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Results for “Extravehicular Mobility Unit”

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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928 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Thin Film Synthesis of SrZn2P2 with SrI2 Post-Annealing for Enhanced Crystallinity and Optoelectronic Quality

Ternary Zintl phosphides are promising light-absorbing semiconductors for thin-film optoelectronic applications, but strategies for controlling their microstructure and optoelectronic quality remain underexplored. Here, we report the synthesis of phase-pure SrZn2P2 thin films using radio-frequency co-sputtering in a PH3 + Ar atmosphere and investigate the impact of post-growth processing on their structural and optical properties. Grazing-incidence X-ray scattering and Raman spectroscopy confirm the formation of crystalline SrZn2P2 films over a finite compositional window. Optical measurements reveal clear absorption near the direct-band-gap energy (~1.8 eV) and near-band-edge photoluminescence. Further, we have studied the effects of chemically compatible halide-assisted annealing. It is found that SrI2 treatments lead to pronounced grain growth and reduced diffraction peak broadening while preserving phase purity, in contrast to rapid thermal or forming-gas annealing. Notably, annealing with SrI2 at 450 degrees C significantly enhances both the intensity and spatial uniformity of the photoluminescence, thus connecting the observed microstructural consolidation with improved radiative recombination. Our study demonstrates that halide-assisted annealing provides an effective pathway for microstructural control in SrZn2P2 thin films and highlights a generalizable processing strategy for advancing Zintl phosphide semiconductors toward optoelectronic applications.

14 SOLAR ENERGY↗
DOE OSTI2026

Hierarchical Epoxy Structures via Tunable Polymerization-Induced Phase Separation Combined with Additive Manufacturing

Polymerization-induced phase separation (PIPS) allows for the control of thermoset morphologies and properties, enabling the tuning of domain sizes and thermomechanical response. However, its use in generating substructural features in additively manufactured materials has been limited. In this work, we combine epoxy PIPS with UV curable acrylate and rheological modifiers to print nano- to macro-phase separating materials via a two-step, dual-cure approach. This method enables direct ink write printing of hierarchical structures with both controlled morphologies through phase separation and macroscale architecture through print design. We find that formulations for phase-separating materials require judicious incorporation of additives to enable printability and to provide sufficient green strength. Atomic force microscopy-nano infrared mapping reveals tunable, reticulated nano- to micron-scale domains of the resultant multiphase materials and their morphology changes due to additives, resulting in alterations to thermomechanical and tensile properties. Shape memory behavior is also demonstrated through multimaterial additive manufacturing of epoxies with functionally graded internal morphology using active mixing techniques, highlighting this method’s ability to fabricate complex architectures with controlled morphologies and thermomechanical response.

Van Meter, Kylie E [Organic Materials Science, San↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2023

Speciation of Transition Metal Dissolution in Electrolyte from Common Cathode Materials

Significant capacity loss has been observed across extended cycling of lithium-ion batteries cycled to high potential. One of the sources of capacity fade is transition metal dissolution from the cathode active material, ion migration through the electrolyte, and deposition on the solid-electrolyte interphase on the anode. While much research has been conducted on the oxidation state of the transition metal in the cathode active material or deposited on the anode, there have been limited investigations of the oxidation state of the transition metal ions dissolved in the electrolyte. Here, in this work, X-ray absorption spectroscopy has been performed on electrolytes extracted from cells built with four different cathode active materials (LiMn 2 O 4 (LMO), LiNi 0.5 Mn 1.5 O 4 (LNMO), LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811), and (x Li 2 MnO 3 *(1-x) LiNi a Mn b Co c O 2 , with a+b+c=1) (LMRNMC)) that were cycled at either high or standard potentials to determine the oxidation state of Mn and Ni in solution. Inductively coupled plasma-mass spectrometry has been performed on the anodes from these cells to determine the concentration of deposited transition metal ions. While transition metal ions were found dissolved in all electrolytes, the oxidation state(s) of Mn and Ni were determined to be dependent on the cathode material and independent of cycling potential.

25 ENERGY STORAGE↗
DOE OSTI2026

Equation of state for Hf, Ta, W, Re, Os, Ir, Pt, and Au to multi-terapascal pressures from density-functional theory

We present the zero-temperature equation of state (pressure dependence of compression) and phase stability predictions for the 5d-transition metals obtained from all-electron density-functional theory (DFT) calculations. The results compare favorably with experiments but extend beyond current experimental capabilities to 10 TPa. Our study reveals phase changes that are explained from the calculated electronic structure. The cubic face-centered and body-centered structures (fcc and bcc), together with two-, three-, and four-layered hexagonal structures, play major roles under compression. The results’ dependence on the electron exchange and correlation in the DFT approach is investigated, and it is shown that the impact of the choice, while significant at lower pressures, diminishes in the terapascal regime. We further illustrate that the normal parabolic trends in atomic volume and bulk modulus with atomic number, due to the occupation of bonding and anti-bonding 5d states, break down at TPa pressures, suggesting drastically different chemical bonding at these extreme conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Aerosol Can Fireball Tests: Commodity Hazards in the Transportation Environment Phase 1 Report

This report describes a series of tests performed at Sandia’s burn site to better understand the behavior of aerosol commodities and their hazards in the transportation environment. This comes on the tail of a prior study on the use cases and historical hazards associated with aerosol commodities in the shipping environment (Cambridge Systematics Incorporated, CSI, 2020). It is also mindful of the National Fire Protection Agency NFPA30B standard for safe warehousing of aerosol commodities. Warehousing is different from transit because warehousing typically involves active suppression and mitigation measures not practical or relevant to the shipping environment. Transit also typically involves tighter packing and smaller enclosure spaces. The transportation hazard space has not been heavily studied in prior testing specifically aimed towards the ground, rail, and nautical shipping environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Quantum Filtering and Analysis of Multiplicities in Eigenvalue Spectra

Fine-grained spectral properties of quantum Hamiltonians, including both eigenvalues and their multiplicities, provide useful information for characterizing many-body quantum systems as well as for understanding phenomena such as topological order. Extracting such information with small additive error is #BQP-complete in the worst case. In this work, we introduce QFAMES (quantum filtering and analysis of multiplicities in eigenvalue spectra), a quantum algorithm that efficiently identifies clusters of closely spaced dominant eigenvalues and determines their multiplicities under physically motivated assumptions, which allows us to bypass worst-case complexity barriers. QFAMES also enables the estimation of observable expectation values within targeted energy clusters, providing a powerful tool for studying quantum phase transitions and other physical properties. We validate the effectiveness of QFAMES through numerical demonstrations, including its applications to characterizing quantum phases in the transverse-field Ising model and estimating the ground-state degeneracy of a topologically ordered phase in the two-dimensional toric code model. We also generalize QFAMES to the setting of mixed initial states. Our approach offers rigorous theoretical guarantees and significant advantages over existing subspace-based quantum spectral analysis methods, particularly in terms of the sample complexity and the ability to resolve degeneracies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Kauhale 'O Kipapa: Kahikinui Community Cultural, Educational, and Resilience Center Preliminary Design Technical Assistance Summary Report

The Kahikinui Homestead Community in Maui faces energy resilience challenges due to its remote, off-grid location. This report summarizes preliminary technical assistance to design a microgrid for six modular homes using solar PV, wind, and battery storage. Findings show hybrid PV and battery systems, supplemented by small wind turbines, offer cost-effective, resilient solutions. This work supports enhanced energy independence and disaster preparedness for the community.

Quiroz, Jimmy Edward [Sandia National Laboratories↗
DOE OSTI2022

Variational Quantum Circuits to Prepare Low Energy Symmetry States

We explore how to build quantum circuits that compute the lowest energy state corresponding to a given Hamiltonian within a symmetry subspace by explicitly encoding it into the circuit. We create an explicit unitary and a variationally trained unitary that maps any vector output by ansatz A(α → ) from a defined subspace to a vector in the symmetry space. The parameters are trained varitionally to minimize the energy, thus keeping the output within the labelled symmetry value. The method was tested for a spin XXZ Hamiltonian using rotation and reflection symmetry and H 2 Hamiltonian within S z = 0 subspace using S 2 symmetry. We have found the variationally trained unitary gives good results with very low depth circuits and can thus be used to prepare symmetry states within near term quantum computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Emergent surface resonance from charge density wave symmetry breaking in TiSe 2

Surface confined electronic states provide a fertile ground for discovering emergent phenomena that have no counterpart in the bulk, offering new routes to manipulate correlations, symmetry breaking, and dimensionality at the atomic scale. Here, in this study, we show that charge density wave (CDW) symmetry breaking can yield surface states in 1⁢T−TiSe 2 . Micro–angle-resolved photoemission spectroscopy (µ-ARPES) resolves a sharp, two-dimensional surface resonant state (SRS) that emerges within the CDW reconstructed low energy spectrum. The SRS exhibits notable temperature dependence and its spectral weight collapses around ∼ 160 K, while CDW transition temperature 𝑇 CDW is commonly reported as ≈ 202 K. Slab DFT + 𝑈 calculations reproduce a surface localized resonance when CDW folding brings valence and conduction states into near degeneracy, suggesting a correlation tuned, surface selective origin. These results point to a form of correlation-tuned surface resonance in a layered CDW compound and suggest a framework for engineering low-dimensional quantum states in van der Waals materials via symmetry breaking and electronic structure tuning.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Growth of deuterium supersaturated surface layer with increasing ion flux and fluence in plasma-exposed tungsten

Deuterium supersaturated surface layer (DSSL) in tungsten, a few nm thick layer exhibiting extremely high deuterium content (> 5%), has been studied as a function of deuterium plasma ion flux and fluence. Tungsten samples were exposed at 400 K and deuterium ion energy of ∼ 60 eV. The deuterium ion flux spanned over an order of magnitude, being 7.3 × 10 20 , 4.2 × 10 21 , and 3.8 × 10 22 D/m 2 . The fluence ranged from 3.4 × 1024 to 3.4 × 1025 D/m2. The samples and their deuterium content were analyzed by nuclear reaction analysis (NRA), scanning transmission electron microscopy (STEM), and thermal desorption spectroscopy (TDS). The largest thickness of DSSL was found to be around 10.5 nm and was observed in the case of the highest exposure flux and fluence, whereas the layer was only about 3.8 nm thick in the case of the lowest value of the two parameters. The thickness of the DSSL was found to monotonically increase with both deuterium flux and fluence. Finally, similar to the thickness, the estimated D concentration seems to follow the same trend, increasing from the lowest value of around 3 at.% to the highest value of around 5 at.%.

Deuterium↗
DOE OSTI2026

Nonlocal Effect of Percolated Particle Networks on Viscoelasticity of Polymer–Filler Nanocomposites: A Mesoscale Simulation Study

With nanoparticles (NPs) as fillers, polymer nanocomposites (PNCs) usually exhibit enhanced mechanical properties. However, a direct connection between the microscopic structural relaxation and macroscopic mechanical properties of PNCs remains to be established. To investigate the micro-to-macro connection, we develop a mesoscale model, in which the NPbridging polymer chains are represented by a dynamic bonded interaction between NPs, and the bulk polymer matrix is implicitly modeled by overdamped Langevin dynamics. Extensive equilibrium simulations are performed to quantify the microscopic dynamics of model PNCs. Systematic analyses of modified Rouse dynamics, dynamic structure factor, and relaxation modulus uncover that the microscopic relaxation dynamics of PNCs are significantly decelerated across different length scales because of nonlocal effects of percolated particle networks a phenomenon that has not been adequately captured in prior simulation studies. We find that NPvolume- fraction and NP-bonding-energy barrier are the two critical variables that affect bulk viscoelasticity the most. The proposed mesoscale model is versatile and provides a powerful framework for studying structure−property relations of different PNCs.

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

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation↗
DOE OSTI2026

Hybrid biophysical systems for atmospheric CO 2 capture

Negative emissions technologies will be essential for limiting anthropogenic global temperature increases to 2 °C in the later years of the 21st century. Carbonic anhydrase (CA) metalloenzymes catalyze the otherwise slow conversion of CO 2 into carbonic acid (H 2 CO 3 ), suggesting their utility in the rapid hydration and downstream capture of dissolved CO 2 in aqueous media for a variety of CO 2 capture methods, such as thermal and pH swings and mineralization. The possibility of driving the rapid capture of CO 2 by catalyzing the CO 2 hydration bottleneck carries real potential for realizing efficient direct air capture (DAC) and direct ocean capture (DOC) systems. However, scaled application of CAs will be dependent on some way of economically sourcing the enzymes at volumes relevant to scaled DAC/DOC operations. In this perspective, we consider the prospect of catalyzing CO 2 hydration using a CA that is bound to the outer membrane of a cyanobacterial host, engineered constructs we call CyCAMs. Coupling extracellular CA expression to a marine, photosynthetic cyanobacterial host results in a CO 2 hydration catalyst that is continuously refreshed during the bacterial growth cycle, without the need for enzyme purification or harvesting steps. In the case of marine cyanobacteria, sunlight and the solutes native to seawater provide the respective energy, nutrients and sources of inorganic carbon essential to maintaining the bacterial population. We consider the potential impact of CA-mediated CO 2 hydration on a variety of DAC processes, with CO 2 mineralization explored as a primary use case.

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

Lanthanum-Promoted Electrocatalyst for the Oxygen Evolution Reaction: Unique Catalyst or Oxide Deconstruction?

A conventional performance metric for electrocatalysts that promote the oxygen evolution reaction (OER) is the current density at a given overpotential. However, the assumption that increased current density at lower overpotentials indicates superior catalyst design is precarious for OER catalysts in the working environment, as the crystalline lattice is prone to deconstruction and amorphization, thus greatly increasing the concentration of catalytic active sites. We show this to be the case for La 3+ incorporation into Co 3 O 4 . Powder X-ray diffraction (PXRD), Raman spectroscopy and extended X-ray absorption fine structure (EXAFS) reveal smaller domain sizes with decreased long-range order and increased amorphization for La-modified Co 3 O 4 . This lattice deconstruction is exacerbated under the conditions of OER as indicated by operando spectroscopies. The overpotential for OER decreases with increasing La 3+ concentration, with maximum activity achieved at 17% La incorporation. HRTEM images and electron diffraction patterns clearly show the formation of an amorphous overlayer during OER catalysis that is accelerated with La 3+ addition. O 1s XPS spectra after OER show the loss of lattice-oxide and an increase in peak intensities associated with hydroxylated or defective O-atom environments, consistent with Co(O) x (OH) y species in an amorphous overlayer. Furthermore, our results suggest that improved catalytic activity of oxides incorporated with La 3+ ions (and likely other metal ions) is due to an increase in the number of terminal octahedral Co(O) x (OH) y edge sites upon Co 3 O 4 lattice deconstruction, rather than enhanced intrinsic catalysis.

Catalysts↗
DOE OSTI2026

Stoichiometric effects on grain growth in zirconium carbide coatings for high-temperature nuclear fuel

Interest in coated particle fuel for space nuclear propulsion (SNP) has expanded in recent years due to successful demonstrations of the resiliency of the coatings to extreme environments. For SNP applications, the coating layer for the particle design needs to be able to withstand exposure to high temperature hydrogen during operating conditions. ZrC has been proposed as a protective layer, however, it is important to understand the high temperature behavior to ensure adequate protection to this fuel. In this study, surrogate ZrC coated particles were heat treated at 1900 °C up to 300 min, to examine how the microstructure evolves when exposed to high temperature. Scanning electron microscopy and electron backscatter diffraction (EBSD) were conducted to determine grain size and grain boundary character and orientation to determine the degree of change in the ZrC layer post heat treatment. Raman spectroscopy provided insight to understand how the as-fabricated stoichiometry of each sample contributed to the differences in grain growth behavior. Despite the as-fabricated samples showing a similar initial grain size and grain boundary character, the samples with a higher amount of excess carbon exhibited smaller grain areas and slower growth rates when exposed to 1900 °C. In conclusion, this investigation details the as-fabricated microstructure of the ZrC layer, specifically grain size, evolved under high temperature as this can impact the performance of the fuel under operating conditions.

EBSD↗
DOE OSTI2023

Self‐Propelling Macroscale Sheets Powered by Enzyme Pumps

Nanoscale enzymes anchored to surfaces act as chemical pumps by converting chemical energy released from enzymatic reactions into spontaneous fluid flow that propels entrained nano‐ and microparticles. Enzymatic pumps are biocompatible, highly selective, and display unique substrate specificity. Utilizing these pumps to trigger self‐propelled motion on the macroscale has, however, constituted a significant challenge and thus prevented their adaptation in macroscopic fluidic devices and soft robotics. Using experiments and simulations, we herein show that enzymatic pumps can drive centimeter‐scale polymer sheets along directed linear paths and rotational trajectories. In these studies, the sheets are confined to the air/water interface. With the addition of appropriate substrate, the asymmetric enzymatic coating on the sheets induces chemically driven, buoyancy flows that controllably propel the sheet's motion on the air/water interface. The directionality and speed of the motion can be tailored by changing the pattern of the enzymatic coating, type of enzyme, and nature and concentration of the substrate. This work highlights the utility of biocompatible enzymes for generating motion in macroscale fluidic devices and robotics and indicates their potential utility for in vivo applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing

While the complementary metal-oxide semiconductor (CMOS) technology is the mainstream for the hardware implementation of neural networks, an alternative route is explored based on a new class of spiking oscillators called “thermal neuristors”, which operate and interact solely via thermal processes. Utilizing the insulator-to-metal transition (IMT) in vanadium dioxide, a wide variety of reconfigurable electrical dynamics mirroring biological neurons is demonstrated. Notably, inhibitory functionality is achieved just in a single oxide device, and cascaded information flow is realized exclusively through thermal interactions. To elucidate the underlying mechanisms of the neuristors, a detailed theoretical model is developed, which accurately reflects the experimental results. In conclusion, this study establishes the foundation for scalable and energy-efficient thermal neural networks, fostering progress in brain-inspired computing.

36 MATERIALS SCIENCE↗