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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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481 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Decoupling thermal and irradiation effects on grain boundary segregation

Radiation-induced segregation (RIS) is most often measured by peak solute concentration at a boundary. However, this may give an incomplete picture of segregation quantity and phenomena. Radiation-induced and thermal segregation at grain boundaries was investigated in Fe-9.6 at.% Cr after 9 MeV Fe 3+ ion irradiation at 400 °C. The experimental results were compared to kinetic Monte Carlo (KMC) simulations. The study revealed that Cr enrichment (peak segregation) at the grain boundaries was comparable in both the irradiated and non-irradiated conditions, although irradiation resulted in broader segregation profiles in both experiments and simulations, indicating an overall increase in grain boundary segregation due to irradiation. This broadening is attributed to back diffusion into the grain interior. While it is an established phenomenon, this study offers a quantitative evaluation using experimental data and KMC modeling. Further, these results emphasize the importance of analyzing the entire segregation profile and decoupling the thermal and irradiation contributions to solute segregation.

Grain boundary segregation↗
DOE OSTI2023

Predicting microstructurally sensitive fatigue‐crack path in WE43 magnesium using high‐fidelity numerical modeling and three‐dimensional experimental characterization

Abstract Microstructurally small fatigue‐crack growth in polycrystalline materials is highly three‐dimensional due to sensitivity to local microstructural features (e.g., grains). One requirement for modeling microstructurally sensitive crack propagation is establishing the criteria that govern crack evolution, including crack deflection. Here, a high‐fidelity finite‐element modeling framework is used to assess the performance and validity of various crack‐growth criteria, including slip‐based metrics (e.g., fatigue‐indicator parameters), as potential criteria for predicting three‐dimensional crack paths in polycrystalline materials. The modeling framework represents cracks as geometrically explicit discontinuities and involves voxel‐based remeshing, mesh‐gradation control, and a crystal‐plasticity constitutive model. The predictions are compared to experimental measurements of WE43 magnesium samples subject to fatigue loading, for which three‐dimensional grain structures and fatigue‐crack surfaces were measured post‐mortem using near‐field high‐energy x‐ray diffraction microscopy and x‐ray computed tomography. Findings from this work are expected to improve the predictive capabilities of simulations involving microstructurally small fatigue‐crack growth in polycrystalline materials.

Engineering↗
DOE OSTI2026

Atomistic Simulation of Glasses and Amorphous Materials: Challenges and Opportunities for the Next Decade

Atomistic simulations have become indispensable tools for understanding glass structure, dynamics, and properties, yet persistent challenges limit their predictive power. This perspective examines three interconnected issues, namely glass formation procedures, interatomic potential development, and machine learning applications, which emerged from the 5th International Workshop on Challenges of Atomistic Simulations of Glasses and Amorphous Materials. We identify convergent community priorities for (i) standardized validation protocols, (ii) curated benchmark datasets with complete metadata, and (iii) open repositories for glasses. A systematic was forward is provided by a hierarchical validation framework for assessing the structural fidelity, property prediction, and behavioral realism of simulation techniques. Looking ahead, transformative advances are promised by the fusion of classical techniques with machine learning based approaches, for instance, by integrating swap Monte Carlo with machine-learning (ML) potentials, leveraging foundation models through transfer learning, and finetuning ML potentials with experimental data. Progress depends on the community committing to validated models, reproducible protocols, and sustained data sharing.

Krishnan, N. M. Anoop↗
DOE OSTI2026

Update on Radiochemical Assessment of High Burnup Commercially Irradiated Fuel

This work documents an effort to collect burnup measurements on a high burnup rod, designated 6XV, and first cycle accident tolerant fuel (ATF) rod, designated 47I, to enable benchmarking of fuel performance codes and neutronics codes. In addition to measurements, Virtual Environment for Reactor Applications (VERA) full-core-depletion analysis was also performed for the rods that were experimentally analyzed to provide an opportunity for code validation. This effort focuses on collecting data from rods irradiated at Byron Generating Station and shipped to the Oak Ridge National Laboratory (ORNL) hot-cells. This data will also anchor non-destructive examination evaluations of burnup of the various fuel rods undergoing postirradiation examination (PIE) at ORNL. Previous PIE of these fuel rods provides some guidance on the burnup trend across the fuel. Axial gamma spectroscopy scans provide a measure of relative changes in burnup across a fuel pin. Mass spectrometry based burnup measurements performed for this work at specific axial locations in the fuel are fully quantitative. By combining the mass spectrometry data with the gamma scans it is possible to more quantitatively evaluate axial variations in burnup across the entire fuel pin [1]. The combined set of burnup evaluations will be made available to other organizations that have an interest in high burnup radiochemistry data for validation of neutronic simulations and source term evaluation such as the Nuclear Regulatory Commission (NRC).

Harp, Jason [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2024

Experimental Validation of a Modular All-Electric Power Take-Off Topology for Wave Energy Converter Enabling Marine Renewable Energy Interconnection

Power electronic converters are an enabling technology for the emerging marine energy applications, such as using ocean waves to produce electricity. This paper outlines the power take-off system and its key components used in a wave energy converter offering modularity and scalability to generate power efficiently. The proposed power take-off system was implemented based on a modular multilevel converter and could be deployed to convert any alternating current electrical energy to a different alternating current for interconnection to grid or non-grid applications. Examples of widespread deployment are supplying electricity to coastal communities or producing clean drinking water. The analysis using both the simulation tests and laboratory experiments verified the design objectives and basic functionality of the developed power take-off system. An acceptable response using a field programmable gate array-based controlled laboratory testbench was achieved, complying with guidelines specified in the prevalent industry standards. Seamless operation during steady-state and transients for the studied wave energy converter was achieved as supported by the obtained results. The key findings of this work were experimentally examined under different load conditions, direct current bus voltage fluctuations, and generator speed–torque regulation. The ability of the power take-off system to generate high-power quality of the waveforms, e.g., against adhering to the IEEE 519-2022 standard for total harmonic distortion limits, is also confirmed.

Engineering↗
DOE OSTI2025

Detecting thermodynamic phase transition via explainable machine learning of photoemission spectroscopy

Identifying thermodynamic signatures of electronic phases, such as superconductivity, is challenging in low-dimensional materials due to strong fluctuations and low probing volume. Spectroscopic methods are often used to identify new bulk phases, but their main measurable quantity—electronic energy gaps—is no longer an effective order parameter in low-dimensional and fluctuating systems. Combining angle-resolved photoemission with a domain-adversarial neural network, we report a data-driven method to identify thermodynamic phase transitions solely based on single-particle spectra. We demonstrate 97.6% accuracy in cuprate superconductor Bi 2 Sr 2 CaCu 2 O 8+δ with strong superconducting fluctuations. This model notably compensates for the scarcity of experimental data by leveraging virtually inexhaustible simulated data. Further, its explainability reveals the crucial role of in-gap spectral weight in detecting phase fluctuations and thermodynamic transitions. Our work pinpoints the spectroscopic signatures of fluctuating orders and enables using spectroscopy for machine-learning-assisted material discovery for low-dimensional and strong coupling systems.

2D materials↗
DOE OSTI2026

Effects of Composition and Oxidation States on the Structures of Chromium-Containing Sodium Silicate Glasses: Molecular Dynamics Simulations using Machine Learning Interatomic Potentials

Chromium represents a significant challenge for the vitrification of high-level nuclear waste into silicate and borosilicate glasses due to its low solubility and variable oxidation states, which can limit the waste loading due to promotion of crystallization or phase separation during processing. In this study, we modeled chromium containing silicate glasses using molecular dynamics simulations with three machine learning interatomic potentials (MLIPs), MACE, CHGNet, and PFP were employed, to gain insights on glass composition and oxidation states on the structures of these glasses. One of the goals is to evaluate their ability of these MLIPs to accurately represent the general structure of silicate glasses and chromium local environments as a function of chromium oxidation states. Density Functional Theory (DFT) based calculations and experimental data such as neutron structure factors were used to validate the structural models. It was found that the foundation models of all three MLIPs are able to reproduce general structural features of the sodium silicate glass structure consistent with experimental and DFT data, but only CHGNet and PFP can accurately capture the oxidation states and local environment of chromium: tetrahedral for Cr6+ and octahedral for Cr3+. Furthermore, we studied the effect of varying Cr3+/ Cr6+ (Cr3+/Crtotal) ratio and total chromium content using PFP. Our results show that Cr6+ enhances network polymerization by reducing non-bridging oxygens through Na? charge compensation required due to the formation of chromate (CrO42-) species, while Cr³? acts as a network modifier that disrupts connectivity. System size effects on the structural characteristics and chromium environments were also tested using the PFP potential. This work highlights the importance of careful validation on the precision, transferability, and potential of MLIPs for modeling glasses containing transition metal elements that can exist in multiple oxidation states. It is also encouraging to see the foundational models are all three MLFFs are able to reproduce the basic sodium silicate glass structures, while suggesting additional training or refining is needed to improve the description of more complex systems containing transition metals.

Puga, Christina L.↗
DOE OSTI2026

Demonstration of gold nanorod systems for enhanced total efficiency: Experimental and numerical analysis

This study investigates the photothermal performance of gold nanorods engineered to exhibit longitudinal plasmon resonances at 695 nm, 780 nm, and 970 nm. The work combines synthesis, structural characterization, extinction measurements, numerical modeling, and controlled temperature experiments to quantify how nanorod geometry, resonance tuning, concentration, and chamber shape jointly influence heat generation. Transmission electron microscopy confirms that increasing nanorod aspect ratio systematically shifts the longitudinal plasmon peak toward the near-infrared region. Extinction measurements show strong agreement with theoretical predictions, validating the numerical model across two independent datasets. Three chamber geometries were tested under laser excitation at 640 nm, 808 nm, and 980 nm: an ascending stepped base, a flat base, and a descending stepped base. Without nanorods, the ascending geometry produced the highest efficiency due to enhanced natural convection. After introducing gold nanorods, all geometries exhibited substantial thermal enhancement, with total efficiencies exceeding 20%. The strongest improvement was obtained for nanorods resonant at 780 nm with a mass concentration of 4.6 mg/mL implemented on the descending stepped-base geometry. This performance resulted from the combined effect of spectral overlapping with the 808 nm laser, the highest nanorod concentration, and localized heat accumulation that intensified buoyancy-driven flow. The findings demonstrate that total efficiency is governed by a synergistic interplay between optical resonance, nanoparticle concentration, and macroscopic chamber design, revealing the system-level coupling between nanoscale plasmonic absorption and macroscale heat-transfer phenomena. The results provide a validated framework for tuning nanoscale plasmonic absorbers and optimizing thermal systems for applications requiring efficient light-to-heat conversion.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Impact of Limited Degree of Freedom Drag Coefficients on a Floating Offshore Wind Turbine Simulation

The worldwide effort to design and commission floating offshore wind turbines (FOWT) is motivating the need for reliable numerical models that adequately represent their physical behavior under realistic sea states. However, properly representing the hydrodynamic quadratic damping for FOWT remains uncertain, because of its dependency on the choice of drag coefficients (dimensionless or not). It is hypothesized that the limited degree of freedom (DoF) drag coefficient formulation that uses only translational drag coefficients causes mischaracterization of the rotational DoF drag, leading to underestimation of FOWT global loads, such as tower base fore-aft shear. To address these hydrodynamic modeling uncertainties, different quadratic drag models implemented in the open-source mid-fidelity simulation tool, OpenFAST, were investigated and compared with the experimental data from the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project. The tower base fore-aft shear and up-wave mooring line tension were compared under an irregular wave loading condition to demonstrate the effects of the different damping models. Two types of hydrodynamic quadratic drag formulations were considered: (1) member-based dimensionless drag coefficients applied only at the translational DoF (namely limited-DoF drag model) and (2) quadratic drag matrix model (in dimensional form). Based on the results, the former consistently underestimated the 95th percentile peak loads and spectral responses when compared to the OC5 experimental data. In contrast, the drag matrix models reduced errors in estimates of the tower base shear peak load by 7–10% compared to the limited-DoF drag model. The underestimation in the tower base fore-aft shear was thus inferred be related to mischaracterization of the rotational pitch drag and the heave motion/drag by the limited-DoF model.

17 WIND ENERGY↗
DOE OSTI2026

Reducing experimental uncertainty in the calculation of cavity swelling in a transmission electron microscope through crystallographically aided void volume tracking

Accurate measurement of cavity swelling in a transmission electron microscope is essential to define material performance under irradiation, and the conventionally applied spherical assumption for the calculation of cavity volumes in irradiated materials can result in errors ranging between a 25% underestimation and 72% overestimation of volume purely based on the assumption of shape. This assumption is undeniably expedient for calculation but does not sufficiently account for the 3D nature of polyhedral cavities and their shape projection in the transmission electron microscope, and therefore presents too large of an associated uncertainty in swelling determination for faceted cavities. This uncertainty has been defined for many common cavity shapes in FCC and BCC crystal systems, and has been tabulated across the cubic fundamental region. A revised methodology for crystallographically aided void volume tracking, or CAVV-T, is presented and demonstrated on a specimen of neutron irradiated Ni. In-depth discussion on the application of this technique is provided along with resources to allow for conversion between the spherical assumption and this revised method. This work seeks to increase experimental confidence in the characterization and quantification of critical aspects of irradiation damage in materials by applying a crystallographically-resolved approach for cavity swelling calculation.

Haag IV, James V. [Pacific Northwest National Labo↗
DOE OSTI2026

Solvent-Mediated Control of Nanocellulose Dispersion: An Integrated Computational and Experimental Investigation

Fibrillated cellulose derived from forestry feedstocks represents a renewable and high-strength materials platform for circular bioeconomies. However, its practical implementation is hindered by the irreversible aggregation of nanocellulose architectures, including cellulose nanofibers (CNFs). Solvent-based dispersion offers a simple and practical route to prevent CNF aggregation. Here, in this work, we integrate classical and enhanced sampling molecular dynamics (MD) simulations with experimental suspension rheology and atomic force microscopy (AFM) to elucidate how solvent environments tune CNF–CNF interactions and dispersion stability. CNF–CNF contact free energies computed from MD simulations reveal reduced aggregation in acetone/water, γ-valerolactone (GVL)/water, and tetrahydrofuran (THF)/water and pure acetone compared with pure water, reflecting stronger CNF-solvent relative to inter-CNF interactions. Correspondingly, CNF-solvent suspensions in these solvent systems exhibit stronger inter-fibril network structures and enhanced recovery compared to water, indicating improved CNF-solvent affinity. Liquid cell AFM imaging in acetone–water mixtures and in pure acetone further confirm the presence of well-dispersed CNFs. By combining multiscale computation with targeted experiments, this study establishes a rational framework for solvent design to achieve stable nanocellulose dispersions for high-strength biobased materials and efficient bioenergy conversion.

cellulose↗
DOE OSTI2026

Battery Material Synthesis and Scalability using a 50L Taylor Vortex Reactor (Final CRADA Report)

Under this agreement, Laminar will loan Argonne a 50L Taylor Vortex Reactor (TVR) and provide mechanical troubleshooting guidance and consulting to ensure the successful setup of the pilot-scale synthesis process. The U.S. Department of Energy (DOE) will allocate funding for the labor and materials required for the study. To evaluate the physical and electrochemical properties of the materials produced by the 50L TVR, Argonne will perform comprehensive characterizations, including XRD, SEM, PSA, ICP, tap density, and coin half-cell testing. Throughout the collaboration, Argonne will provide feedback and recommendations for mechanical improvements to the reactor system. Furthermore, Argonne will credit Laminar as a collaborator in any presentations or publications resulting from data generated by the system. Laminar will retain no rights to experimental results or intellectual property generated through the experiments conducted with the 50L TVR at Argonne.

25 ENERGY STORAGE↗
DOE OSTI2026

High entropy oxides prediction and discovery by the Mixed Enthalpy-Entropy Descriptor

The vast, high-dimensional composition space of high-entropy oxides (HEOs) offers exceptional opportunities for functional materials discovery, yet it also poses a fundamental challenge: the rational and efficient prediction of stable, synthesizable compositions and the corresponding structure–property relationships. Despite growing interest, the field still lacks broadly applicable, physically grounded descriptors capable of navigating various large chemical spaces. Here, we introduce a Mixed Enthalpy–Entropy Descriptor (MEED) that enables rapid, first-principles–based prediction of HEOs synthesizability across diverse chemistries. Using MEED, we perform high-throughput screening of two distinct HEO families: rocksalt oxides and perovskite oxides. The predicted top candidates in each family were experimentally validated. MEED reveals unifying thermodynamic and structural principles governing stability across both chemical compositions and polymorphs, providing mechanistic insight into the formation of high-entropy phases. This work significantly broadens the accessible chemical design space for HEOs and establishes a data-efficient framework for accelerating the discovery of next-generation functional materials.

Yu, Liping [University of Central Florida]↗
DOE OSTI2026

Experimental investigation of a closed vapour box module for a divertor-like configuration in Magnum-PSI

Efficient management of extreme heat fluxes in the divertor region to extend the lifetime of the components remains a critical challenge for the realization of nuclear fusion-based power plants. Among the alternative concepts explored for the divertor region, the use of liquid metals, particularly lithium, is of interest due its ability to dissipate the incoming plasma heat flux through the vapour shielding effect (VS). In this work, we experimentally investigated a ‘closed’ configuration of a dedicated Vapour Box Module (VBM) in the linear plasma device Magnum-PSI. The goal of the experiments is to simulate the vapour box divertor environment conditions and assess its performance in terms of power mitigation and redistribution and lithium confinement. Initial testing without Li demonstrated the efficacy of a closed VBM structure in inducing detachment via neutral gas accumulation. Apertures which enabled non-condensing gas to be effectively pumped while ensuring lithium condensed on the inner surfaces were therefore added. With a lithium capillary porous structure target used, lithium is directly vaporized by the plasma, forming a dense lithium vapour cloud that interacts with the incoming plasma. This resulted in a significant reduction of the target temperature of at least 48%, together with a temperature locking effect, a phenomenon typically observed in the VS regime. Lithium vapour confinement within the VBM was strongly correlated with the wall temperature. Relatively cold walls promoted Li re-condensation and therefore improved Li confinement, although with the expected trade-off of increased hydrogenic retention on lithium-wetted surfaces. As the wall temperature increased, the confinement efficiency decreased, consistent with reduced Li re-condensation and thermally activated Li–H chemistry and remobilization at the walls. Diagnostic measurements through embedded thermocouples and calorimetry revealed that lithium vaporization and re-condensation processes also playedsignificant roles in plasma power dissipation. The results advance the case for a closed divertor chamber with direct lithium evaporation from the strike-points as a viable method to manage divertor heat fluxes in future fusion reactors.

Romano, Fabio [Dutch Institute for Fundamental Ene↗
DOE OSTI2024

Derivation of low-energy Hamiltonians for heavy-fermion materials

Here, by utilizing a multiorbital periodic Anderson model with parameters obtained from ab initio band structure calculations, combined with degenerate perturbation theory, we derive effective Kondo-Heisenberg and spin Hamiltonians that capture the interaction among the effective magnetic moments. This derivation encompasses fluctuations via both nonmagnetic 4⁢𝑓 0 and magnetic 4⁢𝑓 2 virtual states, and its accuracy is confirmed through comparison with experimental data obtained from CeIn 3 . The significant agreement observed between experimental results and theoretical predictions underscores the potential of deriving minimal models from first-principles calculations for achieving a quantitative description of 4⁢𝑓 materials. Moreover, our microscopic derivation unveils the underlying origin of anisotropy in the exchange interaction between Kramers doublets, shedding light on the conditions under which this anisotropy may be weak compared to the isotropic contribution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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]↗