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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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673 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Gauge theory of giant phonon magnetic moment in doped Dirac semimetals

Here, we develop a quantitative theory of phonon magnetic moment in doped Dirac semimetals. Our theory is based on an emergent gauge field approach to the electron-phonon coupling, applicable to gapless systems. We find that the magnetic moment is directly proportional to the electrical Hall conductivity through the phonon Hall viscosity. Our theory is combined with the first-principles calculations, allowing us to quantitatively implement it to realistic materials. Magnetic moments are found to be of the order of a Bohr magneton for Raman-active phonon modes in graphene and Cd 3 ⁢As 2 . Our results provide practical guidance for the dynamical generation of large magnetization in quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Feasibility of Multi-Use Ocean Thermal Energy Conversion (OTEC) Platforms

Tropical islands and coastal communities in the United States and internationally suffer from high energy costs, unreliable electrical supplies, poverty, and underemployment, which are all being exacerbated by climate change. Multi-use Ocean Thermal Energy Conversion (OTEC) systems could align with the goals and values of these underserved and remote communities as scalable platforms that can provide baseload power, freshwater, and food, as well as potentially support new industries. The cold, nutrient-rich deep seawater needed for OTEC’s power cycles has many promising byproduct applications such as seawater air conditioning (SWAC) for residential and industrial cooling, enhancing aquaculture farms (e.g., cooling and nutrients for seaweed, shellfish, finfish), producing freshwater through desalination, and generating efuels such as ammonia and hydrogen.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Abstract A 3D Convolutional Variational Autoencoder (3D‐CVAE) is introduced for automated anomaly detection in electron energy‐loss spectroscopy spectrum imaging (EELS‐SI) data. This approach leverages the full 3D structure of EELS‐SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross‐entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect‐free material. In exploring methods for anomaly detection, both the 3D‐CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using FeL‐edge ΔEpeak shifts designed to simulate material defects. These results show that 3D‐CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower‐dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise‐dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS‐SI data, particularly valuable for analyzing complex material systems.

Chemistry↗
DOE OSTI2025

Li 21 Ge 8 P 3 S 34 : New Lithium Superionic Conductor with Unprecedented Structural Type

Abstract Lithium superionic conductors are pivotal for enabling all‐solid‐state batteries, which aim to replace liquid electrolytes and enhance safety. Herein, we report the discovery of an unprecedented lithium superionic conductor, Li 21 Ge 8 P 3 S 34 , featuring a novel structural type and a new composition in the Li–Ge–P–S system. This material exhibits high lithium ionic conductivity of approximately 1.0 mS cm −1 at 303 K with a low activation energy of 0.20(1) eV. It's unique crystal structure was elucidated using three‐dimensional electron diffraction (3D ED) and further refined through combined powder X‐ray and neutron diffraction analyses. The structure consists of alternating two‐dimensional slabs: one of corner‐sharing GeS 4 tetrahedra and the other of isolated PS 4 tetrahedra, enabling efficient lithium‐ion transport through a tetrahedrally interconnected network of 1D, 2D, and 3D diffusion pathways. This distinctive structural motif provides a novel design strategy for next‐generation solid electrolytes, broadening the structural landscape of lithium superionic conductors. With further advancements in compositional tuning and interfacial engineering, Li 21 Ge 8 P 3 S 34 could contribute to the development of high‐performance all‐solid‐state batteries.

Chemistry↗
DOE OSTI2025

Energy filtering–induced ultrahigh thermoelectric power factors in Ni 3 Ge

Traditional thermoelectric materials rely on low thermal conductivity to enhance their efficiency but suffer from inherently limited power factors. Innovative pathways to optimize electronic transport are thus crucial. Here, we achieve ultrahigh power factors in Ni 3 Ge-based systems through an unconventional thermoelectric materials design principle. When overlapping flat and dispersive bands are engineered to the Fermi level, charge carriers can undergo intense interband scattering, yielding an energy filtering effect similar to what has long been predicted in certain nanostructured materials. Via a multistep DFT-based screening method developed here, we find a family of L1 2 -ordered binary compounds with ultrahigh power factors up to 11 mW m −1 K −2 near room temperature, which are driven by an intrinsic phonon-mediated energy filtering mechanism. Our comprehensive experimental and theoretical study of these intriguing materials paves the way for understanding and designing high-performance scattering-tuned metallic thermoelectrics.

Science & Technology - Other Topics↗
DOE OSTI2026

Bacterial Bioleaching and Biorecovery for Biomining Unconventional Rare Earth Element Feedstocks

Bacterial metabolic interactions with rare earth elements (REEs) can be harnessed for biomining unconventional feedstocks like abandoned coal-mine drainage (AMD). Pennsylvania has ~500 AMD passive remediation systems that can precipitate REE rich solids. REEs include yttrium and the lanthanide series that are used in modern energy and technology. Bacteria that metabolically interact with REEs can be used for biomining in an affordable efficient process that does not require hazardous chemical additives. Currently, the microbial metal mechanisms that contribute to REE biorelease and biorecovery are poorly understood. Our work shows acidogenic bacterial isolates (Bacillus mycoides JR07 and Bacillus pseudomycoides KB7) successfully bioleach a mixed REE solution from AMD solids by their organic acid production and biofilm formation. Further, our work shows the potential for bacterial lanthanide-dependent enzymes to recover lanthanides from a mixed REE solution; here we have bacterial isolate Methylobacterium sp. B3 that can recover soluble lanthanum. Whole genome sequencing of Methylobacterium sp. B3 predict lanthanide-dependent methanol dehydrogenase XoxF. Understanding the microbial metabolism and genes involved in the REE release and recovery is crucial to optimize the biomining of AMD solids. Our work addresses the growing need to develop novel REE mining methods from unconventional feedstocks.

biogeochemistry↗
DOE OSTI2027

From zonal to nodal capacity expansion planning: Spatial aggregation impacts on a realistic test-case

Solving power system capacity expansion planning (CEP) problems at realistic spatial resolutions is computationally challenging. Thus, a common practice is to solve CEP over zonal models with low spatial resolution rather than over full-scale nodal power networks. Due to improvements in solving large-scale stochastic mixed integer programs, these computational limitations are becoming less relevant, and the assumption that zonal models are realistic and useful approximations of nodal CEP is worth revisiting. Here, this work is the first to conduct a systematic computational study on the assumption that spatial aggregation can reasonably be used for ISO-scale CEP. By considering a realistic, large-scale test network based on the state of California with over 8000 buses, we find that well-designed small spatial aggregations can yield good approximations but that coarser zonal models may result in large distortions of investment decisions, e.g., capacity under-investment of up to 41% for the lowest resolution model considered.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Actuating Liquid Crystals Rapidly and Reversibly by Using Chemical Catalysis

Abstract Microtubules and catalytic motor proteins underlie the microscale actuation of living materials, and they have been used in reconstituted systems to harness chemical energy to drive new states of organization of soft matter (e.g., liquid crystals (LCs)). Such materials, however, are fragile and challenging to translate to technological contexts. Rapid (sub‐second) and reversible changes in the orientations of LCs at room temperature using reactions between gaseous hydrogen and oxygen that are catalyzed by Pd/Au surfaces are reported. Surface chemical analysis and computational chemistry studies confirm that dissociative adsorption of H 2 on the Pd/Au films reduces preadsorbed O and generates 1 ML of adsorbed H, driving nitrile‐containing LCs from a perpendicular to a planar orientation. Subsequent exposure to O 2 leads to oxidation of the adsorbed H, reformation of adsorbed O on the Pd/Au surface, and a return of the LC to its initial orientation. The roles of surface composition and reaction kinetics in determining the LC dynamics are described along with a proof‐of‐concept demonstration of microactuation of beads. These results provide fresh ideas for utilizing chemical energy and catalysis to reversibly actuate functional LCs on the microscale.

Chemistry↗
DOE OSTI2026

Mode Multiplexing for Scalable Cavity-Enhanced Operations in Neutral-Atom Arrays

Neutral-atom arrays provide a versatile platform for quantum information processing. However, in large-scale arrays, efficient photon collection remains a bottleneck for key tasks such as fast, nondestructive qubit readout and remote entanglement distribution. We propose a cavity-based approach that enables fast, parallel operations over many atoms using multiple modes of a single optical cavity. By selectively shifting the relevant atomic transitions, each atom can be coupled to a distinct cavity mode, allowing independent simultaneous processing. We present practical system designs that support cavity-mode multiplexing with up to 50 modes, enabling rapid mid-circuit syndrome extraction and significantly enhancing entanglement distribution rates between remote atom arrays. This approach offers a scalable solution to core challenges in neutral-atom arrays, advancing the development of practical quantum technologies.

Aqua, Ziv [Massachusetts Institute of Technology (↗
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 OSTI2026

The Reaction of Atomic Hydrogen with an Imine: Direct Kinetic Measurements and Computational Studies

Imines are of interest in the combustion modeling of nitrogen-based fuels such as ammonia, as intermediates in atmospheric oxidation of amines, and may offer a new class of environmentally benign substitutes for perhalogenated reagents. Elementary gas-phase rate constants for the consumption of H atoms by 1,1,1,3,3,3-hexafluoro-2-propanimine were measured over 294–736 K using the laser flash photolysis/atomic resonance fluorescence technique. The results are summarized as 3.0 × 10 –11 exp(−14.5 kJ mol –1 /RT) cm 3 molecule –1 s –1 with a confidence interval of ±13%. These are the first temperature-dependent kinetic experiments on an imine of the form R 2 C═NH and thereby provide the only validation of transition-state modeling for such systems. Several pathways are feasible; comparison of theory and experiment suggests the dominant channel is addition of H atoms to the nitrogen atom. On this basis, the observations are rationalized quantitatively. Computations also yield the thermochemistry of (CF 3 ) 2 CNH, with Δ f H 298 = −1232 kJ mol –1 .

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

Singular Hall Response from a Correlated Ferromagnetic Flat Nodal‐Line Semimetal

Abstract Topological quantum phases are largely understood in weakly correlated systems, which have identified various quantum phenomena, such as the spin Hall effect, protected transport of helical fermions, and topological superconductivity. Robust ferromagnetic order in correlated topological materials particularly attracts attention, as it can provide a versatile platform for novel quantum devices. Here, a singular Hall response arising from a unique band structure of flat topological nodal lines in combination with electron correlation in a van der Waals ferromagnetic semimetal, Fe 3 GaTe 2 , with a high Curie temperature ofT c = 347 K is reported. High anomalous Hall conductivity violating the conventional scaling, resistivity upturn at low temperature, and a large Sommerfeld coefficient are observed in Fe 3 GaTe 2 , which implies heavy fermion features in this ferromagnetic topological material. The scanning tunneling microscopy, circular dichroism in angle‐resolved photoemission spectroscopy, and theoretical calculations support the original electronic features of the material. Thus, low‐dimensional Fe 3 GaTe 2 with electronic correlation, topology, and room‐temperature ferromagnetic order appears to be a promising candidate for robust quantum devices.

Chemistry↗
DOE OSTI2025

CASM Monte Carlo: Calculations of the thermodynamic and kinetic properties of complex multicomponent crystals

Monte Carlo techniques play a central role in statistical mechanics approaches that connect macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo techniques for the study of multicomponent crystalline materials within the Clusters Approach to Statistical Mechanics (CASM) software suite, and demonstrates their use in model systems to calculate free energies and kinetic coefficients, study phase transitions, and construct phase diagrams from first principles. Many crystal structures are complex, with multiple sublattices occupied by differing sets of chemical species, along with the presence of vacancies or interstitial species. This imposes constraints on concentration variables, the form of thermodynamic potentials, and the values of kinetic transport coefficients. The framework used by CASM to formulate thermodynamic potentials and kinetic transport coefficients accounting for arbitrarily complex crystal structures is presented and demonstrated with examples of increasing complexity. Additionally, an overview of the capabilities of the CASM software specific to Monte Carlo methods is given, and a new CASM software package is introduced, casm-flow, which helps automate the setup, submission, management, and analysis of Monte Carlo simulations.

Cluster expansion↗
DOE OSTI2025

Glauber’s Salt Composites for HVAC Applications: A Study on the Use of the T-History Method with a Modified Data Evaluation Methodology

Phase change materials (PCMs) can be utilized in buildings for peak load shifting in air conditioning systems, and the use of salt hydrate-based PCMs can reduce the cost of thermal energy storage devices. Glauber’s salt is an economical salt hydrate PCM with a melting point of around 32 °C. However, the desired melting range typically falls between 18 and 22 °C for building air conditioning applications. Although many researchers have characterized Glauber’s salt and its composites with modified melting points, enthalpy–temperature curves for composites of Glauber’s salt and NaCl are unavailable. In this study, we report the melting and solidification enthalpy–temperature curves for two different composites of Glauber’s salt and NaCl with a melting point of 21 °C obtained by the T-history method. Both composites contain NaCl to suppress the melting point, borax to reduce supercooling, and sodium polyacrylate as a thickener to enhance cyclic stability. The first composite with 12 wt.% NaCl demonstrated 139 kJ·kg−1 of latent heat of fusion, and the second composite with 9 wt.% NaCl demonstrated 171 kJ·kg−1. Both the composites have high volumetric energy densities compared to their organic counterparts with similar melting points.

Chemistry↗
DOE OSTI2025

Multireference diffusion Monte Carlo reaches 2D materials

Abstract Quantum confinement in 2D materials strongly enhances electronic correlation effects. Therefore, predicting the properties of these unique materials, with both a high level of accuracy and computational efficiency, without relying on adjustable parameters or functionals, remains an outstanding theoretical challenge. The majority of theoretical studies are based on the approximations of density functional theory (DFT). The reliability of DFT predictions are heavily dependent on the choice of an approximated exchange-correlation functional. Here, we estimate the magnitude of impact of correlation on the total energy for the quintessential 2D material, graphene, by performing and comparing state-of-the-art selected CI and quantum Monte Carlo extrapolated calculations for a single unit cell at the$$\Gamma$$point. We demonstrate that Self-Healing Diffusion Monte Carlo (SHDMC) obtains a very compact, but high-quality wavefunction for this system that lacks the strong basis set dependence displayed by state of the art quantum chemistry methods. The SHDMC wavefunction is of higher quality compared to that obtained from sCI, in the same orbital basis, while being$$\sim$$ 1000 times smaller in terms of determinant count compared to sCI. We also demonstrate that extrapolating SHDMC results to the infinite determinant limit compares extremely well with complete basis set extrapolated sCI. Our work paves the way for future validation of SHDMC applied to challenging 2D materials.

Science & Technology - Other Topics↗
DOE OSTI2026

Interactions Between Climate Policy and Technology-influenced Travel Behavior: Mitigating Induced Demand from CACC

Advances in vehicle technology have influenced the development of automated vehicle systems, where vehicles that do not require human intervention are already deployed in the roadway networks. While these advances are proved to increase roadway safety and highway capacity, more research is needed to understand the long-term and regional-level impacts on mobility, land use, energy consumption, and emissions. This study proposes a multi-model approach to analyze the effect of vehicle automation and deep decarbonization policies over a period from 2020 to 2040 in Austin, Texas. We use the Global Change Analysis Model (GCAM) to develop internally the scenarios that are then passed to the SMART Mobility modeling workflow, a large-scale simulation framework combining the POLARIS activity-based travel demand model and mesoscopic traffic simulator with the Autonomie vehicle energy consumption model and the UrbanSim land use simulator. Results suggest that the introduction of vehicles with advanced automation could increase fuel consumption when no decarbonization policies are implemented. Also, advances in vehicle technology research and development could lead to a decline in energy use in the long-term. Energy pricing and vehicle electrification incentives could help reduce the impact of vehicle automation. Finally, our analysis indicates the relevance of introducing land use processes in longterm vehicle automation studies.

land use↗
DOE OSTI2026

Final Technical Report: Transport of Complex Mixtures in Ion-Containing Polymer Membranes

Permselective ion-containing membranes are an integral component for many applications from water treatment, fuel cells, and solar fuels devices where the selective transport of molecules and ions is desired. In solar fuels devices, ion-containing polymer membranes are responsible for permitting selective transport of ions between electrodes to maintain overall charge neutrality yet limit transport of reaction products produced at the electrodes. While the transport of single solutes through such membranes has been fairly well described, binary and multicomponent transport is poorly understood due to the myriad of interactions that occur in these systems (i.e. between co-permeants and between permeants and the membrane). Solar fuels devices are just one example of an application where understanding the transport of multiple simultaneous species is critically important to improving device performance as product crossover leads to reductions in overall device performance. The objectives of this research was to improve our understanding of the complex array of factors that influence transport behavior of multiple solutes within ion-containing polymer membranes. This experimental project addressed the lack of fundamental understanding of multicomponent transport behavior by synthesizing ion exchange membranes with varied incorporation of comonomers (ionic and neutral moieties) to investigate fundamental relationships between membrane structure, membrane physiochemical properties, and transport behavior of solutes and complex solute mixtures through dense, hydrated membranes.

25 ENERGY STORAGE↗
DOE OSTI2026

Reduced Order Models for Liquid Hydrogen Pooling and Vaporization Supported by Experiments

In the event of a leak of liquid hydrogen, a pool can form that vaporizes, disperses, and eventually dilutes to a non-flammable mixture. In this work, we describe fast-running models for the pooling and vaporization of liquid hydrogen in a steady cross-wind. Several pooling models from the literature are compared to solve for the flow and extent of the pool. The size of the pool can serve as the source for a separate dispersion model, which builds upon the existing one-dimensional Gaussian plume model in HyRAM+. Additional terms for the effects of a cross-wind on momentum and entrainment were added so that the model could handle the effects of a cross-wind on a low-speed flow. The models are compared to experimental data on pooling extent and downwind dispersion for steady flow rates of liquid hydrogen in a steady cross-wind. In the two compared experiments, liquid flow rates of 15 and 45 g/s were spilled onto concrete in cross-winds of approximately 1.8 m/s. The rate of growth of the pool and the downwind concentration boundaries are compared to the models, showing good agreement, although additional tuning is needed. These models can contribute to the advancement of codes and standards for liquid hydrogen systems.

dispersion↗