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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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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Single-shot in-line x-ray phase-contrast imaging of void-shockwave interactions in fusion energy materials

Recent breakthroughs in nuclear fusion, specifically the report of reactions exceeding scientific breakeven at the National Ignition Facility (NIF), highlight the potential of inertial fusion energy (IFE) as a sustainable and virtually limitless energy source. However, further progress in IFE requires characterization of defects in ablator materials and how they affect fuel capsule compression. Voids within the ablator can degrade energy yield, but their impact on the density distribution has primarily been studied through simulations, with limited high-resolution experimental validation. To address this, we used the x-ray free-electron laser (XFEL) at the matter in extreme conditions (MECs) instrument at the Linac coherent light source (LCLS) to capture 2D x-ray phase-contrast (XPC) images of a void-bearing sample with a composition similar to inertial confinement fusion (ICF) ablators. By driving a compressive shockwave through the sample using MEC's long-pulse laser system, we analyzed how voids influence shockwave propagation and density distribution during compression. To quantify this impact, we extracted phase information using two phase retrieval algorithms. First, we applied the contrast transfer function (CTF) method, paired with Tikhonov regularization and a fast optimization approach to generate an initial phase estimate. We then refined the result using a projected gradient descent (PGD) method that works directly with the sample's refractive index. Comparing these results with radiation adaptive grid Eulerian (xRAGE) radiation hydrodynamic simulations enables identification of model validation needs or improvements. By calculating phase maps in situ, it becomes possible to reconstruct areal density maps, improving understanding of laser-capsule interactions and advancing IFE research.

Hodge, D. S. [Colorado State Univ., Fort Collins, ↗
DOE OSTI2023

Adaptive Discovery and Mixed-Variable Optimization of Next Generation Synthesizable Microelectronic Materials

Design of new microelectronic materials is characterized by several challenges such as high-dimensionality of the atomic structure-composition variable space, formidable cost of directly using high-fidelity simulations for design optimization, dispersity in literature-reported similar materials and synthesis methods, complex physical mechanisms, and mixed qualitative and quantitative design variables that lead to a disjointed design space. Even though machine learning (ML) techniques have been employed to expedite materials innovation, existing methods treat ML and design optimization as two separate processes, failing to resolve the fundamental challenges associated with high dimensionality and mixed-variable complexity. We have developed a ML enhanced mixed-variable material design optimization framework to efficiently extract useful information from existing data in literature and physics-based simulations to guide the autonomous search for optimal materials. Our proposed framework is composed of four computational modules: (1) a natural language processing (NLP) based virtual screening module, (2) classification based concept exploration module, (3) a density functional theory (DFT)-based high-fidelity evaluation model, and (4) a novel latent-variable Gaussian process (LVGP) ML model for mixed-variable problems with uncertainty quantification, which seamlessly integrates with Bayesian Optimization (BO) and achieves superb efficiency through embedded physics-based dimension reduction. Our approach is demonstrated and validated using the testbed of functional materials exhibiting metal-insulation transitions (MITs), with the targeted reversible resistivity changes (∼10^5) near room temperature. At the end of the 30-month project, we have developed a series of new ML techniques using NLP, conditional variational autoencoders, active learning, latent-variable Gaussian processes, integrated with Bayesian optimization. Our project has resulted in new predicted MITs compounds and improved understanding of MITs microscopic mechanisms, which in turn will revolutionize microelectronics science to provide energy-saving solutions. Our research has improved both creativity and efficiency in transforming rare-event discoveries of new functional materials to persistent innovations. In addition to open-sourcing the online MIT database and the classification model, the LVGP open source code has been downloaded more than 15,000 times within two years. More than 40 MIT compounds have been identified and many have been pursued experimentally via collaborators. The research results are published in close to 20 collaborative papers in high-impact journals, such as Chem. Mater., Appl. Phys. Rev., Sci. Rep., among others of design space.

36 MATERIALS SCIENCE↗
NASA NTRS2000

An Experimental and Mathematical Study to Evaluate the Role of Ultrasonic Energy in Promoting Microstructural Uniformity During Controlled Directional Solidification Processing

There are many commercially relevant metal and non-metal "alloy" systems that separate into two different liquids upon cooling from a higher temperature. Consequently during solidification processing the inherent density differences between the two liquid phases leads to rapid, gravity driven, separation and severe segregation, a factor that significantly compromises the desired material properties. Processing in a microgravity environment minimizes settling but segregation still occurs due to gravity independent wetting and coalescence phenomena. This presentation reports on experiments that utilized succinonitrile-glycerol mixtures, a transparent system that 1) separates into two liquids upon cooling and 2) is also well established as an analogue to solidification phenomena observed in metals. Segregation was significantly reduced when the mixtures were subjected to ultrasonic energy during directional solidification processing. The processing parameters introduced by this application have been evaluated in view of optimizing dispersion uniformity. The improvement is in good agreement with a novel model that 1) predicts the achievable size of the droplets as a function of applied ultrasonic energy and then 2) calculates their relative sinking velocity through the bulk liquid.

Grugel, R. N.↗
DOE OSTI2025

Ferromagnetic Atomic d ‐ p Orbital Hybridization for Promoting Al‐S Batteries

Rechargeable aluminum‐sulfur batteries (Al‐S) are emerging as a promising alternative energy storage system beyond lithium‐ion batteries due to their high energy density, abundant material resources, and economic efficiency. However, their practical application remains challenged by sluggish conversion kinetics, polysulfide shuttling, and low sulfur cathode utilization. While extensive studies have focused on enhancing polysulfide adsorption through catalytic strategies, the roles of electronic structure in dictating catalytic performance remain underexplored. Here, this work unveils the critical effect of unpaired electronic structure on the catalytic performance of single atom ferromagnetic transition metals through a systematic evaluation of three typical atomically dispersed ferromagnetic single atoms—Fe, Co, and Ni—supported on porous carbon (denoted as PC‐SAFAs). Comprehensive characterizations and density functional theory (DFT) calculations reveal that the PC‐SAFe catalysts, exhibiting the highest spin polarization arising from unpaired electrons, demonstrate the strongest interactions with polysulfide, thereby facilitating rapid and reversible polysulfide conversion reactions. Consequently, Al‐S batteries incorporating the optimized PC‐SAFe cathode achieve an impressive specific capacity of 508.8 mAh g −1 at 1.0 A g −1 after 500 cycles, along with much improved rate capability. In conclusion, this work provides a deeper understanding of the role of electronic structure in catalytic chemistry, and offers new insights for developing high‐performance Al‐S batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Machine Learning Approach for the Prediction of Formability and Thermodynamic Stability of Single and Double Perovskite Oxides

Perovskite oxides continue to attract huge interest due to their fascinating and wide-ranging properties for diverse applications. The tunability of these properties may be further enhanced by increasing their compositional complexity via double perovskite-ordered configurations containing multiple cations. In this work, we focus on an exhaustive chemical space of single and double oxide perovskites and optimally explore this space to identify novel compositions that are likely to form stable compounds. Critically, we examine the relationship between formability, the practical ability to synthesize a compound, and stability, the thermodynamic preference to form the structure. Our formability and stability training data sets were enumerated from the available experimental literature and in-house density functional theory computations and contained 1505 and 3469 examples, respectively, representing state-of-the-art in the current open literature in perovskite and double perovskite compounds. Subsequently, cross-validated and highly accurate machine learning classification models are built using these training data sets and employed to screen for novel stable oxide perovskites. The study identifies (1) atomic features relevant to prediction of formability and stability in perovskite and double perovskite compounds, (2) the importance of including energy contributions due to local structural relaxations going beyond the high symmetry perovskite phase, and (3) 437,828 double perovskite compounds that are likely to be stable and 891,188 compounds that are likely to be formable. From the intersection of this large chemical space of formable and stable oxide perovskites, 414 compositions are identified as the most promising candidates for future experimental synthesis of novel oxide perovskites. The developed models may be generalized and have implications beyond perovskite discovery if applied to other families of compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Inferring relative dose-dependent color center populations in proton irradiated thoria single crystals using optical spectroscopy

In this work, we have utilized photoluminescence spectroscopy and optical ellipsometry to characterize the dose-dependence of the photoluminescence emission intensity and changes in optical absorption of thoria single crystals subject to irradiation with energetic protons at room- and elevated-temperatures. The photoluminescence peaks and the optical absorption bands are attributed to creation of new electronic states emerging from defects resulting from displacement damage. These bands are most likely associated with electrons trapped at the oxygen vacancy sites similar to color centers formed in other irradiated oxides and halides. Our experimental observations are supported by a standard density functional theory calculation of the electronic structure in pristine and oxygen vacancy-bearing thoria crystals. The dose-dependence of the intensity of the photoluminescence peaks is used to parameterize a rate theory model that estimates the concentration of color centers in the irradiated crystals. This parameterization provides optimized migration barrier parameters for oxygen interstitials and vacancies that simultaneously capture the optical response of the crystals irradiated at room- and elevated-temperature. These optical spectroscopy techniques offer a promising pathway to characterize the population of color centers formed at the sites of oxygen anion vacancies, particularly in irradiated nuclear fuels, where atomic-level defects cannot be readily imaged using electron microscopy. When combined with other direct and indirect characterization tools, our approach can provide new insight into defect formation and accumulation in energy materials over single atomic to extended length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Superlattice-Structured Films by Magnetron Sputtering as New Era Electrodes for Advanced Lithium-ion Batteries

Sustaining sound structures in Si-based anodes is extremely challenging because of the high volumetric expansion that occurs upon cycling. To maintain high capacities over cycles, new designs rely on engineering-specific hierarchical geometries and/or optimized composite compositions such that at least one of the multiple elements serves as buffer and/or electron conductive pathways in the electrodes. In this paper, we report an innovative design in which alternating layers of periodic atomic structures involving multiple elements form a new anode material for lithium-ion batteries. In this work, a superlattice-structured amorphous film made using Si, Mo, and Cu is fabricated by a simple and scalable magnetron sputtering process for the first time. This continuous and repetitive superlattice formation along the film thickness provides a homogeneous stress-strain distribution. The Mo-Cu layer in the superlattice acts as an inactive-conductive layer and as a backbone to handle the volume expansion of active Si upon cycling. This nano-functional superlattice approach enables harnessing the high energy density of Si while maintaining its structural stability. As a result, the electrode exhibits high specific capacity and capacity retention even at high cycling rates. The possible use of the film in a full cell is also evaluated by cycling it vs. the LiMn 1.5 Ni 0.5 O 4 cathode. The full cell maintains a stable capacity of about 900 mAh g anode -1 over 150 cycles, at ~600 mA g -1 rate. The remarkable performance of this nano-functional superlattice film is found to be promising as anodes for applications that require high energy, long calendar life, and excellent abuse tolerance such as electric vehicle batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Material Discovery and Design Principles of Perovskite Oxides for Reversible Solid Oxide Cells (R-SOC)

Reversible solid oxide cells (R-SOCs) are highly efficient devices for energy conversion and storage, capable of operating for both hydrogen utilization and production. In fuel cell mode, an R-SOC consumes hydrogen or natural gas to generate electricity, while in electrolysis mode, it produces hydrogen from steam. The discover of new materials with rapid oxygen surface exchange kinetics and enduring stability is crucial for the economically viable commercialization of R-SOCs. To facilitate this pursuit, we conducted extensive Density Functional Theory (DFT) calculations and developed Machine Learning (ML) models to predict critical catalytic properties essential for R-SOCs, such as oxygen surface exchange/diffusivity, and area-specific resistance (ASR). BaCoxFeyZrzO3-d(BFCZ)(x+y+z=1) emerged as a promising family of electrode materials with high activity and stability, validated through systematic experimental study. Moreover, a robust numerical multiphysics model was developed to optimize materials and microstructure parameters, providing the ability to predict the performance of functional R-SOCs.

Liu, Jian↗
DOE OSTI2021

UiO-66 Metal–Organic Framework as an Anode for a Potassium-Ion Battery: Quantum Mechanical Analysis

The natural abundance of potassium in the earth’s crust is 1000 times higher than that of lithium, so energy technologies built on potassium are more sustainable. Potassium-ion batteries have attracted considerable attention because of their relatively low cost and high operating potential, but questions remain about the best anode material for such batteries. Here, in this paper, we report first-principles computations based on density functional theory to investigate the performance of the UiO-66 metal–organic framework as an anode material for potassium-ion batteries; the goal is to provide a fundamental understanding of metal–organic framework (MOF)-based electrodes to guide the design and development of high-performance potassium-ion batteries. Our study includes the stability and electronic properties of potassiated structures and the mechanisms of potassium intercalation and diffusion in the framework. The results indicate that UiO-66 has a maximum specific capacity of 644 mAh/g as the anode of a potassium-ion battery. During potassiation, we observe charge transfer from potassium to carbon or oxygen of UiO-66 near the intercalated K. During K diffusion, the K migrates along the UiO-66 framework with a maximal migration energy barrier of 0.377 eV in the optimal pathway, which is much lower than the barriers for Li and Na diffusion in UiO-66. The diffusion coefficient of K in the anode is several orders of magnitude larger than those of Li and Na. This favors potassium ions over lithium ions or sodium ions when UiO-66 is the anode.

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

Aggregation of Size-Selected Oxide Clusters Deposited onto Au(111)

Kinetic Monte Carlo (kMC) simulations along with density functional theory (DFT) calculations were used to investigate the aggregation of size-selected Nb 3 O y (y = 5, 6, 7) clusters deposited onto the Au(111) surface. Recent STM experiments showed that the cluster binding sites and sizes of the cluster assemblies on the Nb 3 O y /Au(111) surfaces strongly depend on the stoichiometry of the clusters, i.e., the oxygen-to-niobium ratio. To better understand the origins of these differences, kMC simulations of the nucleation and growth of cluster assemblies were performed using energy barriers for diffusion and intercluster interactions estimated from DFT calculations of cluster binding and dimerization energies, respectively. Comparisons of the kMC simulations with STM images of the as-deposited Nb 3 O y /Au(111) surfaces at RT and after high temperature annealing were used to further optimize the energetics and gauge the importance of nearest neighbor interactions. The kMC simulations demonstrate that the assembly of Nb 3 O y clusters on Au(111) are largely controlled by the magnitude of the barriers for diffusion and interparticle-bond formation, while changes at higher temperatures are sensitive to the binding energies between nearest neighbors. Simulations for the Nb 3 O 5 and Nb 3 O 6 clusters, which exhibit smaller cluster assembly sizes in STM, required larger diffusion barriers as well as different barriers for interparticle binding, which reflected differences in DFT calculated dimerization energies. Furthermore, the results demonstrate the effectiveness of combined DFT and kMC calculations for understanding how the stoichiometry affects the aggregation of small oxide clusters on a metal surface.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optimal Binding Affinity for Sieving Separation of Propylene from Propane in an Oxyfluoride Anion-Based Metal–Organic Framework

Highly efficient adsorptive separation of propylene from propane offers an ideal alternative method to replace the energy-intensive cryogenic distillation technology. Molecular sieving-type separation via high-performance adsorbents is targeted for superior selectivity, but the limit in adsorption capacity remains a great challenge. Here, we report an oxyfluoride-based ultramicroporous metal–organic framework UTSA-400, [Ni(WO 2 F 4 )(pyz) 2 ] (pyz = pyrazine), featuring one-dimensional pore channels that can accommodate the propylene molecules with optimal binding affinity while specifically excluding the propane molecules. The exposed oxide/fluoride pairs in UTSA-400 serve as strong functional sites for strengthened propylene–host interactions, accounting for a significantly enhanced propylene uptake, while the propane molecules are excluded due to the regulated host framework dynamics. The strong propylene binding enables near-saturation of propylene in the pore confinement at ambient conditions, leading to full utilization of pore space and superior packing density. Combined in situ infrared spectroscopy measurements and dispersion-corrected density functional theory calculations clearly unveil the nature of boosted host–guest binding. Direct production of polymer-grade (>99.5%) propylene with remarkable dynamic productivity is demonstrated by column breakthrough experiments. Furthermore, this work presents an example of pore engineering with atomic precision to break the trade-off in adsorptive separation through guest binding optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Deciphering the Evolution of Current Distribution in Hybrid Silver Vanadium Oxide / Carbon Monofluoride Cathodes within Lithium Primary Batteries

For batteries to function effectively all active material must be accessible requiring both electron and ion transport to each particle. A common approach to generating the needed conductive network is the addition of carbon to create a composite electrode. An alternative approach is the electrochemically induced formation of conductive reaction products where the electrochemically generated materials are in intimate contact with the active material contributing to effective connection of each active particle. Furthermore, this study probes silver vanadium oxide (Ag 2 V 4 O 11 , SVO), carbon monofluoride (CF x ), and hybrid SVO/CF x electrodes in lithium batteries. Ex situ XRD identifies Ag 0 as a reduction product from SVO and LiF from CF x that can be followed as a function of depth-of-discharge (DOD). Spatially-resolved operando energy dispersive x-ray diffraction reveals that the presence of SVO alleviates reaction heterogeneity in the electrodes which are electron transfer limited in the absence of sufficient Ag 0 . Synchrotron X-ray tomography on discharged cathodes reveals the distribution of silver particles where the particles are more closely spaced near the current collector indicating multiple nucleation sites for their formation. Finally, operando isothermal microcalorimetry is used to determine the heat dissipation of the parent and hybrid battery types. Using material enthalpy potentials, we determine the current distribution between the two active materials for the discharging hybrid cathode adding further insight to the diffraction analysis. Taken together, these results provide a comprehensive understanding of hybrid SVO/CF x cathodes and give guidance on optimal compositions that balance power and energy density considerations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Crystal structure of calcium L-5-methyltetrahydrofolate trihydrate type I, C 20 H 23 N 7 O 6 Ca(H 2 O) 3

The crystal structure of L-5-methyltetrahydrofolate calcium trihydrate has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional techniques. Calcium levomefolate trihydrate crystallizes in space group P2 1 2 1 2 1 (#19) with a = 7.1706(6), b = 6.5371(5), c = 53.8357(41) Å, V = 2523.58(26) Å 3 , and Z = 4. The structure is characterized by alternating hydrophobic and hydrophilic layers along the c-axis. The Ca cations are 7-coordinate, and share edges to form chains along the b-axis. Each of the water molecules acts as a donor in two hydrogen bonds. The coordinated water molecule makes two strong intermolecular O–H∙∙∙O hydrogen bonds to carboxyl and carbonyl groups. The two zeolitic water molecules form weaker hydrogen bonds, to carbonyl O atoms, ring N atoms, and aromatic C atoms. Several N–H∙∙∙O/N hydrogen bonds, as well as C–H∙∙∙O hydrogen bonds, also contribute to the lattice energy.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Solvent oligomerization pathways facilitated by electrolyte additives during solid-electrolyte interphase formation

The solid–electrolyte interphase (SEI) layer formation is known to play an important role in determining the lifetime of lithium-ion batteries. A thin, stable SEI layer is linked to overall improved battery performance and longevity, however, the factors and mechanisms that lead to optimal SEI morphology and composition are not well understood. Inclusion of electrolyte additives (fluoroethylene carbonate, FEC; and vinylene carbonate, VC) is often necessary for improving SEI characteristics. To understand how these electrolyte additives impact SEI formation, we employed molecular dynamics (MD) and density functional theory (DFT) simulations to study the reaction networks and oligomerization pathways, respectively, for three systems containing ethylene carbonate (EC), a lithium ion, and FEC or VC. MD simulations suggest radical oligomerization pathways analogous to traditional oligomerization with nucleophilic alkoxide species via SN1 reaction mechanisms. Both S N 1 and S N 2 mechanisms were studied for all three systems using DFT. Oligomerization reactions were studied with both a standard alkoxide species and a ring-opened EC radical as the nucleophiles and EC, FEC, and VC as the electrophiles. For all cases, FEC and VC exhibited lower free energy barriers and more stable adducts when compared with EC. We conclude that one of the role of additives is to modify the oligomerization process of EC by introducing branching points (FEC) or termination points (VC).

25 ENERGY STORAGE↗
DOE OSTI2026

Observation of Transition from Rate Law to Butler–Volmer Controlled Water Oxidation Kinetics on Hematite Photoanodes

Despite its central role in photoelectrochemical (PEC) water splitting, the mechanistic pathway of water oxidation on metal oxides remains unresolved, with population-based and Butler–Volmer (BV) models offering distinct views on how surface valence band holes drive the reaction. Here, we bring together these two perspectives by combining operando photoinduced absorption (PIA) spectroscopy with photocurrent analyses on α-Fe 2 O 3 (hematite) photoanodes as a function of light intensity. We find a crossover from population-controlled, rate law water oxidation at low hole densities to a BV-like, potential driven regime at high densities, triggered by band edge unpinning once surface M–OH species are fully oxidized, and excess holes accumulate without compensation. This mechanistic transition unifies competing models of interfacial charge transfer and reveals design principles for optimizing water oxidation in metal oxide photoelectrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A microfluidic study of transient flow states in permeable media using fluorescent particle image velocimetry

Velocity fields in flow in permeable media are of great importance to many subsurface processes such as geologic storage of CO 2 , oil and gas extraction, and geothermal systems. Steady-state flow is characterized by velocity fields that do not change significantly over time. The flow field transitions to a new steady state once it experiences a disturbance such as a change in flow rate or in pressure gradient. This transition is often assumed to be instantaneous, which justifies the expression of constitutive relations as functions of instantaneous phase saturations. This work examines the evolution of velocity fields in a surrogate quasi-2D permeable medium using a microfluidic device, a microscopy system, and a high-speed camera. Tracer particles are injected into the medium along with DI water. The evolution of the velocity field is examined by tracing these particles in the captured images using the standard high-density particle image velocimetry algorithm founded on cross-correlation. The results suggest that the transition between steady states for an incompressible fluid takes a finite and non-negligible amount of time that is independent of the magnitude of the change in pressure gradient. The existence of transient states and the nature of the response during these states are readily interpreted by the principle of least action where flow gradually establishes an optimal configuration such that energy dissipation is 2 minimized. The findings provide evidence against the applicability of the assumption that flowing phases relax instantaneously to their steady states and, hence, against the accuracy of the classical multiphase extension of Darcy's law.

42 ENGINEERING↗
DOE OSTI2020

Prediction of Structures and Atomization Energies of Coinage Metals, (M)n, n < 20: Extrapolation of Normalized Clustering Energies to Predict the Cohesive Energy

The geometries of the group 11 coinage metals (n = 2-20) were optimized to determine the lowest energy isomers for each cluster size, singlets for even numbers and doublets for odd numbers. For copper and silver, 2-D (planar) geometries were favored up to n = 6. For gold, 2D (planar) geometries were favored up to n = 13. Normalized clustering energies were plotted as a function of cluster size (n-1/3, for n = 4-20) with various DFT functionals and the CCSD(T)-F12b method and were extrapolated to predict the bulk cohesive energy. In the case of copper and silver, there is excellent agreement between the cohesive energies predicted at the CCSD(T)-F12b level of theory and the experimental values. For gold, the CCSD(T)-F12b values needed to be corrected for spin-orbit relativistic effects to obtain good agreement with experiment. Electronic properties including the HOMO-LUMO gaps for the even clusters and the spin densities for the odd clusters were calculated. The lowest gap is predicted to occur for n = 16 where the HOMO and LUMO are very similar in shape.

Persuad, Rudradatt R.↗