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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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465 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Hydrogen Production and Li-Ion Battery Performance with MoS2-SiNWs-SWNTs@ZnONPs Nanocomposites

This study explores the hydrogen generation potential via water-splitting reactions under UV-vis radiation by using a synergistic assembly of ZnO nanoparticles integrated with MoS2, single-walled carbon nanotubes (SWNTs), and crystalline silicon nanowires (SiNWs) to create the MoS2-SiNWs-SWNTs@ZnONPs nanocomposites. A comparative analysis of MoS2 synthesized through chemical and physical exfoliation methods revealed that the chemically exfoliated MoS2 exhibited superior performance, thereby being selected for all subsequent measurements. The nanostructured materials demonstrated exceptional surface characteristics, with specific surface areas exceeding 300 m2 g−1. Notably, the hydrogen production rate achieved by a composite comprising 5% MoS2, 1.7% SiNWs, and 13.3% SWNTs at an 80% ZnONPs base was approximately 3909 µmol h−1g−1 under 500 nm wavelength radiation, marking a significant improvement of over 40-fold relative to pristine ZnONPs. This enhancement underscores the remarkable photocatalytic efficiency of the composites, maintaining high hydrogen production rates above 1500 µmol h−1g−1 even under radiation wavelengths exceeding 600 nm. Furthermore, the potential of these composites for energy storage and conversion applications, specifically within rechargeable lithium-ion batteries, was investigated. Composites, similar to those utilized for hydrogen production but excluding ZnONPs to address its limited theoretical capacity and electrical conductivity, were developed. The focus was on utilizing MoS2, SiNWs, and SWNTs as anode materials for Li-ion batteries. This strategic combination significantly improved the electronic conductivity and mechanical stability of the composite. Specifically, the composite with 56% MoS2, 24% SiNWs, and 20% SWNTs offered remarkable cyclic performance with high specific capacity values, achieving a complete stability of 1000 mA h g−1 after 100 cycles at 1 A g−1. These results illuminate the dual utility of the composites, not only as innovative catalysts for hydrogen production but also as advanced materials for energy storage technologies, showcasing their potential in contributing to sustainable energy solutions.

Chemistry↗
DOE OSTI2026

Flash Heating of a Hollow Rod to Determine Thermal Properties

In a nuclear reactor, prolonged exposure to high neutron flux levels can change material properties of reactor components. Due to the danger posed to personnel by highly radioactive components such as spent fuel, noncontact methods must be used to determine these properties. The objective of the current research is to test the viability of using a flash-heating method to determine the thermal diffusivity of a silicon carbide (SiC) tube, which could be used as cladding for a nuclear fuel rod. The flash-heating experiment was conducted at Oak Ridge National Laboratory and temperature results were analyzed as a two-Dimensional cross section which assumed axial symmetry. The model was fitted iteratively to the temperature measurements using nonlinear regression which required values for thermal diffusivity, Biot number and a term to determine the magnitude of the heat absorbed by the flash. The method could be expanded in the future to estimate the thermal diffusivity of spent nuclear fuel rods in an effort to increase the certainty of new reactor designs using precise thermal properties throughout the core life. A statistical analysis of the results of this work is provided as part of the analysis.

McMasters, Robert L [Virginia Military Institute, ↗
DOE OSTI2025

Advancements in nanocomposites for enhancing the performance of rechargeable lithium-ion batteries

The benefits of nanotechnology have been realized in almost every component of lithium-ion batteries. From electrodes to electrolytes, the incorporation of nanoparticles as dopants and coatings has shown marked improvements in cell cycle life, efficiency, mechanical and thermal stabilities, and lithium-ion transport. The improvements realized depends on several factors, from processing methods, nanoparticle type, structure, and concentration, to the material into which the nanoparticulate will be incorporated. Regardless of these many factors, nanotechnology has vastly improved the performance of secondary lithium-ion batteries. Here we will highlight some of the works that demonstrate these improvements and the quantitative benefits of nanotechnology.

25 ENERGY STORAGE↗
NASA NTRS2026

An Investigation Regarding the Effects of Volume Dynamics on Gas Turbine Engine Performance and Operability

This work explores the impact of adding volume dynamics to an electrified turbofan engine model. The zero-dimensional single-input single-output volume elements capture the physics of fluid compressibility of flow in the engine core gas path turbomachinery during transient operation with greater fidelity. Some background regarding the motivation for this effort is provided. A model of the volume element is developed from first principles. The baseline engine model is described and an explanation is given of the modifications made to incorporate the volume elements into the new model. Details of the simulated inputs, designed to elicit exaggerated dynamic responses and to facilitate comparison between the baseline and modified engine models, are explicated. The results of these simulations are presented and discussed, demonstrating that the transient performance and operability of the modified engine model, measured by parameters such as shaft speeds, thrust, and high-pressure compressor (HPC) stall margin, are impacted by the additional dynamics. Commentary is provided regarding potential explanations for the differences in behavior exhibited by the two models. Finally, suggestions are offered for future work that might improve the volume models developed in this effort and leverage the improved fidelity enabled by the modeling of turbomachinery volume dynamics.

Volume dynamics↗
DOE OSTI2026

Effects of high-dose neutron irradiation at light-water reactor relevant temperature on the mechanical properties of SiC/SiC composites

For this study, the neutron dose-dependent evolutions and the underlying mechanisms of properties of SiC fiber-reinforced SiC matrix (SiC/SiC) composites at a temperature relevant to light-water reactors (∼600 K) were investigated and analyzed. Chemical vapor infiltrated (CVI) SiC/SiC composites reinforced with Hi-Nicalon Type S or Tyranno SA3 fiber were neutron-irradiated to doses up to 30 dpa. The irradiated composites retained their flexural strengths. The thermal diffusivity and dimensional changes were mostly retained from 2.0 to 30.2 dpa. Discrepancies in irradiation responses among CVI SiC/SiC composites from different sources were found. Additional microstructural analysis using Raman spectroscopy and numerical analysis on irradiation effect on residual stress were used to explain how the microstructural variables, especially of carbon interphases, affect the mechanical properties in the 30–40 dpa dose range.

Continuous fiber-reinforced ceramic matrix composi↗
NASA NTRS1997

The In-Orbit Battery Reconditioning Experience On Board the Orion 1 Spacecraft

The Orion 1 spacecraft is a three-axis stabilized geostationary earth orbiting commercial communications satellite which was launched on November 29, 1994 aboard an Atlas II launch vehicle. The power subsystem is a dual bus, dual battery semi-regulated system with one 78 Ampere-hour nickel-hydrogen battery per bus. The batteries were built and tested by Eagle Picher Industries, Inc., of Joplin, MO and were integrated into the spacecraft by its manufacturer, Matra Marconi Space UK Ltd. This paper presents the results obtained during the first four in-orbit reconditioning cycles and compares the battery performance to ground test data. In addition, the on-station battery management strategy and implementation constraints are described. Battery performance has been nominal throughout each reconditioning cycle and subsequent eclipse season.

Hoover, S. A.↗
DOE OSTI2025

AIVT: Inference of turbulent thermal convection from measured 3D velocity data by physics-informed Kolmogorov-Arnold networks

We propose the artificial intelligence velocimetry-thermometry (AIVT) method to reconstruct a continuous and differentiable representation of the temperature and velocity in turbulent convection from measured three-dimensional (3D) velocity data. AIVT is based on physics-informed Kolmogorov-Arnold networks and trained by optimizing a loss function that minimizes residuals of the velocity data, boundary conditions, and governing equations. We apply AIVT to a set of simultaneously measured 3D temperature and velocity data of Rayleigh-Bénard convection, obtained by combining particle image thermometry and Lagrangian particle tracking. This enables us to directly compare machine learning results to true volumetric, simultaneous temperature and velocity measurements. We demonstrate that AIVT can reconstruct and infer continuous, instantaneous velocity and temperature fields and their gradients from sparse experimental data at a high resolution, providing an additional approach for understanding thermal turbulence.

Science & Technology - Other Topics↗
NASA NTRS1996

Battery performance of the SKYNET 4A spacecraft during the first six years of on station operation

The SKYNET 4A spacecraft is a three-axis stabilized geostationary earth-orbiting military communications satellite which was launched on 1 Jan. 1990 aboard a Titan 3 launch vehicle. The power subsystem is a twin bus, twin battery semi-regulated system and is equipped with one 28-cell, 35 Ampere-hour battery per bus. The cells were manufactured by Gates Aerospace Batteries of Gainesville, FL, and the batteries were built, tested and integrated by British Aerospace Space Systems Ltd. This paper presents a brief survey of the first six years of on-station operation and the operational battery management strategy that has been adopted. Thermal management constraints have led to an unconventional battery operational regime. However, no sign of degradation is evident and the observed spacecraft battery performance remains nominal.

Johnson, P. J.↗
NASA NTRSDate not supplied

Thermomechanical Modeling of Woven Materials With Particle-Based, Explicit-Fiber Simulations

Fiber-based materials are extensively used to protect spacecraft during entry. Insulative fibers, often in a fiber network or woven, provide rigidity, strength, and control of material anisotropy and density. Woven thermal protection materials, such as ADEPT (Adaptable, Deployable Entry and Placement Technology), 3D-MAT (3-Dimensional Multifunctional Ablative Thermal Protection), and 3MDCP (3D Woven Mid-Density Carbon Phenolic), enable missions with stronger and denser materials for entry profiles with high shear and heat flux. Vulnerabilities to woven thermal protection materials include manufacturing-induced material property variation, and impact from micrometeoroids. Simulating woven materials under these conditions require models that can resolve hierarchal structures, thermomechanical behavior, and failure. To address this, we simulate weave thermal conduction and mechanical deformation. We simulate the full weave with a coarse-grained yarn model is presented. The model combines a validated, high-resolution single 3MDCP yarn model and phenolic resin model. Instead of modeling every fiber, each yarn ply with order 10, instead of order 1000, fibers. The discrete element bonded particle model (DEM-BPM) of fibers captures the thermal and mechanical behavior within and between fibers. We study the proportion of heat transfer and stress via the contact network, fiber bonds, and overall weave geometry.

bonded particle↗
NASA NTRS2018

Initial Jitter Analysis of Lynx, a Proposed Future Large Astrophysics Facility

Lynx is an X-Ray telescope large-mission concept for consideration in NASA's 2020 Astrophysics Decadal Survey. A conceptual structural design is evolving that leverages the success and lessons learned from Chandra and that takes into account unique needs of Lynx. Space optics systems require extreme stability. Any motion in-service (thermal effects, structural dynamics, etc.) impacts performance. An initial analysis was performed to predict the first-cut dynamic responses, jitter, at two selected points on the Lynx observatory. One point is on the Lynx X-ray Mirror Assembly (LMA) and the other, on the focal plane Integrated Science Instrument Module (ISIM). Relative motion between these two points was predicted along with vibration spectra. This information will be used in upcoming analyses of the LMA and the ISIM.

J Brent Knight↗
DOE OSTI2026

Excitons in van der Waals magnetic materials

Two-dimensional magnetic semiconductors provide a unique platform where long-range magnetic order coexists with strongly bound excitons. Because excitonic states and magnetic moments originate from the same electronic orbitals and couple via intrinsic exchange interactions, optical excitations in these systems exhibit pronounced sensitivity to magnetic order. Recent experiments show unusually strong magneto-optical responses and direct exciton–magnon coupling, establishing new routes for controlling light–matter interactions with spin degrees of freedom. Here, this Review surveys key developments, focusing on representative material systems, experimental signatures, and theoretical frameworks used to describe these phenomena. We conclude with perspectives on how this rapidly evolving field could enable next-generation optoelectronic and quantum technologies leveraging the coupled dynamics of light, charge and spin.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Interface-induced fast Li+ transport in mixed ionic–electronic conductors

Interfacial instability between lithium metal and solid-state electrolytes limits the performance of all-solid-state lithium metal batteries (ASSLBs), leading to parasitic reactions, non-uniform Li+ flux, and dendrite growth. Here, we develop a composite interlayer composed of the anti-perovskite Li2OHCl0.75Br0.25 (AP) and carbon nanotubes (CNTs) to enhance both interfacial stability and ionic transport. The AP–CNT interlayer exhibits enhanced Li+ conductivity arising from interfacial electron transfer from AP to CNTs, which generates a built-in electric field that facilitates Li+ migration. Lithium symmetric cells incorporating this interlayer achieve a high critical current density of 2.4 mA cm−2 at 55 °C. This design integrates chemical robustness with coupled ion–electron transport, offering a generalizable strategy for safe, dendrite-free, and high-performance ASSLBs.

He, Chenche↗
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↗
NASA NTRS2026

Development and Experimental Validation of a Path-Dependent Spin Forming Finite Element Model

Spin forming is an advanced manufacturing process widely used in the aerospace and defense sectors to produce lightweight, high-strength cylindrical components with tight dimensional tolerances. This study explores the applicability of the path-dependent Mechanical Threshold Stress (MTS) constitutive model by simulating the evolution of geometry, machining forces, and plastic deformation during the spin forming of a 10-mm thick 6061-O aluminum cylinder. While numerical modeling of spin forming has advanced substantially over the past decade, systematic verification and experimental validation of material models remain limited, particularly in predicting through-thickness process evolution. The MTS model, incorporating a Voce hardening rule, is employed for its ability to represent cyclic loading, rapidly varying temperature fields, and strain rates characteristic of spin forming. Numerical convergence analysis indicates discretization uncertainties between 0.3% and 9.2% for key quantities of interest. Experimental validation demonstrates that the MTS model, when implemented with a verified mesh, accurately reproduces both elastic and plastic behavior of 6061-O aluminum, predicting peak roller loads within 11–18% of measurements, geometric tolerances within 3%, and plastic strain distributions within 10% of experimental values. Collectively, these results establish a validated computational framework for predictive spin-forming simulations with quantified confidence, providing a foundation for extension to other alloys, geometries, and forming conditions.

Spin forming↗
DOE OSTI2026

Surrogate modeling of Monte Carlo radiation transport with convolutional neural networks for shielding optimization

Here, we present a machine learning (ML)-based surrogate model using convolutional neural networks (CNN) designed to emulate the attenuation of neutron fields as they pass through various shielding materials. This model can compute the outgoing neutron flux almost instantaneously and achieves reasonable accuracy compared to traditional Monte Carlo (MC)-based codes, which are computationally intensive. This emulator alleviates the complexity of neutron radiation transport through shielding materials by reducing the dimensionality and enables shielding optimization for a known radiation environment. This optimization process, which would have taken an unrealistic timeline due to several complex radiation transport simulations, can now be achieved in minutes, thus increasing computational capabilities in radiation shielding assessment. We demonstrate the applications of this emulator in computing effective dose rates and optimizing shielding solutions for a heavy-ion accelerator facility, such as the Facility for Rare Isotope Beams, where secondary neutrons produced via beam interactions dominate the radiation environment.

accelerator shielding↗
DOE OSTI2024

Analytical Model for Atomic Relaxation in Twisted Moiré Materials

By virtue of being atomically thin, the electronic properties of heterostructures built from two-dimensional materials are strongly influenced by atomic relaxation. The atomic layers behave as flexible membranes rather than rigid crystals. Here we develop an analytical theory of lattice relaxation in twisted moiré materials. We obtain analytical results for the lattice displacements and corresponding pseudo gauge fields, as a function of twist angle. We benchmark our results for twisted bilayer graphene and twisted WSe 2 bilayers using large-scale molecular dynamics simulations. Our single-parameter theory is valid in graphene bilayers for twist angles 𝜃 ≳ 0.7°, and in twisted WSe 2 for 𝜃 ≳ 1.6°. Furthermore, we also investigate how relaxation alters the electronic structure in twisted bilayer graphene, providing a simple extension to the continuum model to account for lattice relaxation.

36 MATERIALS SCIENCE↗
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↗
NASA NTRS2026

Barium Fluoride as a Standard Reference Material for Infrared Refractometry

This work proposes a standard reference material (SRM) for measurements of refractive index in the infrared spectral region (1–12 μm). The purpose of this material is to enable cross-method comparison of refractive index data obtained through minimum deviation, ellipsometry, interferometry, and prism coupling techniques. This will allow vendors and metrology laboratories, regardless of which technique they employ, to certify that their measurements meet required levels of accuracy, precision, and repeatability. Drawing on foundational work by Tilton at the National Bureau of Standards, a figure of merit for candidate SRM materials is outlined, and three materials are selected for further evaluation. Ultimately, barium fluoride is proposed as the most suitable SRM for the infrared spectral region, based on its broad transmission range, chemical and mechanical stability, low temperature dependence of refractive index, and well-characterized dispersion behavior.

Andrew Howe↗