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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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1,697 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

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

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

Axion-like particles↗
DOE OSTI2026

The effect of dogbone sample size in the tensile testing of TATB-based plastic‑bonded explosive materials

Mechanical properties are of interest for many plastic‑bonded explosive (PBX) materials with tensile properties being of particular interest. Direct tensile measurements using dogbone-shaped samples are considered the gold standard, but they are fairly large, making testing more costly and less desirable from a safety perspective. We investigated whether the measured tensile strength depends on the dogbone specimen size, which to our knowledge, has not been reported in the literature for PBX materials. Understanding this should inform the feasibility of employing smaller samples and how sample size should be considered when comparing PBX dogbone values in the literature. The TATB-based PBX dogbone sample size was varied by (a) scaling all dimensions proportionally and (b) varying only the length of the samples. It was observed that the measured tensile peak stress (strength) was a function of the sample size, and was more dependent on the diameter (cross-sectional area) than the length of the samples. Since peak stress is calculated as peak force normalized to the diameter of the sample, one might not expect an explicit diameter dependence for the peak stress. Therefore, these results suggest there may be an additional strengthening effect as the sample diameter is increased.

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

High Pressure X-ray Diffraction and Equation of State of Hydrazine

Synchrotron X-ray diffraction has been used to investigate the structure and equation of state (EOS) of hydrazine (N 2 H 4 ) up to 54.3 GPa at 298 K. The diffraction patterns could be fit to a monoclinic unit-cell structure and put strong constraints on previously reported phase transitions documented by vibrational spectroscopy over this pressure range. Pressure–volume ( P–V ) data were fit using a Vinet EOS, yielding parameters: V 0 = 45.2 Å 3 /molecule (fixed), K 0 = 11.8(7) GPa, and K 0 ′ = 6.5(2). Previously measured high-pressure vibrational frequency shifts were used to estimate the vibrational free energy and model P–V–T isotherms from 0 to 1200 K. The results of the P–V–T isotherms are compared to existing shock Hugoniot data on hydrazine and 298 K isotherms for assemblages of possible decomposition products. This comparison suggests dissociation at high density under shock loading. Good correspondence was found between the static lattice EOS as calculated by the model and the previously reported EOS as calculated by density functional theory. Finally, these results resolve existing uncertainties about the EOS and crystal symmetry of hydrazine at high pressure and provide valuable baseline information on this important energetic material.

diffraction↗
DOE OSTI2026

High-Q superconducting lumped-element resonators for low-mass axion searches

Low-frequency superconducting lumped-element resonators have recently attracted significant attention in the context of axion dark matter searches. Here, we present the design and implementation of a fixed-frequency superconducting resonator operating near 250 kHz, possessing an inductor volume of ∼1 liter and achieving an unloaded quality factor Q ≈ 2.1 × 10 6 . This resonator represents a significant improvement over the state of the art and informs the design of searches for low-mass axions.

Bosons↗
DOE OSTI2025

Polaron catastrophe within quantum acoustics

The quantum acoustic framework has recently emerged as a nonperturbative, coherent approach to electron–lattice interactions, uncovering rich physics often obscured by perturbative methods with incoherent scattering events. Here, we model the strongly coupled dynamics of electrons and acoustic lattice vibrations within this framework, representing lattice vibrations as coherent states and electrons as quantum wave packets, in a manner distinctively different from tight-binding or discrete hopping-based approaches. We derive and numerically implement electron backaction on the lattice, providing both visual and quantitative insights into electron wave packet evolution and the formation of acoustic polarons. We investigate polaron binding energies across varying material parameters and compute key observables—including mean square displacement, kinetic energy, potential energy, and vibrational energy—over time. Our findings reveal the conditions that favor polaron formation, which is enhanced by low temperatures, high deformation potential constants, slow sound velocities, and high effective masses. Additionally, we explore the impact of external electric and magnetic fields, showing that while polaron formation remains robust under moderate fields, it is weakly suppressed at higher field strengths. These results deepen our understanding of polaron dynamics and pave the way for future studies into nontrivial transport behavior in quantum materials.

Science & Technology - Other Topics↗
DOE OSTI2025

Lepto-axiogenesis with light right-handed neutrinos

We study lepto-axiogenesis in theories where the right-handed neutrino is light enough that its dynamics affect the determination of the baryon asymmetry. When compared with theories of high-scale lepto-axiogenesis where the Majorana neutrino mass may be treated as an effective dimension-five operator, we find that the predicted saxion mass is lower. Two distinct scenarios emerge. In the first, processes that generate the baryon asymmetry are in equilibrium down to the mass of the right-handed neutrino. In the second, the relevant processes never reach equilibrium; the baryon number freezes in. We comment on implications for supersymmetric spectra and discuss constraints on late decays of supersymmetric relics and from dark radiation. In contrast to high-scale lepto-axiogenesis, which predicts superpartners with masses of 10–100 TeV or more, we find this scenario is consistent with a wider range of superpartner masses, all the way down to current direct search bounds.

Axions and ALPs↗
DOE OSTI2025

Mild-Annealed Molecular Layer Deposition (MLD) Tincone Thin Film as Photoelectrochemically Stable and Efficient Electron Transport Layer for Si Photocathodes

Metalcone thin films, composed of inorganic–organic hybrids, are synthesized using molecular layer deposition (MLD) through reactions between organometallic precursors (e.g., Sn, Al, and Ti) and organic reactants (e.g., ethylene glycol and glycerol). Despite their unique properties, metalcones exhibit significant vulnerability to water due to their organic components, limiting their potential in electrochemical applications. This study focuses on enhancing the photoelectrochemical stability of tincone thin films in aqueous electrolyte while preserving their hybrid characteristics through mild annealing in air at 250 °C. As-deposited and vacuum-annealed tincone thin films exhibited significant degradation under these conditions, while high-temperature-annealed (500 °C) tincone thin films offered improved stability with a significant decline in charge transfer efficiency. In contrast, mild annealing in air maintained the C–O bond at half level and improved the stability and charge transport without compromising the unique characteristics of tincone. This was confirmed by ellipsometry, X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared spectroscopy (FTIR). Mild-annealed tincone deposited on a lightly doped p-type silicon (p-Si) photocathode produced a 20-fold increase in CO volume compared to high-temperature annealed tincone in a CO 2 -saturated potassium bicarbonate (KHCO 3 ) electrolyte with dispersed graphene oxide–cobalt phthalocyanine (GO-CoPc) under 1 sun illumination at 0.9 V vs reversible hydrogen electrode (RHE), while maintaining the faradaic efficiency for CO and H 2 . These results suggest that mild-annealed tincone thin films hold significant potential as protective charge transport layers on silicon photocathodes for the aqueous CO 2 reduction reaction (CO 2 RR).

Annealing (metallurgy)↗
DOE OSTI2026

Universal Relationship between Limiting Current and Electrochemical Transport Properties in Malonate-Based Polymer Electrolytes

There is considerable interest in developing high-performance electrolytes for rechargeable lithium batteries. For practical applications, the electrolyte must support large dc currents. However, the parameters most often reported in the literature, conductivity, κ, and current fraction, ρ + , reflect ion transport in the limit of infinitesimal currents. In this limit, the efficacy of an electrolyte is given by the product κρ + . The limiting current density, i lim , is the maximum current density that can be applied across an electrolyte; the cell voltage diverges if the applied current density exceeds ilim. This parameter reflects ion transport in the limit of large dc currents and is therefore of practical interest. It would therefore be convenient if i lim could be predicted from measurements of κρ + . In order to explore this possibility, we studied six malonate-based polymers and PEO at a fixed salt concentration (r = 0.08) and temperature (90°C) using symmetric cells with planar electrodes. Unfortunately, there is no correlation between ilim and κρ + . When the applied current density, i, is less than ilim, the cell voltage approaches a stable plateau, ϕ plateau . Here, we found a linear dependence between i and thickness-normalized plateau potential, ϕ plateau L –1 , irrespective of the magnitude of the applied current. In all seven polymer electrolytes, we found a linear correlation between ilim and the slopes of these lines, σ. In other words, measurements of σ can be used to predict the limiting current.

Jana, Rounak [Lawrence Berkeley National Laborator↗
DOE OSTI2024

Fluorophilic Sigma(σ)‐Lock Self‐Healable Copolymers

Although F-Containing molecules and macromolecules are often used in molecular biology to increase the binding with Lewis acidic groups by introducing favorable C−F dipoles, there is virtually no experimental evidence and limited understanding of the nature of these interactions, especially their role in synthetic polymeric materials. These studies elucidate the molecular origin of inter- and intra-Chain interactions responsible for self-healing of F-Containing copolymers composed of pentafluorostyrene and n-butyl acrylate units (p(PFS/nBA). Guided by dynamic surface oscillating force (SOF) and spectroscopic measurements supported by molecular dynamics (MD) simulations, these studies show that the reformation of σ-σ orbitals in −C−F of PFS and CH 3 CH 2 − of nBA units enables the recovery of entropic energy via fluorophilic-σ-lock van der Waals forces when PFS/nBA molar ratios are ~50/50. The strength of these interactions determined experimentally for self-healable PFS/nBA compositions is in the order ~0.3 kcal/mol which primarily comes from fluorophilic-σ-lock (~70 %) contributions. These interactions are significantly diminished for non-self-healable counterparts. Strongly polarized −C−F σ orbitals create lateral dipolar forces enhancing the affinity towards −C−H orbitals, facilitating energetically favorable interactions. Entropic recovery driven by non-Covalent bonding offers a valuable tool in designing materials with unique functionalities, particularly self-healable batteries and energy storage devices.

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

Salt‐Assisted Vapor–Liquid–Solid Growth of 1D van der Waals Materials

The method of salt-assisted vapor–liquid–solid (VLS) growth is introduced to synthesize 1D nanostructures of trichalcogenide van der Waals (vdW) materials, exemplified by niobium trisulfide (NbS 3 ). The method uses a unique catalyst consisting of an alloy of Au and an alkali metal halide (NaCl) to enable rapid and directional growth. High yields of two types of NbS 3 1D nanostructures, nanowires and nanoribbons, each with sub-ten nanometer diameter, tens of micrometers length, and distinct 1D morphology and growth orientation are demonstrated. Strategies to control the location, size, and morphology of growth, and extend the growth method to synthesize other transition metal trichalcogenides, NbSe 3 and TiS 3 , as nanowires are demonstrated. Finally, the role of the Au–NaCl alloy catalyst in guiding VLS synthesis is described and the growth mechanism based on the relationships measured between structure (growth orientation, morphology, and dimensions) and growth conditions (catalyst volume and growth time) is discussed. These results introduce opportunities to expand the library of emerging 1D vdW materials to make use of their unique properties through controlled growth at nanoscale dimensions.

1D van der Waals material↗
DOE OSTI2026

Distributed Tomographic Reconstruction with Quantization

Conventional tomographic reconstruction typically depends on centralized servers for both data storage and computation, leading to concerns about memory limitations and data privacy. Distributed reconstruction algorithms mitigate these issues by partitioning data across multiple nodes, reducing server load and enhancing privacy. However, these algorithms often encounter challenges related to memory constraints and communication overhead between nodes. In this paper, we introduce a decentralized Alternating Directions Method of Multipliers (ADMM) with configurable quantization. By distributing local objectives across nodes, our approach is highly scalable and can efficiently reconstruct images while adapting to available resources. To overcome communication bottlenecks, we propose two quantization techniques based on K-means clustering and JPEG compression. Numerical experiments with benchmark images illustrate the tradeoffs between communication efficiency, memory use, and reconstruction accuracy.

Miao, Runxuan↗
DOE OSTI2026

Comparing the fluorination of Pb+ and Po+: insights into p-block relativistic effects for superheavy elements

It is expected that the chemical properties of the heaviest of the superheavy elements (SHEs, = 113 – 118) do not align with what is suggested by their current positions on the periodic table. Specifically, the onset of significant relativistic effects, including increased spin–orbit splitting of the p-orbitals may lead to enhanced stability of low-oxidation states. Notably, it is predicted that flerovium ( = 114) may exhibit pseudo-noble gas behavior from a electron configuration that acts as an ‘inert pair’. Even though it is expected that the – splitting becomes pronounced toward the end of the p-block’s sixth row, there is currently limited experimental evidence to confirm its extent or impact. Here, the production of gas-phase lead ( = 82) and polonium ( = 84) fluoride cations (PbF and PoF ) were compared to elucidate differences in accessible oxidation states. The PoF and PbF species were produced and identified with the FIONA spectrometer at the Lawrence Berkeley National Laboratory 88-Inch Cylctron Facility. Polonium showed notably different fluorination chemistry than lead, producing PoF and PoF as primary products compared to lead’s PbF and PbF . The distribution of PoF products observed offer insights as to the role of spin–orbit splitting for polonium. Similar studies of superheavy elements would elucidate the accessibility of their low-oxidation states as well as to inform chemical predictions for eighth-row elements not yet discovered.

Pore, Jennifer L [Nuclear Science Division, Lawren↗
DOE OSTI2026

Precise Modeling of a Complex Solenoidal Magnetic Field Using a Combination of Analytic Functions and a PINN

We demonstrate an iterative approach to modeling a sparsely measured magnetic field in a large-bore solenoid. This approach uses a hybrid of traditional and machine learning techniques. The traditional technique is a linear least-squares fit using a series solution to Laplace's equation, while the machine learning technique involves the training of a physics-informed neural network (PINN) on the least-squares fit residuals. We use a newly defined activation function "DELTAsnake," a modification to the snake activation function proposed by Ziyin et al. that allows for stronger curvature and non-monotonicity. The combined model approximately obeys Maxwell's equations to a level sufficient for producing high quality physics simulations and analysis. Our approach is applied to a highly realistic calculation of the expected magnetic field in the Mu2e experiment's Detector Solenoid which includes a simple model for the expected statistical measurement uncertainties. Using ten toy measurement simulations, we demonstrate the capabilities of our model in comparison to the least-squares method alone; the least-squares method alone results in a reduced chi-squared statistic of ${2.15 \pm 0.01}$, while our approach improves the reduced chi-square to ${1.034 \pm 0.005}$. Furthermore, for an average toy simulation, we show that the range of the RMS of the three field component residuals reduces from ${0.07-0.37}$ Gauss to ${0.05-0.07}$ Gauss. We find that this novel method is robust against a realistic systematic uncertainty deriving from Hall probe calibration bias and can be used to significantly reduce the number of measurements required to achieve an accurate model.

Kampa, Cole [Caltech] (ORCID:0000000192972920)↗
DOE OSTI2026

Dimensional Reduction for Sampled Priors and Application to Photometric Redshift Distributions

A typical Bayesian inference on the values of some parameters of interest q from some data D involves running a Markov Chain (MC) to sample from the posterior $p$($q$,$n$|$D$) $\propto$ $\mathcal{L}$($D$|$q$,$n$)$p$(q)$p$($n$), where n are some nuisance parameters with a separable prior. In some cases, the nuisance parameters are high-dimensional, and their prior p(n) is itself defined only by a set of samples that have been drawn from some other MC. The MC for the posterior will typically require evaluation of p(n) at arbitrary values of n, i.e., one needs to provide a density estimator over the full n space from the provided samples. But the high dimensionality of n hinders both the density estimation and the efficiency of the MC for the posterior. We describe a solution to this problem: a linear compression of the n space into a much lower-dimensional space u, which projects away directions in n space that cannot appreciably alter $\mathcal{L}$. The algorithm for doing so is a slight modification to principal components analysis, and is less restrictive on p(n) than other proposed solutions to this issue. We demonstrate this “mode projection” technique using the analysis of 2-point correlation functions of weak lensing fields and galaxy density in the Dark Energy Survey, where n is a binned representation of the redshift distribution n(z) of the galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Revealing the evolution of order in materials microstructures using multi-modal computer vision

The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La 1−x Sr x FeO 3 . We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Roadmap and Benchmarking: Privacy in Federated Load Forecasting

Data-driven techniques for energy demand forecasting continue to emerge with promising impacts on distribution grid planning. However, the development of robust and generalizable machine learning models requires that representative high quality training data are available. Distributed energy resources have begun to embed intelligence, gathering large amounts of data on customer demand, behavior, and household devices that are connected to the grid. Though utilities aggregate meter-level demand data for load shaping, demand response, outage management, reliability planning, and billing applications, there lies an inherent privacy concern in sharing consumption data that may identify individual consumer behavioral patterns. Hence, while sharing the data is crucial, the private sensitive customer data must be safeguarded from being exposed or manipulated. In this study, we propose a roadmap for implementing a based privacy preserving framework to support the advancement of data-driven analytics in data-sensitive distributed energy resources environments. The roadmap incorporates federated learning–a distributed training framework, differential privacy–a statistical framework that provides guarantees to safeguard the leakage of sensitive data, secure multiparty computation and homomorphic encryption– techniques for encrypting model gradients and applying secure aggregation on the server. Moreover, we perform baseline experiments on the federated short-term load forecasting (STLF) task using open-source residential load profile datasets, offering insights into the challenges of integrating differential privacy into federated learning.

Abebe, Waqwoya [Oak Ridge National Laboratory (ORN↗