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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Designing Ta C Virtual Substrates for Vertical Al x Ga 1 − x N Power Electronics Devices

Power electronics are critical for a sustainable energy future, playing a key role in electrification and integration of renewable energy sources into the grid. Advances in ultrawide band gap materials are needed to handle higher powers in smaller form factors while reducing electrical and thermal losses. High Al content Al x Ga 1 − x N is theoretically capable of meeting these demands, but its impact in power electronics has been severely restricted by a lack of substrates that can satisfy conductivity, lattice matching, and/or thermal expansion requirements. We demonstrate that electrically conductive Ta C can be used as a virtual substrate for Al x Ga 1 − x N heteroepitaxy. Scaleably sputtered Ta C grown on Al 2 O 3 , followed by high-temperature face-to-face annealing, produces a thin film Ta C template with an effective hexagonal lattice constant matched to Al 0.70 Ga 0.30 N . Annealing of the Ta C promotes recrystallization, significantly improving crystallinity and reducing crystalline defects from as-deposited columnar grains to a step-and-terrace surface morphology, enabling the subsequent growth of high-quality Al 0.70 Ga 0.30 N by molecular beam epitaxy. X-ray diffraction and scanning transmission electron microscopy confirm that the Al x Ga 1 − x N layer is heteroepitaxially aligned, strain-free, and lattice-matched, transitioning abruptly from Ta C to Al x Ga 1 − x N without intermediate phases. These results demonstrate Ta C virtual substrates as electrically conductive, lattice-matched, and thermally compatible templates for vertical Al x Ga 1 − x N devices that can meet the growing power needs of a sustainable energy future. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2026

Efficient Probabilistic Visualization of Local Divergence of 2D Vector Fields with Independent Gaussian Uncertainty

This work focuses on visualizing uncertainty of local divergence of two-dimensional vector fields. Divergence is one of the fundamental attributes of fluid flows, as it can help domain scientists analyze potential positions of sources (positive divergence) and sinks (negative divergence) in the flow. However, uncertainty inherent in vector field data can lead to erroneous divergence computations, adversely impacting downstream analysis. While Monte Carlo (MC) sampling is a classical approach for estimating divergence uncertainty, it suffers from slow convergence and poor scalability with increasing data size and sample counts. Thus, we present a two-fold contribution that tackles the challenges of slow convergence and limited scalability of the MC approach. (1) We derive a closed-form approach for highly efficient and accurate uncertainty visualization of local divergence, assuming independently Gaussian-distributed vector uncertainties. (2) We further integrate our approach into Viskores, a platform-portable parallel library, to accelerate uncertainty visualization. In our results, we demonstrate significantly enhanced efficiency and accuracy of our serial analytical (speed-up up to 1946×) and parallel Viskores (speed-up up to 19698×) algorithms over the classical serial MC approach. We also demonstrate qualitative improvements of our probabilistic divergence visualizations over traditional mean-field visualization, which disregards uncertainty. We validate the accuracy and efficiency of our methods on wind forecast and ocean simulation datasets.

Ouermi, Timbwaoga [University of Utah]↗
DOE OSTI2024

From oxide epitaxy to freestanding membranes: Opportunities and challenges

Motivated by the growing demand to integrate functional oxides with dissimilar materials, numerous studies have been undertaken to detach a functional oxide film from its original substrate, effectively forming a membrane, which can then be affixed to the desired host material. This review article is centered on the synthesis of functional oxide membranes, encompassing various approaches to their synthesis, exfoliation, and transfer techniques. First, we explore the characteristics of thin-film growth techniques with emphasis on molecular beam epitaxy. We then examine the fundamental principles and pivotal factors underlying three key approaches of creating membranes: (i) chemical lift-off, (ii) the two-dimensional layer–assisted lift-off, and (iii) spalling. We review the methods of exfoliation and transfer for each approach. Last, we provide an outlook into the future of oxide membranes, highlighting their applications and emerging properties.

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

Collisional effects on resonant particles in quasilinear theory

A careful examination of the effects of collisions on resonant wave-particle interactions leads to an alternate interpretation and deeper understanding of the quasilinear operator originally formulated by Kennel and Engelmann (Phys. Fluids vol. 9, 1966, pp. 2377- 2388) for collisionless, magnetized plasmas, and widely used to model radio frequency heating and current drive. The resonant and nearly resonant particles are particularly sensitive to collisions that pitch angle scatter them out of and into resonance. As a result, the resonant particle-wave interactions occur in the center of a narrow collisional boundary when the collision frequency nu is very small compared to the wave frequency omega. The diffusive nature of the pitch angle scattering combined with the wave-particle resonance condition enhances the collision frequency by (omega/nu)2/3 >>1, resulting in an effective resonant particle collision time of tau_int ~ (nu /omega)2/3 nu <<1/ nu . A rigorous collisional boundary layer analysis generalizes the standard quasilinear operator to a form that is fully consistent with Kennel-Englemann, but allows replacing the delta function appearing in the diffusivity with a simple integral (having the appropriate delta function limit) retaining the new physics associated with the narrow boundary layer, while preserving the entropy production principle. The limitations of the collisional boundary layer treatment are also estimated, and indicate that substantial departures from Maxwellian are not permitted.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Moment-based adaptive time integration for thermal radiation transport

Here, in this paper we develop a framework for moment-based adaptive time integration of deterministic multifrequency thermal radiation transpot (TRT). We generalize our recent semi-implicit-explicit (IMEX) integration framework for gray TRT to multifrequency TRT, and also introduce a semi-implicit variation that facilitates higher-order integration of TRT, where each stage is implicit in all components except opacities. To appeal to the broad literature on adaptivity with Runge–Kutta methods, we derive new embedded methods for four asymptotic preserving IMEX Runge–Kutta schemes we have found to be robust in our previous work on TRT and radiation hydrodynamics. We then use a moment-based high-order-low-order representation of the transport equations. Due to the high dimensionality, memory is always a concern in simulating TRT. We form error estimates and adaptivity in time purely based on temperature and radiation energy, for a trivial overhead in computational cost and memory usage compared with the base second order integrators. We then test the adaptivity in time on the tophat and Larsen problem, demonstrating the ability of the adaptive algorithm to naturally vary the timestep across 4–5 orders of magnitude, ranging from the dynamical timescales of the streaming regime to the thick diffusion limit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Allometric Trophic Networks From Individuals to Socio-Ecosystems: Consumer–Resource Theory of the Ecological Elephant in the Room

A well-known parable is that of the blind men studying an elephant each of which assert the elephant is the part they first hold in their hands, e.g., “rope!” says the tail holder while the leg holder asserts “tree!” The various subdisciplines of ecology appear similar in that we each engage in our enthusiastic but at least somewhat myopic study with remarkably limited agreement or even discussion about the overall system which we all study. Allometric trophic network (ATN) theory offers a path out of this dilemma by integrating across scales, taxa, habitats and organizational levels from physiology to ecosystems based on consumer-resource interactions among co-existing organisms. The network architecture and the metabolic and behavioral processes that determine the structure and dynamics of these interactions form the first principles of ATN theory, which in turn provides a synthetic overview and powerfully predictive framework for ecology from organisms to ecosystems. Beyond ecology, ATN theory also synthesizes eco-evolutionary and socio-ecological research still largely based on consumer-resource mechanisms but respectively integrated with different processes including natural selection and market mechanisms. This paper briefly describes foundations, advances, and future directions of ATN theory including predicting an ecosystem’s phenotype from its community’s genotype in order to accelerate more predictive and unified understanding of the complex systems studied by ecologists and other environmental scientists.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Integration of machine learning with neutron scattering for the Hamiltonian tuning of spin ice under pressure

Quantum materials research requires co-design of theory with experiments and involves demanding simulations and the analysis of vast quantities of data, usually including pattern recognition and clustering. Artificial intelligence is a natural route to optimise these processes and bring theory and experiments together. Here, we propose a scheme that integrates machine learning with high-performance simulations and scattering measurements, covering the pipeline of typical neutron experiments. Our approach uses nonlinear autoencoders trained on realistic simulations along with a fast surrogate for the calculation of scattering in the form of a generative model. We demonstrate this approach in a highly frustrated magnet, Dy 2 Ti 2 O 7 , using machine learning predictions to guide the neutron scattering experiment under hydrostatic pressure, extract material parameters and construct a phase diagram. Our scheme provides a comprehensive set of capabilities that allows direct integration of theory along with automated data processing and provides on a rapid timescale direct insight into a challenging condensed matter system.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Integrability and Symmetries of Classical Geometries

This research project had two major objectives: advancement in constructing quantum theory of gravity and analytical understanding of strongly--coupled systems. The project contributed to advancing quantum theory of gravity by studying dynamics of black holes. A comprehensive analysis of excitations of rotating black holes in arbitrary dimensions has been performed, all solutions of Maxwell's equations as well as their generalizations to arbitrary p-forms in such backgrounds have been constructed, and a significant progress towards extension of these results to gravitational waves has been made. The project also advanced theoretical understanding of strongly-coupled theories by analyzing properties of exactly-solvable (integrable) models. A new method for solving dynamical equations for various fields in a large class of backgrounds without isometries has been developed, and this technique was used to extract spectra of supergravity modes in several integrable string theories. The analytical structure of large classes of integrable string theories has also been analyzed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Adsorptive behavior of poly (vinylidene fluoride) membranes for the recovery of lignin-derived hydrophobic deep eutectic solvents

Abstract Recently, membrane technology has gained significant traction as an energy-efficient alternative to traditional thermal processes for solvent recovery. Deep eutectic solvents (DESs) have emerged as sustainable alternatives to conventional organic solvents, yet a systematic methodology for selecting compatible membrane materials for their recovery remains underdeveloped. This study established a predictive framework for membrane material selection in hydrophobic DES applications using Hansen Solubility Parameters (HSP) with inverted criteria targeting materials with relative energy difference (RED) values greater than 1.0. Flat sheet membranes were fabricated via the non-solvent induced phase separation (NIPS) technique. Four NIPS fabricated polymer membranes were evaluated: polysulfone, cellulose acetate, polyvinylidene fluoride (PVDF) fabricated with polyethylene glycol (PEG) as a pore-forming agent, and polybenzimidazole (PBI). The HSP approach successfully predicted membrane-solvent compatibility, with polysulfone (RED = 0.6) and cellulose acetate (RED = 0.9) dissolving completely within 24 h, while PVDF (RED = 1.9) and PBI (RED = 1.1) maintained structural integrity throughout a 7-day exposure period. Furthermore, PVDF demonstrated superior performance with minimal weight gain (3.0%), hydrophobic surface characteristics (122° water contact angle), and enhanced mechanical properties following DES exposure. Comprehensive chemical and morphological characterization confirmed PVDF’s chemical stability and revealed a surface-selective interaction mechanism involving simultaneous PEG (pore-forming agent) extraction and DES component adsorption. Adsorption kinetics followed pseudo-first-order behavior with reversible characteristics, best described by the Temkin isotherm model (R² = 0.9987). PVDF membranes-maintained separation functionality with average lignin rejection (75.2 ± 7.69%) and demonstrated filtration permeability of 2.0 ± 0.34 LMH/bar. This methodology provides a rational approach for membrane selection in emerging solvent systems, contributing to the advancement of sustainable separation technologies for DES-based biomass processing applications.

Science & Technology - Other Topics↗
DOE OSTI2025

Quantum chaos, integrability, and late times in the Krylov basis

Quantum chaotic systems are conjectured to display a spectrum whose fine-grained features (gaps and correlations) are well described by random matrix theory (RMT). We propose and develop a complementary version of this conjecture: quantum chaotic systems display a Lanczos spectrum whose local means and covariances are well described by RMT. To support this proposal, we first demonstrate its validity in examples of chaotic and integrable systems. We then show that for Haar-random initial states in RMTs the mean and covariance of the Lanczos spectrum suffice to produce the full long-time behavior of general survival probabilities including the spectral form factor, as well as the spread complexity. In addition, for initial states with continuous overlap with energy eigenstates, we analytically find the long-time averages of the probabilities of Krylov basis elements in terms of the mean Lanczos spectrum. This analysis suggests a notion of eigenstate complexity, the statistics of which differentiate integrable systems and classes of quantum chaos. Lastly, we clarify the relation between spread complexity and the universality classes of RMT by exploring various values of the Dyson index and Poisson distributed spectra.

Combinatorics↗
DOE OSTI2020

Integrable deformation of $\mathbb{C}$P n and generalised Kähler geometry

We build on the results of [1] for generalised frame fields on generalised quotient spaces and study integrable deformations for CP n . In particular we show how, when the target space of the Principal Chiral Model is a complex projective space, a two-parameter deformation can be introduced in principle. The second parameter can however be removed via a diffeomorphism, which we construct explicitly, in accordance with the results stemming from a thorough integrability analysis we carry out. We also elucidate how the deformed target space can be seen as an instance of generalised Kähler, or equivalently bi-Hermitian, geometry. In this respect, we find the generic form of the pure spinors for CP n and the explicit expression for the generalised Kähler potential for n = 1, 2.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Cross-scale modeling and experimental integration for advancing cathode electrolyte interphase studies in high energy density lithium-ion batteries

Electrochemical interfaces are critical to the performance and durability of lithium-ion batteries (LIBs). The solid electrode-electrolyte interphase (SEI and CEI) structures that form during cycling can passivate reactive surfaces, ensuring safe operation, but also may contribute to performance degradation. Understanding the microscopic factors influencing interphase formation, growth, and evolution is essential for balanced battery design. While significant research has focused on the anode-electrolyte interphase (SEI), the cathode-electrolyte interphase (CEI) remains less explored, despite its importance in high-voltage and advanced battery technologies. Challenges in conducting in-situ or operando experiments arise from the occluded nature of these interfaces and the long timescales involved, often leading to biased interpretations. A validated multi-scale, multi-physics modeling approach, integrated with advanced characterization techniques, can effectively elucidate the intrinsic stability of electrolyte and cathode surfaces, the impact of chemical heterogeneity, and the role of microstructural features on CEI performance. In conclusion, this article reviews current modeling and simulation strategies for studying CEI in advanced LIBs and highlights opportunities for future methodological advancements and experimental integration.

Cathode-electrolyte interphase↗
DOE OSTI2020

Adjusting the pH of a pretreatment solution using carbon dioxide useful for integrating saccharification and fermentation

The present invention provides for a method of fermenting or saccharifying a biomass comprising: (a) (i) contacting a biomass comprising a polysaccharide, and an ionic liquid (IL) to form a first solution, or (ii) providing the first solution comprising the biomass and the IL, (b) contacting the first solution and carbon dioxide such that the first solution results in a lower pH, (c) introducing (i) an enzyme capable of enzymatically to breakdown at least one bond in the polysaccharide or a breakdown product of the polysaccharide, and/or (ii) a microorganism that capable of producing the enzyme and/or fermenting the polysaccharide or a breakdown product of the polysaccharide, such that the polysaccharide is at least partially broken down and the first solution is transformed into a second solution.

Sun, Jian↗
DOE OSTI2021

Maximum bound principle preserving integrating factor Runge–Kutta methods for semilinear parabolic equations

A large class of semilinear parabolic equations satisfy the maximum bound principle (MBP) in the sense that the time-dependent solution preserves for any time a uniform pointwise bound imposed by its initial and boundary conditions. Here, the MBP plays a crucial role in understanding the physical meaning and the well-posedness of the mathematical model. Investigation on numerical algorithms with preservation of the MBP has attracted increasingly attentions in recent years, especially for the temporal discretizations, since the violation of MBP may lead to nonphysical solutions or even blow-ups of the algorithms. In this paper, we study high-order MBP-preserving time integration schemes by means of the integrating factor Runge-Kutta (IFRK) method. Beginning with the space-discrete system of semilinear parabolic equations, we present the IFRK method in general form and derive the sufficient conditions for the method to preserve the MBP. In particular, we show that the classic four-stage, fourth-order IFRK scheme is MBP preserving for some typical semilinear systems although not strong stability preserving, which can be instantly applied to the Allen-Cahn type of equations. To our best knowledge, this is the first time to present a fourth-order linear numerical method preserving the MBP. In addition, convergence of these numerical schemes is proved theoretically and verified numerically, as well as their efficiency by simulations of 2D and 3D long-time evolutional behaviors. Numerical experiments are also carried out for a model which is not a typical gradient flow as the Allen-Cahn type of equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

On the quenching of star formation in observed and simulated central galaxies: evidence for the role of integrated AGN feedback

ABSTRACT In this paper, we investigate how massive central galaxies cease their star formation by comparing theoretical predictions from cosmological simulations: EAGLE, Illustris, and IllustrisTNG with observations of the local Universe from the Sloan Digital Sky Survey (SDSS). Our machine learning (ML) classification reveals supermassive black hole mass (MBH) as the most predictive parameter in determining whether a galaxy is star forming or quenched at redshift z = 0 in all three simulations. This predicted consequence of active galactic nucleus (AGN) quenching is reflected in the observations, where it is true for a range of indirect estimates of MBH via proxies as well as its dynamical measurements. Our partial correlation analysis shows that other galactic parameters lose their strong association with quiescence, once their correlations with MBH are accounted for. In simulations, we demonstrate that it is the integrated power output of the AGN, rather than its instantaneous activity, which causes galaxies to quench. Finally, we analyse the change in molecular gas content of galaxies from star-forming to passive populations. We find that both gas fractions (fgas) and star formation efficiencies (SFEs) decrease upon transition to quiescence in the observations but SFE is more predictive than fgas in the ML passive/star-forming classification. These trends in the SDSS are most closely recovered in IllustrisTNG and are in direct contrast with the predictions made by Illustris. We conclude that a viable AGN feedback prescription can be achieved by a combination of preventative feedback and turbulence injection which together quench star formation in central galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Probing configurational disorder in ZnGeN 2 using cluster-based Monte Carlo

ZnGeN 2 is sought as a semiconductor with comparable lattice constant to GaN and tunable band gap for integration in optoelectronic devices. Configurational disorder on the cation sublattice of ZnGeN 2 can strongly modify the electronic structure compared to the ordered material, and both ordered and disordered forms of ZnGeN 2 are candidates for light-emitting diodes and other emitters. The nonisovalent character of the disordered species (Zn 2+ and Ge 4+ ) subjects the cation ordering to strong short-range order effects. To model these effects, we use Monte Carlo (MC) simulations utilizing a cluster expansion to approximate formation enthalpy. Representative disordered configurations in 1024-atom supercells are relaxed in density functional theory calculations. From the MC structures, we extract a short-range order parameter (the N-cation coordination motif), and two long-range order parameters (Bragg-Williams and stretching parameters), and examine their correlations. We perform a thermodynamic integration to determine the mixing entropy and free energy. ZnGeN 2 exhibits a first-order phase transition with pronounced discontinuities in enthalpy and entropy, as well as in the structural order parameters. We discuss the relationship between the effective temperature used in the MC simulation and the growth temperatures in experiment in relation to the crossover from the nonequilibrium to the equilibrium growth regime. This work expands on current models of site disorder in ZnGeN 2 and provides atomic structure models with a systematic variation of the degree of cation disorder.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

String-based parametrization of nucleon GPDs at any skewness: A comparison to lattice QCD

We introduce a string-based parametrization for nucleon quark and gluon generalized parton distributions (GPDs) valid at all skewness values. The conformal moments of the GPDs are expressed as sums of the spin-j nucleon A-form factor and the skewness-dependent spin-j nucleon D-form factor. This representation, which fulfills the polynomiality condition (due to Lorentz invariance) and does not rely on model-specific assumptions, is derived from t-channel string exchanges in anti-de Sitter spaces. The spin-j nucleon D-form factor is closely related to the spin-j nucleon A-form factor. We use the Mellin moments from empirical parton distributions to model the spin-j nucleon A-form factors. Using only five Regge slope parameters, fixed from the electromagnetic and gravitational form factors, our string-based parametrization generates accurate singlet, nonsinglet, isovector, and flavor-separated nucleon quark GPDs, along with symmetric nucleon gluon GPDs from their Mellin-Barnes integral representations. Our isovector nucleon quark GPD is in agreement with existing lattice data. Our string-based parametrization should facilitate the empirical extraction and global analysis of nucleon GPDs in exclusive processes, bypassing the deconvolution challenge.

Electron-ion collisions↗
DOE OSTI2024

Comparisons Between Resolved Star Formation Rate and Gas Tracers in the Strongly Lensed Galaxy SDSS J0901+1814 at Cosmic Noon

We report new radio observations of SDSS J090122.37+181432.3, a strongly lensed star-forming galaxy at $z=2.26$. We image 1.4 GHz (L-band) and 3 GHz (S-band) continuum using the VLA and 1.2 mm (band 6) continuum with ALMA, in addition to the CO(7-6) and CI(${\rm ^3P_2\rightarrow ^3\!P_1}$) lines, all at $\lesssim1.^{\prime\prime}7$ resolution. Based on the VLA integrated flux densities, we decompose the radio spectrum into its free-free (FF) and non-thermal components. The infrared-radio correlation (IRRC) parameter $q_{\rm TIR}=2.65_{-0.31}^{+0.24}$ is consistent with expectations for star forming galaxies. We obtain radio continuum-derived SFRs that are free of dust extinction, finding $\rm {620}_{-220}^{+280}\,M_\odot\,yr^{-1}$, $\rm {230}_{-160}^{+570}\,M_\odot\,yr^{-1}$, and $\rm {280}_{-120}^{+460}\,M_\odot\,yr^{-1}$ from the FF emission, non-thermal emission, and when accounting for both emission processes, respectively, in agreement with previous results. We estimate the gas mass from the CI(${\rm ^3P_2\rightarrow ^3\!P_1}$) line as $M_{\rm gas}=(1.2\pm0.2)\times10^{11}\,M_\odot$, which is consistent with prior CO(1-0)-derived gas masses. Using our new IR and radio continuum data to map the SFR, we assess the dependence of the Schmidt-Kennicutt relation on choices of SFR and gas tracer for $\sim{\rm kpc}$ scales. The different SFR tracers yield different slopes, with the IR being the steepest, potentially due to highly obscured star formation in J0901. The radio continuum maps have the lowest slopes and overall fidelity for mapping the SFR, despite producing consistent total SFRs. We also find that the Schmidt-Kennicutt relation slope is flattest when using CO(7-6) or CI(${\rm ^3P_2\rightarrow ^3\!P_1}$) to trace gas mass, suggesting that those transitions are not suitable for tracing the bulk molecular gas in galaxies like J0901.

79 ASTRONOMY AND ASTROPHYSICS↗