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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Carbon-carbon interactions in warm dense titanium carbide

Encouraged by experimental reports of diamond precipitation in carbon-containing materials under warm dense matter conditions and in shock compression experiments, we examine the behavior of carbon in TiC using density functional theory-molecular dynamics simulations. Two polymorphs of TiC are considered, the ambient-pressure B1 ($Fm$$\overline{3}$$m$) structure in which C-C interactions are prevented by geometric constraints, and a high-pressure Cmcm structure in which C atoms condense into zigzag chains. Chemistry-inspired bonding analyses confirm the covalently bound nature of these chains and further illuminate important interatomic interactions in both structures. Upon melting of B1 TiC, new short-range C-C interactions develop in the liquid, while the pre-existing C-C interactions in Cmcm TiC persist in the liquid. Here, the resulting carbon networks in the melt provide a promising environment for eventual diamond nucleation.

Ab initio molecular dynamics↗
DOE OSTI2021

Post-Newtonian kinetic theory

A kinetic theory for relativistic gases in the presence of gravitational fields is developed in the second post-Newtonian approximation. The corresponding Boltzmann equation is determined from the evolution of the one-particle distribution function with respect to the proper time along the world line of the particle. From the knowledge of the equilibrium Maxwell–Jüttner distribution function in the second post-Newtonian approximation the components of the particle four-flow and energy–momentum tensor are obtained. The Eulerian hydrodynamic equations for the mass density, mass-energy density and momentum density in the second post-Newtonian approximation are determined from the Boltzmann equation. It is shown that the combination of the hydrodynamic equations of mass and mass-energy densities leads to the hydrodynamic equation for the internal energy density in the first post-Newtonian approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Fe doped aluminoborate PKU-1 catalysts for the ketalization of glycerol to solketal: Unveiling the effects of iron composition and boron

An inexpensive Fe doped aluminoborate consisted of 18% Fe in PKU-1 material that exhibits high selectivity of 4-hydroxymethy-2,2-dimethyl-1,3-dioxolane (Solketal, 98.3%), considerable activity (TOF 51.7 h -1 ), and recyclable ability in the ketalization of glycerol to Solketal with acetone at 318 K has been developed. Here our study demonstrated that the structure of Fe (less agglomerated iron species vs. FeO x clusters) can be tuned by changing Fe loading in the PKU-1 material, which correlated well with experimental observations. Furthermore, the surface boron sites were promoted by iron loading and behaved as Lewis-acid sites to facilitate the reaction process of glycerol ketalization, while the Solketal selectivity was closely related with the structure of iron species in PKU-1, which was proved by kinetic studies, density function theory (DFT) calculations, and a series of spectroscopy studies. This investigation demonstrates that the surface B sites can play important roles in the reaction instead of being spectators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The effects of vanadium substitution on one-dimensional tunnel structures of cryptomelane: Combined TEM and DFT study

Rational design of energy storage materials requires mechanistic understanding which relies on atomic scale characterization of structure and defects. In this paper we utilize vanadium (V)-substituted one-dimensional cryptomelane as a model material to study structural features critical to electrochemical reversibility of the cathode in lithium-ion batteries. We found the substitution of manganese (Mn) atoms in the tunnel wall with V enhances structural uniformity in the parent KMn 8 O 16 material by inhibiting formation of irregular (2 × 3 and 2 × 1) manganese oxide tunnel structures. Upon lithiation, both transmission electron microscopy (TEM) and density functional theory (DFT) reveal significant structural evolution, eventually resulting in phase separation and formation of highly reduced manganese oxide. During this process, Mn 4+ accepts electrons donated by intercalated Li, while the V 4+ substituent is not electrochemically reduced but acts to stabilize the tunnel framework structure. As a result, the V substituted material shows higher operating voltage and improved electrochemical reversibility. Our results highlight the benefits of V-substitution in cryptomelane, and the significance of integrating characterization with simulation for understanding and developing design principles for lithium ion battery materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Universal machine learning framework for defect predictions in zinc blende semiconductors

Our article introduces a universal predictive framework for point defect formation energies and charge transition levels in a wide chemical space of zinc blende semiconductors and possible impurity atoms selected from across the periodic table. This framework was developed by leveraging high-throughput quantum mechanical simulations benchmarked using some experimental data from the literature, as well as machine learning (ML)-based regressions techniques that map unique materials descriptors to computed defect properties and yield optimized and generalizable models. Furthermore, the power and utility of these models is revealed through quick predictions for thousands of new defects and screening of low-energy impurities, which may tune the equilibrium conductivity in the semiconductor. This work presents, to our knowledge, the largest density functional theory (DFT) dataset of defect properties in semiconductors and the largest DFT+ML-based screening of point defects in semiconductors to date.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Theoretical Assessment of the Transition Between Electron Emission Mechanisms for Nonplanar Diodes

Theoretically and computationally describing the operation of nanodiodes requires characterizing the transitions between multiple electron emission mechanisms for nanodiodes with complicated geometries. This motivates our development of techniques to determine when simplified theories for individual mechanisms suffice compared to more complete, but more computationally expensive, models. Leveraging recent theories that define a canonical gap distance to translate planar theory to nonplanar diodes, we derive the conditions for the transitions among thermal emission, field emission, and space-charge-limited current density (SCLCD) in vacuum and with collisions for non-Cartesian coordinate systems, including spherical, cylindrical, and prolate spheroidal coordinate systems. Particle-in-cell (PIC) simulations of the current density as a function of applied voltage for a tip-to-plate geometry in vacuum agreed qualitatively with the asymptotes for thermal emission at low voltage and SCLCD at higher voltage using the canonical gap distance. As a result, this demonstrates the utility of this approach for guiding system design and suggests future extensions to save simulation time for more realistic geometries that are more computationally expensive.

Conformal mapping↗
DOE OSTI2023

Safe Electrolytes for Batteries

The demand for reliable and safe lithium-ion batteries (LIBs) for electric vehicles (EVs) and energy storage systems (ESS) necessitates the exploration of nonflammable phosphorus-based electrolytes as alternatives to the traditional flammable carbonate-based ones. However, integrating phosphorus-based electrolyte poses challenges, including capacity fading and compatibility issues with graphite material. Here, a high-throughput (HTP) electrochemical characterization method, similar to PH test paper, is introduced to fast screen compatible phosphorus-based electrolyte for use with graphite. Among 1,740 combinations of phosphorus-based electrolytes and graphite materials, 101 promising combinations are identified for further evaluation. These identified phosphorus-based electrolytes and graphite materials are evaluated and optimized in Li/Graphite half-cells and Graphite/LiFePO 4 (LFP) full-cells using commercial-level electrodes. The desolvation energy of a complex with one Li+ and four solvent molecules of phosphate or carbonate is calculated by density functional theory (DFT). Key parameters such as viscosity, ionic conductivity, and flammability of the electrolytes are thoroughly tested and optimized. The modified phosphate-dominant electrolyte (2 M LiFSI TEP/DME/EC (6/2/2, volume ratio) + 5 wt.% VEC + 5 wt.% FEC) demonstrates excellent thermal stability with lithiated graphite and showcases superior cycling performance in the Graphite/LFP full cell, surpassing prior research findings in phosphate-dominant electrolytes. By the rapid HTP screening and identification of compatible electrolyte-graphite combinations, this approach contributes to expediting the development of safer LIBs for EVs and ESS.

25 ENERGY STORAGE↗
DOE OSTI2023

Optimizing 3d spin polarization of CoOOH by in situ Mo doping for efficient oxygen evolution reaction

Transition-metal oxyhydroxides are attractive catalysts for oxygen evolution reactions (OERs). Further studies for developing transition-metal oxyhydroxide catalysts and understanding their catalytic mechanisms will benefit their quick transition to the next catalysts. Herein, Mo-doped CoOOH was designed as a high-performance model electrocatalyst with durability for 20 h at 10 mA cm -2 . Additionally, it had an overpotential of 260 mV (glassy carbon) or 215 mV (nickel foam), which was 78 mV lower than that of IrO 2 (338 mV). In situ, Raman spectroscopy revealed the transformation process of CoOOH. Calculations using the density functional theory showed that during OER, doped Mo increased the spin-up density of states and shrank the spin-down bandgap of the 3d orbits in the reconstructed CoOOH under the electrochemical activation process, which simultaneously optimized the adsorption and electron conduction of oxygen-related intermediates on Co sites and lowered the OER overpotentials. Our research provides new insights into the methodical planning of the creation of transition-metal oxyhydroxide OER catalysts.

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

Convergent Concordant Mode Approach for Molecular Vibrations: CMA-2

The concordant mode approach (CMA) is a promising new scheme for dramatically increasing the system size and level of theory achievable in quantum chemical computations of molecular vibrational frequencies. Here, we achieve advances in the CMA hierarchy by computations targeting CCSD(T)/cc-pVTZ (coupled cluster singles and doubles with perturbative triples using a correlation-consistent polarized-valence triple-ζ basis set) benchmarks within the G2 molecular test set, executing a statistical analysis for 1501 frequencies from 111 compounds and then separately solving the refractory case of pyridine. First, MP2/cc-pVTZ (second-order Møller–Plesset perturbation theory with the same basis set) proves to be an excellent and preferred choice for generating the underlying (Level B) normal modes of the CMA scheme. Utilizing this Level B within the CMA-0A method reproduces the 1501 benchmark frequencies with a mean absolute error (MAE) of only 0.11 cm –1 and an attendant standard deviation of 0.49 cm –1 . Second, a convergent CMA-2 method is constituted that allows efficient computation of higher level (Level A) frequencies to any reasonable accuracy threshold by using only Hartree–Fock (HF) and MP2 or density functional theory (DFT) data to generate ξ parameters, which select the sparse off-diagonal force field elements for explicit evaluation at Level A. When Level B = MP2/cc-pVTZ, a cutoff of ξ = 0.02 provides an average maximum absolute error per molecule of only 0.17 cm –1 by incurring merely a 33% increase in average cost over CMA-0A. This CMA-2 method also eradicates the 4 problematic CMA-0A outliers of pyridine with even less effort (ξ = 0.04, 22% increase). Finally, the newly developed CMA procedures are shown to be highly successful when applied to 1-(1H-pyrrol-3-yl)ethanol, a new test molecule with diverse types of vibration.

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

Influence of Polymorphs and Local Defect Structures on NMR Parameters of Graphite Fluorides

In this study, the role of local molecular structure on calculated 13 C and 19 F NMR chemical shifts for graphite fluoride materials was explored by using gauge-including projector augmented wave (GIPAW) computational methods for different periodic crystal polymorphs and density functional theory (DFT) gauge-including atomic orbital (GIAO) computational methods for individual graphite fluoride platelets, i.e., fluorinated graphene (FG). The impact of stacking sequences, d -spacing, and ring conformations on fully fluorinated graphite fluoride structures was investigated. A range of different defects including Stone–Wales, F and C vacancies, void formation, and F inversion were also evaluated using FG structures. These calculations show that distinct chemical shift signatures exist for many of these polymorphs and defects, therefore providing a basis for spectral assignment and development of models describing the mean local CF structure in disordered graphite fluoride materials.

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

Resistive Switching of Spinel Li 4 Ti 5 O 12 Lithium-Ion Battery Material for Neuromorphic Computing

The rapid rise of AI has exposed significant limitations in conventional Von Neumann computing architecture, particularly in regard to speed and energy efficiency. To address these challenges, researchers are exploring a brain-inspired neuromorphic architecture that mimics biological neural networks, enabling massive parallel processing with reduced power consumption for complex AI computational demands. Recent interest has focused on utilizing battery electrodes and solid electrolyte materials for their resistive switching properties in developing a neuromorphic architecture. These properties are precisely tuned through local- and bulk-level chemical composition modifications via voltage bias stimuli. In this study, we demonstrate fabricating a three-terminal lithium-ion electrochemical transistor based on lithium titanium oxide (Li 4 Ti 5 O 12 ), a popular lithium-ion battery anode material. We deposited and characterized LTO thin films using RF sputtering, demonstrating a 6 orders of magnitude increase in electronic conductivity upon lithiation, with conductivity plateauing after 20% lithiation. Density functional theory calculations revealed transformation from the insulating to conducting state, supported by experimental characterization through X-Ray Photoelectron Spectroscopy (XPS) and Direct Current (DC) polarization analyses. The fabricated transistor consisted of LTO as the channel layer, gold as source/drain terminals, lithium phosphorus oxynitride (LiPON) as the lithium-ion conductor, and copper as the gate terminal. The device exhibited clear hysteresis in transfer characteristics due to lithium insertion/extraction processes. Long-term potentiation (LTP) and long-term depression (LTD) measurements showed an asymmetric ratio of 1.425 and maximum/minimum conductance ratio of 7.83. When implemented in a deep neural network (DNN) for MNIST handwritten digit recognition, the device achieved 92.03% accuracy over 20 training epochs. Detailed transport mechanism analysis revealed the crucial role of oxygen vacancies and interface effects in device operation. Our preliminary findings establish LTO-based lithium-ion electrochemical transistors as promising candidates for energy-efficient neuromorphic computing applications, offering potential solutions to traditional Von Neumann architecture limitations.

25 ENERGY STORAGE↗
DOE OSTI2024

Atomic cluster expansion potential for large scale simulations of hydrocarbons under shock compression

We present an Atomic Cluster Expansion (ACE) machine learned potential developed for high-fidelity atomistic simulations of hydrocarbons, targeting pressures and temperatures near and above supercritical fluid regimes for molecular fluids. A diverse set of stoichiometries were covered in training, including 1:0 (pure carbon), 1:4 (methane), and 1:1 (benzene), and rich bonding environments sampled at supercritical temperatures, hydrogen rich, reactive mixtures where metastable stoichiometries arise, including 1:2 (ethylene) and 1:3 (ethane). A high-fidelity training database was constructed by performing large-scale quantum molecular dynamic simulations [density functional theory (DFT) MD] of diamond, graphite, methane, and benzene. A novel approach to selecting structures from DFT MD is also presented, which allows for the rapid selection of unique DFT MD frames from complex trajectories. Comparisons to DFT and experimental data demonstrate that the presented ACE potential accurately reproduces isotherms, carbon melting curves, radial distribution functions, and shock Hugoniots for carbon and hydrocarbon systems for pressures up to 100 GPa and temperatures up to 6000 K for hydrocarbon systems and up to 9000 K for pure carbon systems. This work delivers a potential that can be used for accurate, large-scale simulations of shocked hydrocarbons and demonstrates a methodology for fitting and validating machine learning interatomic potentials to complex molecular environments, which can be applied to energetic materials in future works.

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

Machine Learning-Assisted Recovery of Delicate Kinetic Information from Transient Reactor Experiments

Identifying active sites and their roles in chemical reaction steps remains a vital challenge in heterogeneous catalysis. Transient experiments offer a unique way to probe active sites and distinguish subtle kinetic features. Although physics-based analysis methods may be well-developed, they can be highly susceptible to experimental noise, and smoothing methods may erase or even distort important features; a smooth curve is not always the best curve. We demonstrate a new workflow for the direct interpretation of intrinsic kinetic information from exit flux curves measured in transient reactor experiments. This workflow contains three artificial neural networks (ANNs), including a noise reducer, a concentration predictor, and a rate predictor to analyze experimental data, followed by the virtual TAP (VTAP) physics-based reactor model and density functional theory (DFT) calculations of adsorption energies on specific sites. We use this workflow to analyze the data from experiments titrating Pt/Al 2 O 3 and Pt/SiO 2 catalysts with carbon monoxide (CO) in the temporal analysis of products (TAP) reactor. Our workflow separates the time-evolving chemical reaction and mass transfer information contained in the TAP pulse response. The existence of strong- and weak-binding sites on the Pt/Al 2 O 3 catalyst is observed in the catalyst titration experiment in the transient reactor. The structures of the strong- and weak-binding sites are then identified by using DFT calculations. We find that the Pt/SiO 2 catalyst has only strong-binding sites, which aligns with the inactive support effect of SiO 2 . We demonstrate how machine learning methods provide unique insights with high-resolution data analysis that cannot be achieved by using state-of-the-art physics-based methods.

Adsorption↗
DOE OSTI2022

How the Bioinspired Fe 2 Mo 6 S 8 Chevrel Breaks Electrocatalytic Nitrogen Reduction Scaling Relations

The nitrogen reduction reaction (NRR) is a renewable alternative to the energy- and CO 2 -intensive Haber–Bosch NH 3 synthesis process but is severely limited by the low activity and selectivity of studied electrocatalysts. The Chevrel phase Fe 2 Mo 6 S 8 has a surface Fe–S–Mo coordination environment that mimics the nitrogenase FeMo-cofactor and was recently shown to provide state-of-the-art activity and selectivity for NRR. Here, we elucidate the previously unknown NRR mechanism on Fe 2 Mo 6 S 8 via grand-canonical density functional theory (GC-DFT) that realistically models solvated and biased surfaces. Fe sites of Fe 2 Mo 6 S 8 selectively stabilize the key *NNH intermediate via a narrow band of free-atom-like surface d-states that selectively hybridize with p-states of *NNH, which results in Fe sites breaking NRR scaling relationships. These sharp d-states arise from an Fe–S bond dissociation during N 2 adsorption that mimics the mechanism of the nitrogenase FeMo-cofactor. Furthermore, we developed a new GC-DFT-based approach for calculating transition states as a function of bias (GC-NEB) and applied it to produce a microkinetic model for NRR at Fe 2 Mo 6 S 8 that predicts high activity and selectivity, in close agreement with experiments. Furthermore, our results suggest new design principles that may identify effective NRR electrocatalysts that minimize the barriers for *N 2 protonation and *NH 3 desorption and that may be broadly applied to the rational discovery of stable, multinary electrocatalysts for other reactions where narrow bands of surface d-states can be tuned to selectively stabilize key reaction intermediates and guide selectivity toward a target product. Furthermore, our results highlight the importance of using GC-DFT and GC-NEB to accurately model electrocatalytic reactions.

10 SYNTHETIC FUELS↗
DOE OSTI2024

Extracting the electronic structure of light elements in bulk materials through a Compton scattering method in the readily accessible hard x-ray regime

Here, our Compton profile measurements of Ti and TiH 2 using readily available hard X-ray radiation at 27.5 keV, detected by both a Hitachi Vortex silicon-drift detector and a high-resolution superconducting transition-edge sensor array, are found to be in excellent accord with state-of-the-art density functional theory based calculations. The spherically averaged difference between the Compton profiles of TiH 2 and Ti is well described by an inverted parabola, supporting an itinerant behavior of the electron gas screening the protons in the Ti matrix. Our experimental approach, validated by two different detectors, extends the applicability of Compton scattering technique to the readily accessible hard x-ray regime (below 30 keV). Our study suggests possibilities for experiments at low-flux bending magnet synchrotron beamlines and paves the way for the development of tabletop Compton experiments with x-ray tubes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Electronic transport, thermal transport, thermal expansion, and magnetization in the strongly correlated metal LaNi⁢O 3

Perovskite structured LaNiO 3 is a strongly correlated metal with intriguing thermal and magnetic properties. The volume dependence of calculated and measured physical properties can add additional critical information to develop a more in-depth understanding of this strongly correlated phenomenon. Taking advantage of recent single crystal LaNiO 3 growth using the floating-zone method, we have measured the thermal expansion, the magnetostriction, and the pressure dependence of the magnetic susceptibility, which then allows derivation of the Grüneisen parameters γ e = $\frac{dlnN(E_F)}{d lnV}$, γ χ = $\frac{dlnχ}{d lnV}$, as well as of electric and thermal transport properties. We simulate the volume dependence of structural and magnetic properties using Density Functional Theory calculations at the Generalized Gradient Approximation level. A large discrepancy between experimental values and calculated ones suggests that strong correlations are likely to be dynamic in nature. This study also provides a side-by-side comparison of measurements in single crystal and polycrystalline samples of LaNiO 3 to elucidate intrinsic materials properties. A broad hump at high temperatures in the temperature dependence of magnetization found in the single crystal sample of LaNiO 3 has been rationalized by a model that includes the influence of electron correlations on the Landau diamagnetism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2002

Structural Fluctuations and Thermophysical Properties of Molten II-VI Compounds

The objectives of the project are to conduct ground-based experimental and theoretical research on the structural fluctuations and thermophysical properties of molten II-VI compounds to enhance the basic understanding of the existing flight experiments in microgravity materials science programs as well as to study the fundamental heterophase fluctuation phenomena in these melts by: 1) conducting neutron scattering analysis and measuring quantitatively the relevant thermophysical properties of the II-VI melts (such as viscosity, electrical conductivity, thermal diffusivity and density) as well as the relaxation characteristics of these properties to advance the understanding of the structural properties and the relaxation phenomena in these melts and 2) performing theoretical analyses on the melt systems to interpret the experimental results. All the facilities required for the experimental measurements have been procured, installed and tested. Thermal diffusivity of molten tellurium has been measured by a laser flash method in the temperature range of 500 C to 900 C. The measured diffusivity as a function of temperature agrees fairly well with published data. However, a relaxation phenomenon, which shows a slow drift of the measured thermal conductivity toward the equilibrium value after cooling of the melt, was observed for the first time. An apparatus based on the transient torque induced by a rotating magnetic field has been developed to determine the viscosity and electrical conductivity of semiconducting liquids. Viscosity measurements on molten tellurium showed a similar relaxation behavior to the measured diffusivity. The density and volume expansion coefficients for pure Te and HgTe melts were measured as a function of temperature using a pycnometric method. A density maximum was found for both melts but no relaxation behavior was observed. Neutron scattering experiments were performed on the HgTe and HgZnTe melts and the results on pair distribution showed better resolution than previously reported. A simple kinetic theory, which contains the formation reactions of Te polymerization that increases the molecular weight, was proposed to interpret the relaxation behavior of HgZnTe viscosity data.

Su, Ching-Hua↗
DOE OSTI2023

From Femtoseconds to Gigaseconds: The SolDeg Project to Analyze and Mitigate the Performance Degradation of a-Si:H/c-Si Heterojunction Solar Cells

We pursued two major projects. In the first, we studied the degradation of a-Si/c-Si Heterojunction cells. We substantially expanded our previously developed SolDeg platform, and incorporated hydrogen into it. We also expanded the capabilities of SolDeg by developing a three channel model for a very efficient way to determine long term junction dynamics. The first main result was that we identified hydrogen drifting away from the interface as a key degradation channel. The second was that we developed and proposed the concept of a “reverse silicon density gradient” in the a-Si layer that had the promise of reducing degradation by up to 80%. In the second project, we studied the degradation of TOPCon solar cells. We again identified a key degradation channel, which in these cells was the formation of pinholes across the oxide layer. We then again were able to develop and to propose a way to dramatically reduce degradation by discovering that tuning the hydrogen concentration forms a sharp and deep minimum of the recombination current.

14 SOLAR ENERGY↗