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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hydrogen Evolution on Restructured B-Rich WB: Metastable Surface States and Isolated Active Sites

Borides have been recently identified to be a class of earth-abundant and low-cost materials that are surprisingly active toward oxidative dehydrogenation and hydrogen evolution reaction (HER) catalysis. Here, we explain from first-principles calculations the HER activity of WB, an industrial material known for its superior physical properties and chemical inertness. We find that, compared to bulk termination, a major surface reconstruction takes place, leading to the off-stoichiometric B-rich surface termination that contains the active sites. The hydrogen adsorbate configurations are further investigated under various adsorbate coverages. Many competing configurations appear to be accessible in reaction conditions, and thus, a grand canonical ensemble is established to describe the catalytic system. A phase diagram of adsorbate coverages is constructed as a function of pH and the applied potential. A complex reaction network is presented based on the ensemble-averaged reaction rates, and the electrocatalytic activities are evaluated under different overpotentials. Here, the major contributors to the activity are found to be a few metastable surface states with a distinct electronic structure that are only accessible at high adsorbate coverages in reaction conditions. In addition, while the activity of the dominant active site is nearly the same as that on the unreconstructed WB, the B-rich formations play an important role of isolating the active sites and preventing the passivation of the surface with H 2 bubble formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Large polaron formation and its effect on electron transport in hybrid perovskites

Many experiments have indicated that a large polaron may be formed in hybrid perovskites, and its existence is proposed to screen the carrier-carrier and carrier-defect scattering, thus contributing to the long lifetime of the carriers. However, a detailed theoretical study of the large polaron and its effect on carrier transport at the atomic level is still lacking. In particular, how strong is the large polaron binding energy? How does its effect compare with the effect of dynamic disorder caused by the A-site molecular rotation? And how does the inorganic sublattice vibration impact the motion of the large polaron? All of these questions are largely unanswered. In this work, using CH3NH3PbI3 as an example, we implement a tight-binding model fitted from density-functional theory to describe the electron large polaron ground state and to understand the large polaron formation and transport at its strong-coupling limit. We find that the formation energy of the large polaron is around -12 meV for the case without dynamic disorder, and -55 meV by including dynamic disorder. By performing the explicit time-dependent wavefunction evolution of the polaron state, together with the rotations of CH 3 NH 3 + and vibrations of the PbI3- sublattice, we studied the diffusion constant and mobility of the large polaron state driven by the dynamic disorder and the sublattice vibration. Two effects of the inorganic sublattice vibrations are found: on one hand, the vibration of the sublattice provides an additional driving force for carrier mobility; on the other hand, the large polaron polarization further localizes the electron, reducing its mobility. Overall, the effect of the large polaron is to slow down the electron mobility by roughly a factor of two. We believe that both dynamic disorder due to rotation of the organic molecule, and large polaron effects induced by the polarization and vibration of the inorganic sublattice, play important roles for the electronic structure and carrier dynamics of the system.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Metal–oxygen decoordination stabilizes anion redox in Li-rich oxides

Reversible high-voltage redox chemistry is an essential component of many electrochemical technologies, from (electro)catalysts to lithium-ion batteries. Oxygen-anion redox has garnered intense interest for such applications, particularly lithium-ion batteries, as it offers substantial redox capacity at more than 4 V versus Li/Li + in a variety of oxide materials. However, oxidation of oxygen is almost universally correlated with irreversible local structural transformations, voltage hysteresis and voltage fade, which currently preclude its widespread use. By comprehensively studying the Li 2-x Ir 1-y Sn y O 3 model system, which exhibits tunable oxidation state and structural evolution with y upon cycling, we reveal here that this structure–redox coupling arises from the local stabilization of short approximately 1.8 Å metal–oxygen π bonds and approximately 1.4 Å O–O dimers during oxygen redox, which occurs in Li 2-x Ir 1-y Sn y O 3 through ligand-to-metal charge transfer. Crucially, formation of these oxidized oxygen species necessitates the decoordination of oxygen to a single covalent bonding partner through formation of vacancies at neighbouring cation sites, driving cation disorder. These insights establish a point-defect explanation for why anion redox often occurs alongside local structural disordering and voltage hysteresis during cycling. Our findings offer an explanation for the unique electrochemical properties of lithium-rich layered oxides, with implications generally for the design of materials employing oxygen redox chemistry.

25 ENERGY STORAGE↗
DOE OSTI2026

Small-𝑥 behavior in QCD from maximal entanglement and conformal invariance

Recent evidence suggests that, at small Bjorken 𝑥, QCD evolution drives the proton into a state of maximal entanglement. If the evolution kernel is assumed to be conformally invariant—as is the case for the Balitsky-Fadin-Kuraev-Lipatov equation—we can describe it by a conformal field theory. Moreover, the central charge 𝑐 of the corresponding conformal field theory emerges as the key parameter governing the 𝑥 dependence of both the entanglement entropy and the structure function. Here we apply the exact Bethe ansatz methods to the quantum spin chain dual to Lipatov’s high energy effective action to extract the central charge of the theory, and find that 𝑐 = 1. This implies the ∼𝑥 −1/3 small 𝑥 behavior for the structure function—the prediction that can be tested at the forthcoming Electron-Ion Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Nonintrusive projection-based reduced order modeling using stable learned differential operators

Nonintrusive projection-based reduced order models (ROMs) are essential for dynamics prediction in multi-query applications where underlying governing equations are known but the access to the source of the underlying full order model (FOM) is unavailable; that is, FOM is a glass-box. This article proposes a learn-then-project approach for nonintrusive model reduction. In the first step of this approach, high-dimensional stable sparse learned differential operators (S-LDOs) are determined using the generated data. In the second step, the ordinary differential equations, comprising these S-LDOs, are used with suitable dimensionality reduction and low-dimensional subspace projection methods to provide equations for the evolution of reduced states. This approach allows easy integration into the existing intrusive ROM framework to enable nonintrusive model reduction while allowing the use of Petrov–Galerkin projections. The applicability of the proposed approach is demonstrated for Galerkin and LSPG projection-based ROMs through four numerical experiments: 1-D scalar advection, 1-D Burgers, 2-D scalar advection and 1-D scalar advection–diffusion–reaction equations. In conclusion, the results indicate that the proposed nonintrusive ROM strategy provides accurate and stable dynamics prediction.

42 ENGINEERING↗
DOE OSTI2021

A Physics-Constrained Deep Learning Model for Simulating Multiphase Flow in 3D Heterogeneous Porous Media

Physics-based simulators for multiphase flow in porous media emulate nonlinear processes with coupled physics, and usually require extensive computational resources for software development, maintenance and simulation execution. As a result, a huge demand exists for fast modeling of coupled processes in a wide range of subsurface applications including geological sequestration, hydrocarbon recovery and geothermal energy extraction. In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3-Dimensional (3D) heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural networks, specifically U-Net with successive contracting and expansive steps, and is coupled with an efficient continuity-based smoother to predict flow responses that need spatial continuity. Furthermore, the transient regions are penalized to steer the training process such that the model can accurately capture flow in these regions. The model takes inputs including properties of porous media, fluid properties and well controls, and predicts the temporal-spatial evolution of the state variables (pressure and saturation). While maintaining the continuity of fluid flow, the 3D spatial domain is decomposed into 2D images for reducing training cost, and the decomposition results in an increased number of training data samples and better training efficiency. Additionally, a surrogate model is separately constructed as a postprocessor to calculate well flow rate based on the predictions of state variables from the deep learning model. We use the example of CO 2 injection into saline aquifers, and apply the physics-constrained deep learning model that is trained from physics-based simulation data and emulates the physics process. The model performs prediction with a speedup of ~ 1400 times compared to physics-based simulations, and the average temporal errors of predicted pressure and saturation plumes are 0.27% and 0.099% respectively. Furthermore, water production rate is efficiently predicted by a surrogate model for well flow rate, with a mean error less than 5%. Therefore, with its unique scheme to cope with the fidelity in fluid flow in porous media, the physics-constrained deep learning model can become an efficient predictive model for computationally demanding inverse problems or other coupled processes.

58 GEOSCIENCES↗
DOE OSTI2024

Data-driven models of nonautonomous systems

Nonautonomous dynamical systems are characterized by time-dependent inputs, which complicates the discovery of predictive models describing the spatiotemporal evolution of the state variables of quantities of interest from their temporal snapshots. When dynamic mode decomposition (DMD) is used to infer a linear model, this difficulty manifests itself in the need to approximate the time-dependent Koopman operators. Our approach is to approximate the original nonautonomous system with a modified system derived via a local parameterization of the time-dependent inputs. The modified system comprises a sequence of local parametric systems, which are subsequently approximated by a parametric surrogate model using the DRIPS (dimension reduction and interpolation in parameter space) framework. The offline step of DRIPS relies on DMD to build a linear surrogate model, endowed with reduced-order bases for the observables mapped from training data. The online step interpolates on suitable manifolds to construct a sequence of iterative parametric surrogate models; the target/test parameter points on these manifolds are specified by a local parameterization of the test time-dependent inputs. Here, we use numerical experimentation to demonstrate the robustness of our method and compare its performance with that of deep neural networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Microturbulence-mediated route for energetic ion transport and Alfvénic mode amplitude oscillations in tokamaks

The new regimes of Alfvén eigenmode (AE) induced fast ion transport in tokamak plasmas are reported, in which microturbulence plays the role of a mediator of fast ion relaxation. Coulomb collisional scattering alone leads to small AE amplitudes and does not reproduce the steady state regimes observed in experiments. We show that in nonlinear regimes the sufficiently large effective pitch angle scattering due to microturbulence can lead to steady state AE amplitude evolution. This indicates a new route for fast ion losses, which is beyond the scenarios described in “Energetic ion transport by microturbulence is insignificant in tokamaks”. As a result, microturbulence can significantly increase the amplitude of AEs in predictive simulations of burning plasma experiments such as ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Nitrogen Vacancies Induce Fatigue in Ferroelectric Al 0.93 B 0.07 N

Wurtzite ferroelectrics (e.g., Al 0.93 B 0.07 N) are being explored for high-temperature and emerging near-, or in-compute, memory architectures due to the material advantages offered by their large remanent polarization and robust chemical stability. Despite these advantages, current Al0.93B0.07N devices do not have sufficient endurance lifetime to meet roadmap targets. To identify the defects responsible for this limited endurance, a combination of electronic measurements and optical spectroscopies characterized the evolution of defect states within Al 0.93 B 0.07 N with cycling. Ultrathin (∼10 nm) metal contacts were used to optically probe regions subject to ferroelectric switching; photoluminescence spectroscopy identified the emergence of a transition near 2.1 eV whose intensity scaled with the non-switching polarization quantified via positive-up negative-down (PUND) measurements. Accompanying thermally stimulated depolarization current (TSDC) and modulus spectroscopy measurements also observed the strengthening of a state near 2.1 eV. The origin of this feature is ascribed to transitions between a nitrogen vacancy and another defect deeper in the bandgap. Recognizing that the impurity concentration is largely fixed, strengthening of this transition indicates an increase in the number of nitrogen vacancies. Switching, therefore, creates vacancies in Al 0.93 B 0.07 N likely due to hot-atom damage induced by the aggressive fields necessary to switch wurtzite materials that ultimately limits endurance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Operando High-Energy-Resolution X-ray Spectroscopy of Evolving Cu Nanoparticle Electrocatalysts for CO 2 Reduction

Advances in electrocatalysis research rely heavily on building a thorough mechanistic understanding of catalyst active sites under realistic operating conditions. Only recently have techniques emerged that enable sensitive spectroscopic data collection to distinguish catalytically relevant surface sites from the underlying bulk material under applied potential in the presence of an electrolyte layer. Here, we demonstrate that operando high-energy-resolution fluorescence detected X-ray absorption spectroscopy (HERFD-XAS) is a powerful spectroscopic method which offers critical surface chemistry insights in CO 2 electroreduction with sub-electronvolt energy resolution using hard X-rays. Combined with the high surface area-to-volume ratio of 5 nm copper nanoparticles, operando HERFD-XAS allows us to observe with clear evidence the breaking of chemical bonds between the ligands and the Cu surface as part of the ligand desorption process occurring under electrochemical potentials relevant for the CO 2 reduction reaction (CO 2 RR). In addition, the dynamic evolution of oxidation state and coordination number throughout the operation of the nanocatalyst was continuously tracked. With these results in hand, undercoordinated metallic copper nanograins are proposed to be the real active sites in the CO 2 RR. In conclusion, this work emphasizes the importance of HERFD-XAS compared to routine XAS in catalyst characterization and mechanism exploration, especially in the complicated electrochemical CO 2 RR.

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

Operando Unveiling of Hydrogen Spillover Mechanisms on Tungsten Oxide Surfaces

Hydrogen spillover is an important process in catalytic hydrogenation reactions, facilitating H 2 activation and modulating surface chemistry of reducible oxide catalysts. This study focuses on the operando unveiling of platinum-induced hydrogen spillover on monoclinic tungsten trioxide (γ-WO 3 ), employing ambient pressure X-ray photoelectron spectroscopy, density functional theory calculations and microkinetic modeling to investigate the dynamic evolution of surface states at varied temperatures. At room temperature, hydrogen spillover results in the formation of W 5+ and hydrogen intermediates (hydroxyl species and adsorbed water), facilitated by Pt metal clusters. With increasing temperature, water desorption, reverse hydrogen spillover and surface-to-bulk diffusion of hydrogen atoms compete with each other, leading initially to reoxidation and then further reduction of W atoms in the near-surface. The combined experimental results and simulations provide a comprehensive understanding of the mechanisms underlying hydrogen interaction with reducible metal oxides, lending insights of relevance to the design of enhanced hydrogenation catalysts.

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

Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders

Abstract Coherent diffraction imaging (CDI) is an advanced non-destructive 3D X-ray imaging technique for measuring a sample’s electron density. The main challenge of CDI is loss of phase information in diffraction intensity measurements, resulting in lengthy iterative reconstruction processes that can return non-unique solutions, which pose challenges for experiments attempting to track dynamic sample evolution through multiple states. As the increased brightness of fourth-generation light sources enables faster sample measurements and drives operando experiments with Bragg CDI, there is a growing need for faster reconstruction techniques that can keep pace. We have developed an adaptive generative autoencoder approach for uniquely tracking a sample’s electron density as it dynamically evolves. Our approach adaptively tunes the low-dimensional latent embedding of a generative autoencoder, enabling a computationally efficient manner to account for time-varying shifting distributions in real-time. Analytic proof of convergence is provided as well as numerical demonstration of sample tracking with noisy measurements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

MHD stability of spherical tokamak equilibria with non-monotonic q-profiles

We use the 3D magnetohydrodynamic (MHD) code M3D-C1 [Jardin et al., Comput. Sci. Discovery 5, 014002 (2012)] to examine the MHD stability and subsequent evolution of NSTX shot 129169. This discharge had a period with a non-monotonic safety factor profile, q (reversed shear), which was terminated by a MHD event that abruptly lowered the central safety factor, q0, and greatly reduced the peakedness of the pressure profile. We show that the equilibrium just before the MHD event occurred was linearly unstable to many pressure-driven infernal modes. Modes with toroidal mode number n≥3 all had rational surfaces very close to the minimum value of q. However, a non-resonant pressure-driven (1, 1) mode was also present, and this dominated the nonlinear evolution. The final state in the simulation, after the MHD activity subsided, had a reduced and flattened pressure profile and a nearly monotonic q-profile, in qualitative agreement with experimental results. The initial state was also unstable to the resistive interchange criteria in the reversed-shear region, but the final state was stable everywhere. The “double tearing mode” (DTM) does not appear to play a role in the MHD activity of this discharge. In Appendix A, we show that in a torus, the DTM is strongly stabilized by pressure, but it is destabilized in cylindrical geometry (which has been the most extensively analyzed in the literature).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Upon the horizon’s verge: Thermal particle creation between and approaching horizons

Abstract Quantum particle creation from spacetime horizons, or accelerating boundaries in the dynamical Casimir effect, can have an equilibrium, or thermal, distribution. Using an accelerating boundary in flat spacetime (moving mirror), we investigate the production of thermal energy flux despite non-equilibrium accelerations, the evolution between equilibrium states, and the ‘interference’ between horizons. In particular, this allows us to give a complete solution to the particle spectrum of the accelerated boundary correspondence with Schwarzschild–de Sitter spacetime.

Astronomy & Astrophysics↗
DOE OSTI2023

Initial study on thermal stability of cold spray tantalum coating irradiated with deuterium for fusion applications

Abstract Removal of neutral hydrogen atoms in the plasma edge reduces the number of charge exchange events and thus, the net energy losses in the plasma, significantly improving performance of fusion devices. Effective control of the residual pressure of hydrogen isotopes (HIs) in the plasma edge may be achieved by utilizing a hydrogen absorbing first wall interface capable of withstanding the harsh fusion environment. In this study, we have investigated tantalum (Ta) coating deposited by cold spray technology on 316L stainless steel substrate as a potential plasma-facing material surface. High fluence low energy deuterium plasma irradiation experiments and subsequent thermal annealing cycles associated with thermal desorption spectrometry (TDS) demonstrated superior structural stability of the Ta coating. TDS experiments revealed the outgassing of deuterium (as measure of its retention) for cold spray Ta coatings to be three times higher than bulk Ta and two orders of magnitude greater than bulk polycrystalline W. X-ray photoelectron spectroscopy revealed evolution of oxidation states upon deuterium irradiation and a partial recovery of the metallic signature of Ta after the thermal treatment at 1100 K.

Physics↗
DOE OSTI2024

Artificial intelligence in cryo-EM protein particle picking: recent advances and remaining challenges

Abstract Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by enabling the determination of high-resolution 3-Dimensional (3D) structures of large biological macromolecules. Protein particle picking, the process of identifying individual protein particles in cryo-EM micrographs for building protein structures, has progressed from manual and template-based methods to sophisticated artificial intelligence (AI)-driven approaches in recent years. This review critically examines the evolution and current state of cryo-EM particle picking methods, with an emphasis on the impact of AI. We conducted a comparative evaluation of popular AI-based particle picking methods, using both general machine learning metrics and specific cryo-EM structure determination metrics. This analysis involved constructing the 3D density map from the picked protein particles and assessing the obtained resolution and particle orientation diversity, underscoring the significant impact of AI on cryo-EM particle picking. Despite the advancements, we also identified key obstacles, such as handling complex micrographs with small proteins. The analysis provides insights into the future development of more sophisticated and fully automated AI methods in cryo-EM particle recognition.

Biochemistry & Molecular Biology↗
DOE OSTI2021

White dwarf and subdwarf stars in the Sloan Digital Sky Survey Data Release 16

ABSTRACT White dwarfs are the end state of the evolution of more than 97 per cent of all stars, and therefore carry information on the structure and evolution of the Galaxy through their luminosity function and initial-to-final mass relation. Examining the new spectra of all white or blue stars in the Sloan Digital Sky Survey Data Release 16, we report the spectral classification of 2410 stars, down to our identification cut-off of signal-to-noise ratio equal to three. We newly identify 1404 DAs, 189 DZs, 103 DCs, 12 DBs, and nine CVs. The remaining objects are a mix of carbon or L stars (dC/L), narrow-lined hydrogen-dominated stars (sdA), dwarf F stars, and P Cyg objects. As white dwarf stars were not targeted by SDSS DR16, the number of new discoveries is much smaller than in previous releases. We also report atmospheric parameters and masses for a subset consisting of 555 new DAs, 10 new DBs, and 85 DZs for spectra with signal-to-noise ratio larger than 10.

Kepler, S. O. (ORCID:0000000274705703)↗
DOE OSTI2019

Supernovae and their host galaxies – VI. Normal Type Ia and 91bg-like supernovae in ellipticals

ABSTRACT We present an analysis of the galactocentric distributions of the ‘normal’ and peculiar ‘91bg-like’ subclasses of 109 supernovae (SNe) Ia, and study the global parameters of their elliptical hosts. The galactocentric distributions of the SN subclasses are consistent with each other and with the radial light distribution of host stellar populations, when excluding bias against central SNe. Among the global parameters, only the distributions of u − r colours and ages are inconsistent significantly between the ellipticals of different SN Ia subclasses: the normal SN hosts are on average bluer/younger than those of 91bg-like SNe. In the colour–mass diagram, the tail of colour distribution of normal SN hosts stretches into the Green Valley – transitional state of galaxy evolution, while the same tail of 91bg-like SN hosts barely reaches that region. Therefore, the bluer/younger ellipticals might have more residual star formation that gives rise to younger ‘prompt’ progenitors, resulting in normal SNe Ia with shorter delay times. The redder and older ellipticals that already exhausted their gas for star formation may produce significantly less normal SNe with shorter delay times, outnumbered by ‘delayed’ 91bg-like events. The host ages (lower age limit of the delay times) of 91bg-like SNe does not extend down to the stellar ages that produce significant u-band fluxes – the 91bg-like events have no prompt progenitors. Our results favour SN Ia progenitor models such as He-ignited violent mergers that have the potential to explain the observed SN/host properties.

Barkhudaryan, L. V.↗