learning (ML) method for efficient computation of vibrational thermal expectation values of physical properties from first principles. Our approach is based on the nonperturbative frozen phonon formulation in which stochastic Monte Carlo algorithm is employed to sample configurations of nuclei in a supercell at finite temperatures based on a first-principles phonon model. A deep-learning neural network is trained to accurately predict physical properties associated with sampled phonon configurations, thus bypassing the time-consuming ab initio calculations. To incorporate the point-group symmetry of the electronic system into the ML model, group-theoretical methods are used to develop a symmetry-invariant descriptor for phonon configurations in the supercell. We apply our ML approach to compute the temperature dependent electronic energy gap of silicon based on density functional theory (DFT). We show that, with less than a hundred DFT calculations for training the neural network model, an order of magnitude larger number of sampling can be achieved for the computation of the vibrational thermal expectation values. Our work highlights the promising potential of ML techniques for finite temperature first-principles electronic structure methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Copacabana: a probabilistic membership assignment method for galaxy clusters

Cosmological analyses using galaxy clusters in optical/near-infrared photometric surveys require robust characterization of their galaxy content. Precisely determining which galaxies belong to a cluster is crucial. In this paper, we present the COlor Probabilistic Assignment of Clusters And BAyesiaN Analysis (Copacabana) algorithm. Copacabana computes membership probabilities for all galaxies within an aperture centred on the cluster using photometric redshifts, colours, and projected radial probability density functions. We use simulations to validate Copacabana and we show that it achieves up to 89 per cent membership accuracy with a mild dependence on photometric redshift uncertainties and choice of aperture size. We find that the precision of the photometric redshifts has the largest impact on the determination of the membership probabilities followed by the choice of the cluster aperture size. We also quantify how much these uncertainties in the membership probabilities affect the stellar mass–cluster mass scaling relation, a relation that directly impacts cosmology. Using the sum of the stellar masses weighted by membership probabilities (⁠μ * ⁠) as the observable, we find that Copacabana can reach an accuracy of 0.06 dex in the measurement of the scaling relation at low redshift for a Legacy Survey of Space and Time type survey. These results indicate the potential of Copacabana and μ * to be used in cosmological analyses of optically selected clusters in the future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

3D Printing ofThermally Responsive Shape Memory LiquidCrystalline Epoxy Networks

Abstract A two-component liquid crystalline epoxy network (LCEN) with shape memory behavior was developed and evaluated as a candidate material for 3D printing. The cure kinetics of the uncured material and the shape memory properties of the cured LCEN were investigated by using parallel plate rheology and dynamic mechanical analysis, respectively. A commercially available fumed silica additive was introduced to the neat, uncured material to improve the rheological properties for 3D printing. The addition of fumed silica was found to increase the yield stress, shear-thinning behavior, and toughness of the uncured epoxy ink. Polarized light microscopy, differential scanning calorimetry, and wide-angle X-ray scattering measurements between the neat and additive-modified LCEN suggested a reduction in liquid crystalline alignment in the modified LCEN, owing to interactions between crystalline domains and fumed silica, which in turn influenced the mechanical behavior. Overall, the additive was found to be successful in preserving the shape memory properties of LCEN while improving its printability.

Chemistry↗
DOE OSTI2025

High‐Performance Rechargeable Lithium‐Chlorine Batteries with ALD Conformal Starburst Porous Graphene Positive Electrodes

Abstract Rechargeable alkali metal‐chlorine batteries are emerging as a promising high‐energy‐density solution. However, they confront significant challenges, including the primary issue stemming from the weak binding affinity of cathode materials for Cl 2 , which leads to a sluggish and inadequate supply of Cl 2 during the redox reactions, resulting in a shortened cycle life and low Coulombic efficiency (CE), particularly when operating at ultrahigh specific capacity outputs. Herein, an Al 2 O 3 ‐skinned heterostructured starburst porous graphene with conformal metasurfaces (Al 2 O 3 @rGO) is reported, crafted from a hierarchical porous starburst graphene arranged in a unique layered structure by the PTFE microemulsion skin effect, leveraging subsequent fluidized bed atomic layer deposition (FBALD) of Al 2 O 3 groups. Al 2 O 3 @rGO features superhydrophilicity, effective adsorption, fast kinetics from stable dynamic respiratory interface, high electrical and thermal conductivity anisotropy, intelligent thermal management and safe operation over a wide temperature range. Consequently, the Li‐Cl 2 @Al 2 O 3 @rGO battery achieves an ultrahigh discharge specific capacity of 5000 mAh g −1 at ≈100% CE, and even delivers stable cycling over 200 cycles with 2000 mAh g −1 at an average CE of 99.8% under low temperature environment of ‐40 °C. The scalable heterostructure approach offers a sustainable perspective of the development of functionalized metamaterials and metasurfaces for next‐generation safe and energy‐dense batteries and broader applications.

Chemistry↗
DOE OSTI2026

Multi-modal dynamic radiography using short-pulse laser-generated probe beams

Radiography is an important tool for the interrogation of dynamic experiments in the fields of dynamic properties of materials, and in condensed matter, high explosive, and high-energy-density physics. Multi-modal radiography advances the hypothesis that combining the information delivered by multiple radiographic modalities can lead to more constrained (improved) “reconstruction” of the scene than can be obtained from a single probe. We identify four modalities: multi-probe, time sequence, multi-view, and multi-messenger. Multi-probe radiography is a promising candidate for a next-generation dynamic radiographic facility. High-energy X-rays are the most frequently used probe for dynamic radiography, although recent developments show the utility of proton (pRad), electron (eRad), and neutron probe beams. Because each probing species interacts with material in the radiographic scene through quantitatively different mechanisms, each returns independent information about the scene, which can add extra constraints to the reconstruction process. How to conduct detailed, quantitative “co-analysis” of multiple data streams remains an area of active research. Multi-beam, short-pulse, laser-generated probes offer sufficient dose, an appropriate spectrum, and appropriate spatio-temporal resolution to produce high-quality dynamic radiographs. This paper reports on technology development to advance the state of the art of multi-modal/multi-probe radiography and the pursuit of both deterministic and inferential (AI/ML assisted) co-analysis methodologies to produce more constrained reconstructions from multi-modal data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Investigating two-dimensional adjoint QCD on the lattice

We present our investigations of SU(N) adjoint QCD in two dimensions with one Majorana fermion on the lattice. We determine the relevant parameter range for the simulations with Wilson fermions and present results for Polyakov loop, chiral condensate, and string tension. In the theory with massive fermions, all observables we checked show qualitative agreement between numerical lattice data and theory, while the massless limit is more subtle since chiral and non-invertible symmetry of the continuum theory are explicitly broken by lattice regularization. In thermal compactification, we observe N perturbative vacua for the holonomy potential at high-T with instanton events connecting them, and a unique vacuum at low-T. At finite-N, this is a cross-over and it turns to a phase transition at large-N thermodynamic limit. In circle compactification with periodic boundary conditions, we observe a unique center-symmetric minimum at any radius. In continuum, the instantons in the thermal case carry zero modes (for even N) and indeed, in the lattice simulations, we observe that chiral condensate is dominated by instanton centers, where zero modes are localized. We present lattice results on the issue of confinement vs. screening in the theory and comment on the roles of chiral symmetry and non-invertible symmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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 OSTI2026

CO2 Handling & Electrolyzer Efficiency Scaling Evaluator

CHEESE is an interactive dashboard tool for estimating the performance and material requirements of carbon dioxide electrolysis systems. It helps users evaluate how electrode area, current density, product selectivity, gas flow, cell voltage, and the number of cells in a stack affect system operation. The dashboard provides simple and advanced modes so it can be used for both quick estimates and more detailed engineering analysis. Users can estimate product output, carbon dioxide use, electrical power, electrode area, gas and liquid flow rates, energy efficiency, material cost per test, and the effect of scaling from a single cell to a multi cell stack. It also includes tools for examining carbon balance, equipment durability, component replacement, and changes in performance over time. This is intended to help both academia and industry researchers who are either getting into CO2 electrolysis on lab-scale or are trying to establish a larger footprint. CHEESE presents results through tables, charts, and simplified cell and stack diagrams. It is intended to support research planning, experimental design, comparison of operating conditions, and early stage scale up studies.

Prajapati, Aditya [Lawrence Livermore National Lab↗
DOE OSTI2026

Design of monolithic piezoelectric bimorph mirrors made from lithium niobate

Recent advances in deformable mirrors based on monolithic piezoelectric substrates, such as lithium niobate, have the potential to improve the image quality of X-ray optical systems on synchrotron and free-electron laser beamlines and microscopes. However, the quantitative relationship between design parameters and the deformed shape has not been readily available in the literature. We present an analytical model, validated through finite element analysis, enabling calculation of tangential and sagittal curvatures based on mirror dimensions, crystallographic orientation, and applied voltage. We demonstrate that through the selection of material orientation, it is possible to achieve different deformed shapes (sphere, cylinder, or hyperbolic paraboloid). This methodology can be generalized to other piezoelectric materials and substrate-integrated actuator systems.

Marzari, Francesco [University of Trento (Italy); ↗
DOE OSTI2025

A Phenazine‐Based Two‐Dimensional Covalent Organic Framework for Photochemical CO 2 Reduction with Increased Selectivity for Two‐Carbon Products

Abstract The reduction of carbon dioxide (CO₂) into valuable products will contribute to sustainable carbon use. Here we report the photocatalytic reduction of CO₂ to carbon monoxide, formate, and oxalate ions using a redox‐active phenazine‐based 2D covalent organic framework (Phen‐COF) and its phenazine monomer. Under similar irradiation conditions,Phen‐COFproduced 2.9 times more CO, 11 times more formate, and 13 times more oxalate compared to equimolar amounts of the monomeric phenazine, demonstrating that the COF architecture enhances catalytic performance (TOF COF : 10 −7 s −1 CO, 10 −8 s −1 formate, and 10 −11 s −1 oxalate). Structural analysis, including X‐ray diffraction and N₂ porosimetry, confirmed the COF's long‐range order and porosity. Mechanistic studies suggest a sequential formate‐to‐oxalate pathway, with CO and formate acting as intermediates. These results demonstrate the potential of the COF architecture to improve the performance of metal‐free, redox‐active aromatic systems such as phenazines to facilitate efficient and selective CO₂ conversion under mild conditions.

Chemistry↗
DOE OSTI2025

Carbon in GaN as a nonradiative recombination center

Trap-assisted nonradiative recombination has been shown to limit the efficiency of optoelectronic devices. While substitutional carbon (⁠C N ) has been suggested to be a nonradiative recombination center in GaN devices, a complete recombination cycle including the two charge-state transition levels has not been previously described. In this work, we investigate the trap-assisted recombination process due to C N in GaN, including multiphonon emission, radiative recombination, trap-assisted Auger–Meitner (TAAM) recombination as well as thermal emission of holes. Our study shows the key role of TAAM processes at the high carrier densities relevant for devices. We also reveal the carrier-density regimes where thermal emission and radiative recombination are expected to play an observable role. Our results highlight that carbon concentrations exceeding ~10 17 cm −3 can have a noticeable impact on device efficiency, not just in GaN active layers but also in InGaN and AlGaN. Furthermore, our comprehensive formalism not only offers detailed results for carbon but also provides a general framework for assessing the multiple processes that participate in trap-assisted recombination in semiconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Mechanism of H 2 plasma-enabled reduction of hematite thin films

Hydrogen plasma is gaining significant interest as a promising pathway for direct iron ore reduction and for lowering process temperatures but the reduction mechanism remains poorly understood. In this work we analyzed the plasma and thermal reduction of thin-film hematite (Fe 2 O 3 ) at temperatures below 340 °C using X-ray diffraction and scanning electron microscopy with energy-dispersive X-ray spectroscopy. Plasma reduced the incubation period by an order of magnitude and increased the reduction rate by a factor of 2.6 compared to thermal reduction. Plasma-produced H-atoms facilitate the formation of numerous iron nucleation sites, bypassing the energetically unfavorable dissociative adsorption of H 2 on iron oxide. These iron nuclei can autocatalyze the reduction of the surrounding hematite via a hydrogen spillover mechanism. Our results demonstrate that plasma-derived H-atoms primarily impact the initial nucleation-limited stage. These new insights provide a mechanistic framework that can aid the implementation and optimization of hydrogen plasma-assisted iron oxide reduction at reduced temperatures.

08 HYDROGEN↗
DOE OSTI2024

Three-dimensional dispersion in the type-II Dirac semimetals PtTe 2 and PdTe 2 revealed through circular dichroism in angle-resolved photoemission spectroscopy

PtTe 2 and PdTe 2 are among the first transition metal dichalcogenides that were predicted to host type-II Dirac fermions, exotic particles prohibited in free space. These materials are layered and air stable, which makes them top candidates for technological applications that take advantage of their anisotropic magnetotransport properties. Here, in this work, we provide a detailed characterization of the electronic structure of PtTe 2 and PdTe 2 using angle-resolved photoemission spectroscopy (ARPES) and density functional theory calculations, offering an alternative interpretation for one of the Dirac-like dispersions in these materials. Through the use of circularly polarized light, we report a different behavior of such dispersion in PdTe 2 compared to PtTe 2 , that we relate to a symmetry analysis of the dipole matrix element. Such analysis reveals a link between the observed circular dichroism and the different momentum-dependent terms in the dispersion of these two compounds, despite their close similarity in crystal structure. Additionally, our data show a clear difference in the circular dichroic signal for the type-II Dirac cones characteristic of these materials, compared to their topologically protected surface states. Our paper provides a useful reference for the ARPES characterization of other transition metal dichalcogenides with topological properties and illustrates the use of circular dichroism as a guide to identify the topological character and attributes of two otherwise equivalent band dispersions.

angle-resolved photoemission spectroscopy↗
DOE OSTI2026

Two-dimensional non-equilibrium melting of charged colloids

Thermodynamic two-dimensional melting has been extensively studied in experiments and simulations, and is well predicted by theory. For systems in equilibrium, this transition is well described by the Kosterlitz–Thouless–Halperin–Nelson–Young theory, where melting is directly linked to the unbinding of topological defects. For driven, non-equilibrium melting and other non-equilibrium phase transitions, the picture is less clear. Here, in this work, we study the two-dimensional melting of a crystal of charged colloids. By randomly replacing some charged colloids with magnetic colloids, we can melt our system by rotating a fraction of the particles to create non-equilibrium, hydrodynamic random flows and local stresses. We can also melt it thermally by changing the particle number density. We find that an effective temperature approach cannot explain the results of our driven system. Rather, in both experiments and simulations, we observe that plotting the hexatic order parameter and the hexatic correlation’s exponent versus the density of disclinations and dislocations, respectively, yields universal curves. This implies that in our systems, two-dimensional melting depends directly on the density of topological defects and is independent of whether thermal or non-equilibrium forces generate them.

critical phenomena↗
DOE OSTI2026

Power Lane County Electric Grid Handbook

In 2024, Lane Couty was selected to participate in the U.S. Department of Energy’s Energy to Community program. Through the program, National Laboratory researchers from Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory, and the National Laboratory of the Rockies provide three years of technical assistance to Lane County and their project partners: the Center for Rural Livelihoods, Springfield Utility Board, and Emerald People’s Utility District. The project, named Power Lane County, aims to improve local electric system affordability, reliability and resilience in the face of natural hazards and potentially rising loads. The Power Lane County Electric Grid Handbook establishes a foundational understanding of the energy landscape and electric grid in Lane County to inform community engagement, education, and analysis in future project phases. This document synthesizes public data and utility and stakeholder engagement, including utility interviews to give the reader a comprehensive view of the challenges facing Lane County's electric system and the opportunities to address them

Electricity↗
DOE OSTI2026

A Novel Low-Profile High-Efficiency Three-Phase Matrix Transformer

High step-down isolated DC-DC conversion from an 800 V DC bus to low-voltage, high-current outputs is required in automotive auxiliary converters and data center power supplies. In such applications, conventional transformer-based converters require large turns ratios, which increase winding resistance, leakage inductance, and magnetic height. This paper proposes a novel low-profile three-phase matrix transformer that realizes a large effective voltage ratio through flux division among multiple secondary legs, without increasing the physical turns count of each winding. As a result, the proposed structure reduces copper usage and transformer height while preserving the voltage conversion capability of a conventional three-phase transformer. Finite element analysis shows that the proposed design reduces magnetic height by 27%, ferrite volume by 34%, and copper volume by 28%. Circuit-level simulations of an 800 V/12 V,3 kW CLLLC dual-active-bridge converter further show that the lower winding resistance reduces total system loss by 91% and increases DC-DC efficiency from 82.6% to 97.6% at 3 kW output.

Inoue, Shuntaro [ORNL] (ORCID:0000000262637627)↗
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↗