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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Diffusion of cesium in oxidized and unoxidized IG-110 nuclear graphite

Time-release diffusion measurements of cesium have been conducted over the temperature range 1073 K – 1973 K on oxidized and unoxidized IG-110 graphite. Four cesium concentrations were tested to investigate the concentration dependence of the diffusion coefficient. Two levels of oxidation were tested and compared to unoxidized concentration-matched sets to explore the effects of graphite oxidation. Here, the results demonstrate that cesium diffusion coefficient in unoxidized IG-110 graphite is independent of concentration within the range 34 – 163 µg Cs/g graphite . Above this, the effective cesium diffusion coefficient changes with concentration. The diffusion coefficient was increased by a factor of 2–12 in the oxidized set with 7.8% mass loss. These results can be used to aid predictive modeling of cesium diffusion in HTGR cores.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Theoretical examination of nuclear spin diffusion in light-induced spin coherences in photosystem I

Microsecond coherence times are predicted in spin dynamics calculations of a donor–acceptor electron spin pair P + A 1A - created upon light excitation of photosystem I (PSI). The effects of nuclear spin diffusion (NSD) due to the anisotropic protein environment on the predicted coherence times T M are studied. Closely positioned pairs and triples of protons located 5–8 Å from the electron spin are shown to largely control T M . Additionally, knowledge of the crystal structure of PSI allows for spin dynamics calculations where specific cofactors and amino acid residues are removed or replaced and the identification of anisotropic environmental features controlling electronic decoherence. Finally, we show that NSD alone cannot explain the >3× shorter experimentally observed coherence times and suggest that methyl groups at key protein sites may explain this discrepancy.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

First principles density functional theory study of tritium species adsorption on Ni(111) surface and diffusion in nickel-sublayer for tritium storage

The nickel-plated zircaloy-4 is used as a tritium ( 3 H) getter in the tritium-producing burnable absorber rods (TPBARs) to capture 3 H produced in the 6 Li-riched annular γ-LiAlO 2 pellet under neutron irradiation. The experimental data and our previous theoretical results showed that the 3 H species produced from the γ-LiAlO 2 pellet were mainly 3 H 2 and 3 H 2 O. These 3 H species diffuse from the surface of the LiAlO 2 pellet across vacuum to the nickel-plated zircaloy-4 getter and then further diffuse into the getter to chemically form metal hydrides. While a number of studies show that oxygen binds strongly as compared to 3 H on the nickel (Ni) layer, the detailed mechanism of 3 H species absorption and diffusion across the Ni plate and Ni/Zr interface are still unclear. By employing density functional theory calculations, here we explored the 3 H 2 and 3 H 2 O species adsorption and dissociation on the Ni(111) surface and diffusion into the Ni sublayer. Our results indicated that the 3 H 2 and 3 H 2 O dissociate on the Ni(111) surface. The NiO x and Ni(O 3 H) x could be formed in the Ni layer due to the higher oxygen (O) diffusion energy barrier and formation of Ni vacancy defects. The oxygen was found to be retained in the Ni layer from diffusing across the Ni–Zr interface. This was revealed by comparing the diffusion barriers for 3 H with O. 3 H was found to have nearly three times smaller diffusion barrier than for O, making 3 H comparatively easier to diffuse through the Ni layer. In conclusion, the obtained results provide guidelines for experimental measurements on 3 H retention behavior in TPBARs and may open further avenues to explore the impurity effects on 3 H diffusion and storage at the Ni/zircaloy interfaces.

Tafen, De Nyago [National Energy Technology Lab. (↗
DOE OSTI2024

Numerical validation of scaling laws for stratified turbulence

Recent theoretical progress using multiscale asymptotic analysis has revealed various possible regimes of stratified turbulence. Notably, buoyancy transport can either be dominated by advection or diffusion, depending on the effective Péclet number of the flow. Two types of asymptotic models have been proposed, which yield measurably different predictions for the characteristic vertical velocity and length scale of the turbulent eddies in both diffusive and non-diffusive regimes. The first, termed a ‘single-scale model’, is designed to describe flow structures having large horizontal and small vertical scales, while the second, termed a ‘multiscale model’, additionally incorporates flow features with small horizontal scales, and reduces to the single-scale model in their absence. By comparing predicted vertical velocity scaling laws with direct numerical simulation data, we show that the multiscale model correctly captures the properties of strongly stratified turbulence within regions dominated by small-scale isotropic motions, whose volume fraction decreases as the stratification increases. Meanwhile its single-scale reduction accurately describes the more orderly, layer-like, quiescent flow outside those regions.

Mechanics↗
DOE OSTI2023

Evaluation of Tungsten—Steel Solid-State Bonding: Options and the Role of CALPHAD to Screen Diffusion Bonding Interlayers

Critical aspects of innovative design in engineering disciplines like infrastructure, transportation, and medical applications require the joining of dissimilar materials. This study investigates the literature on solid-state bonding techniques, with a particular focus on diffusion bonding, as an effective method for establishing engineering bonds. Welding and brazing, while widely used, may pose challenges when joining materials with large differences in melting temperature and can lead to mechanical property degradation. In contrast, diffusion bonding offers a lower temperature process that relies on solid-state interactions to develop bond strength. The joining of tungsten and steel, especially for fusion reactors, presents a unique challenge due to the significant disparity in melting temperatures and the propensity to form brittle intermetallics. Here, diffusion characteristics of tungsten–steel interfaces are examined and the influence of bonding parameters on mechanical properties are investigated. Additionally, CALPHAD modeling is employed to explore joining parameters, thermal stability, and diffusion kinetics. The insights from this research can be extended to join numerous dissimilar materials for specific applications such as aerospace, automobile industry, power plants, etc., enabling advanced and robust design with high efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Techniques for improved statistical convergence in quantification of eddy diffusivity moments

While recent approaches, such as the macroscopic forcing method (MFM) or Green's function-based approaches, can be used to compute Reynolds-averaged Navier-Stokes closure operators using forced direct numerical simulations, MFM can also be used to directly compute moments of the effective nonlocal and anisotropic eddy diffusivities. The low-order spatial and temporal moments contain limited information about the eddy diffusivity but are often sufficient for quantification and modeling of nonlocal and anisotropic effects. However, when using MFM to compute eddy diffusivity moments, the statistical convergence can be slow for higher-order moments. In this work, we demonstrate that using the same direct numerical simulation (DNS) for all forced MFM simulations improves statistical convergence of the eddy diffusivity moments. We present its implementation in conjunction with a decomposition method that handles the MFM forcing semianalytically and allows for consistent boundary condition treatment, which we develop for both scalar and momentum transport. We demonstrate that for a two-dimensional Rayleigh-Taylor instability case study, using the same DNS for all forced MFM simulations results in convergence with 𝒪⁡(100) simulations rather than 𝒪⁡(1000) simulations. In conclusion, we then demonstrate the impacts of improved convergence on the quantification of the eddy diffusivity.

general physics↗
DOE OSTI2025

Low-energy pathways lead to self-healing defects in CsPbBr 3

Self-regulation of free charge carriers in perovskites via Schottky defect formation has been posited as the origin of the well-known defect-tolerance of metal halide perovskite materials. Understanding the mechanisms of self-regulation promises to lead to the fabrication of better performing solar cell materials with higher efficiencies. We investigate many such mechanisms here for CsPbBr 3 , a popular representative of a more commercially viable all-inorganic metal halide perovskite. We investigate different atomic-level mechanisms and pathways of the diffusion and recombination of neutral and charged interstitials and vacancies (Schottky pairs) in CsPbBr 3 . We use nudged elastic band calculations and ab initio-derived pseudopotentials within quantum ESPRESSO to determine energies of formation and migration and hence the activation energies for these defects. While halide vacancies are known to exhibit low formation energies, the migration of interstitials is less studied. Our calculations uncover interstitial defect pathways capable of producing an activation energy at, or below, the single experimental value of 0.53 eV observed for the slow, temperature-dependent recovery of light-induced conductivity in bulk CsPbBr 3 . Our work reveals the existence of a low-energy diffusion pathway involving a concerted “domino effect” of interstitials, with the net result that interstitials can diffuse more readily over longer distances than expected. This observation suggests that defect self-healing can be promoted if the “domino effect” strategy can be engaged.

14 SOLAR ENERGY↗
DOE OSTI2025

First-principles elucidation of the effects of Al-doping on Li-ion diffusion in LiCoO 2

Al-doped garnet Li 7 La 3 Zr 2 O 12 solid-electrolyte and LiCoO 2 cathode are promising choices as catholyte materials in all solid-state Li batteries, however, interdiffusion of Al is commonly evident during high-temperature processing and electrochemical cycling. Furthermore, to address the impact of Al interdiffusion on Li + transport properties in LiCoO 2 , we carried out a systematic evaluation of Al doping on Li + diffusion barriers in LiCoO 2 using first-principles based methods. Following the monovacancy diffusion mechanism, Al-doping (primarily at the Co site) is found to improve Li diffusion kinetics in the LiCoO 2 lattice due to favorable CoO 6 octahedral distortion experienced at the transition states. However, when considering the previously established dominant divacancy diffusion mechanism, slower Li diffusion is generally expected. In addition, a broad variation of Li diffusion barriers is observed upon Al doping, which suggests the system may suffer from non-uniform Li incorporation and diffusion that adversely affects its rate capacity during cycling. In summary, this work highlights, for the rational design of catholyte of all solid-state batteries, special attention may need to be paid to address the potential impact of non-intentional doping induced during processing on the overall electrochemical performance of the catholyte.

Al-doped LiCoO2↗
DOE OSTI2023

Learning effective stochastic differential equations from microscopic simulations: Linking stochastic numerics to deep learning

We identify effective stochastic differential equations (SDEs) for coarse observables of fine-grained particle- or agent-based simulations; these SDEs then provide useful coarse surrogate models of the fine scale dynamics. We approximate the drift and diffusivity functions in these effective SDEs through neural networks, which can be thought of as effective stochastic ResNets. The loss function is inspired by, and embodies, the structure of established stochastic numerical integrators (here, Euler–Maruyama and Milstein); our approximations can thus benefit from backward error analysis of these underlying numerical schemes. They also lend themselves naturally to “physics-informed” gray-box identification when approximate coarse models, such as mean field equations, are available. Existing numerical integration schemes for Langevin-type equations and for stochastic partial differential equations can also be used for training; we demonstrate this on a stochastically forced oscillator and the stochastic wave equation. Our approach does not require long trajectories, works on scattered snapshot data, and is designed to naturally handle different time steps per snapshot. We consider both the case where the coarse collective observables are known in advance, as well as the case where they must be found in a data-driven manner.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

High-resolution planar electron beam induced current in bulk diodes using high-energy electrons

Understanding the impact of high-energy electron radiation on device characteristics remains critical for the expanding use of semiconductor electronics in space-borne applications and other radiation harsh environments. Here in this paper, we report on in situ measurements of high-energy electron radiation effects on the hole diffusion length in low threading dislocation density homoepitaxial bulk n-GaN Schottky diodes using electron beam induced current (EBIC) in high-voltage scanning electron microscopy mode. Despite the large interaction volume in this system, quantitative EBIC imaging is possible due to the sustained collimation of the incident electron beam. This approach enables direct measurement of electron radiation effects without having to thin the specimen. Using a combination of experimental EBIC measurements and Monte Carlo simulations of electron trajectories, we determine a hole diffusion length of 264 ± 11 nm for n-GaN. Irradiation with 200 kV electron beam with an accumulated dose of 24 × 10 16 electrons cm -2 led to an approximate 35% decrease in the minority carrier diffusion length.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Reduced Artifact Approach for Determining Diffusion Coefficients in Time-Resolved Microscopy

Ultrafast microscopy methods traditionally assume a Gaussian profile to extract excited state diffusivities from transport measurements. Although this fitting method recovers accurate diffusion coefficients when the point spread function is well-represented by a Gaussian, even minor spatial aberrations introduced by the imaging system cause significant errors in the determined value. To provide a more accurate measure of excited state transport in nano- and microscale materials systems, in this work an alternative analysis protocol is proposed that numerically convolves the Green’s function solution to the diffusion equation with the experimentally measured point spread function. In contrast to the Gaussian fitting approach, the numerical convolution is shown to be robust against artifacts caused by nonideal point spread functions. Furthermore, the numerical convolution approach is highly effective at resolving anisotropic diffusion in modeled data.

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

Hydrogen Diffusion in Slit Pores: Role of Temperature, Pressure, Confinement, and Roughness

Diffusion of hydrogen (H 2 ) is important to understand the leakage risk and transport behavior for H 2 geologic storage. We applied molecular dynamics simulations to investigate the influencing factors of H2 diffusion in the slit pores of calcite, hematite, and quartz, owing to their abundance. It is revealed that the H2 self-diffusion coefficient increases with the temperature, regardless of the type of pore minerals. The diffusion of H 2 in the 20 nm slit pores falls into the bulk diffusion regime when the pressure is 10 MPa. The self-diffusion of H 2 decreases with pressure in all three types of slit pores, following a power law model with the exponents ranging from -0.825 to -0.964. Furthermore, the impact of confinement on H 2 diffusion is more pronounced for the slit pores with stronger interactions with H 2 -like calcite. The role of surface roughness in H 2 diffusion depends on the slit aperture. The rough surface enhances H 2 diffusion in the larger slit pores due to the enlarged effective pore space, whereas it weakens H 2 diffusion in the small slit pores due to stronger adsorption. These findings will fill the knowledge gap on the coupling effect of different factors influencing H 2 diffusion.

08 HYDROGEN↗
DOE OSTI2023

Automated Symbolic Upscaling: 1. Model Generation for Extended Applicability Regimes

Abstract In porous media theory, upscaling techniques are fundamental to deriving rigorous Darcy‐scale models for flow and reactive transport in subsurface systems. Due to limitations in classical techniques, a number of ad hoc approaches have been proposed to address physical regimes in which reactive time scales are similar to, or faster than, diffusive time scales. In Part 1 of this two part series, we present a strategy for expanding the applicability of classical homogenization theory by generalizing the assumed closure form. We detail the implementation of this strategy on two reactive mass transport problems with moderately reactive physics. The strategy produces nontrivial homogenized models with emergent terms and effective parameters that couple reactive, diffusive, and advective transport. The differences in equation forms between the macroscopic and pore‐scale descriptions advise caution to further studies where the forms of macroscopic equations are assumed, as opposed to rigorously derived. Numerical validation is provided for each problem to show that the error estimates of homogenization theory are satisfied, and to justify the implemented strategy. In Part 2, the presented strategy is automated using symbolic computing to expedite its implementation.

Pietrzyk, Kyle↗
DOE OSTI2023

Screen printable copper pastes for silicon solar cells

The current work demonstrates the successful metallization of a PERC silicon solar cell with screen-printable copper (Cu) paste that is sintered at elevated temperature in air atmosphere. The existing state of the art in Silicon (Si) solar cell metallization is silver (Ag) paste; Cu cost is 1/100th the cost of Ag and has a comparable conductivity. However, Cu undergoes rapid oxidation at elevated temperatures and the high diffusion of Cu into Si restricts its usage in the metallization of silicon solar cells. In this paper, a Cu paste containing a proprietary mixture of antioxidant additives and diffusion inhibitors was used to make front gridlines on PERC cells. The Cu-printed cells were fired in an IR belt furnace with a peak temperature of 576°C in air atmosphere. The solar cells discussed here reached an efficiency of 19%, which is 88% of the efficiency measured for a commercial Ag-printed cell. The working devices were further characterized using STEM, EDX, ToF-SIMS and long-term suns-V oc studies demonstrating an absence of Cu diffusion. Furthermore, thermally stressing the Cu-printed solar cells yielded a reduction of less than 1.9% of the initial pseudo fill factor (pFF) after 1000 hours at 200°C. Here, the shunt resistance of cells monitored over 3 years remained within 2.5% of its initial value, which demonstrates the effectiveness of the Cu diffusion barrier.

14 SOLAR ENERGY↗
DOE OSTI2025

Nonlocal, Pattern-Aware Response and Feedback Framework for Regional Climate Response

We devise a pattern-aware feedback framework for representing the forced climate response using a suite of Green’s function experiments with solar radiation perturbations. By considering the column energy balance, a comprehensive linear response function (CLRF) for important climate variables and feedback quantities such as moist static energy, sea surface temperature, albedo, cloud optical depth, and lapse rate is learned from Green’s function data. The learned CLRF delineates the effects of the energy diffusion in both the ocean and atmosphere and the pattern-aware feedbacks from the aforementioned radiatively active processes. The CLRF can then be decomposed into forcing–response mode pairs, which are in turn used to construct a reduced-order model describing the dominant dynamics of climate responses. These mode pairs capture nonlocal effects and teleconnections in the climate and thus make the reduced-order model apt for capturing regional features of climate response. A key observation is that the CLRF captures the polar-amplified response as the most excitable mode of the climate system, and this mode is explainable in the data-learned pattern-aware feedback framework. The reduced-order model can be used for predicting the response for a given forcing and for reconstructing the forcing from a given response; we demonstrate these capabilities for multiple independent forcing scenarios.

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