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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Diffusion Blurring of GaAs Quantum Wells Grown at Low Temperature

The processes of the diffusion blurring of a periodic system of GaAs quantum wells separated by AlGaAs barriers are studied by photoluminescence spectroscopy. The system is grown by molecular-beam epitaxy at a low temperature (200°C) and additionally doped with Sb and P isovalent impurities. Postgrowth annealing at the temperature 750°C for 30 min induces an increase in the energy corresponding to the photoluminescence peak of the e1–hh1 exciton state in quantum wells because of blurring of the epitaxial GaAs/AlGaAs interfaces due to enhanced Al–Ga interdiffusion in the cation sublattice. For the Al concentration profile defined by linear diffusion into quantum wells, the Schrödinger equation for electrons and holes is solved. It is found that the experimentally observed energy position of the photoluminescence peak corresponds to the Al–Ga interdiffusion length 3.4 nm and to the effective diffusion coefficient 6.3 × 10{sup –17} cm{sup 2} s{sup –1} at the temperature 750°C. This value is found to be close to the corresponding value for GaAs quantum wells grown at low temperatures without additional doping with Sb and P impurities. From the results obtained in the study, it is possible to conclude that enhanced As–Sb and As–P interdiffusion in the anion sublattice only slightly influences the processes of Al–Ga interdiffusion in the cation sublattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

A Domain Decomposition Model Reduction Method for Linear Convection-Diffusion Equations with Random Coefficients

We developed a domain decomposition model reduction method for linear steady- state convection-diffusion equations with random coefficients. Of particular interest to this effort are the diffusion equation with random diffusivity and the convection-dominated transport equation with random velocity. We investigated two types of random fields, i.e., colored noises and discrete white noises, both of which can lead to high-dimensional parametric dependence in practice. The motivation is to exploit domain decomposition to reduce the parametric dimension of local problems in subdomains, such that an entire parametric map can be approximated with a small number of expensive partial differential equation (PDE) simulations. The new method combines domain decomposition with model reduction and sparse polynomial approximation, so as to simultaneously handle the high dimensionality and irregular behavior of the PDEs under consideration. Here, the advantages of our method lie in three aspects: (i) online-offline decomposition, i.e., the online cost is independent of the size of the triangle mesh; (ii) sparse approximation of operators involving nonaffine high-dimensional random fields; (iii) an effective strategy to capture irregular behaviors, e.g., sharp transitions of the PDE solutions. Two numerical examples are provided to demonstrate the advantageous performance of our method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Investigating Liquid Water Transport in Different Pore Structure of Gas Diffusion Layers for PEMFC Using Lattice Boltzmann Method

Proton exchange membrane fuel cells (PEMFC) require a gas diffusion layer (GDL) to aid in the transport of liquid fuel to the catalyst layer. In this work, direct modeling using the Lattice Boltzmann Method (LBM) was applied to X-ray CT scans of four different carbon gas diffusion layers to understand the mass transport properties through the samples. Three injection orientations were used to study local saturation levels, water evolution through the sample, and mass transport behavior at breakthrough conditions. The LBM, combined with computational fluid dynamic modeling techniques, can accurately predict liquid saturation at the macro and micro scale, which provides more insight into the mass transport phenomena through the GDL. The change of pore structure and orientation in both the in-plane and through-plane determines the path that liquid water must take, which could aid or impact PEMFC performance. The outcomes from this work will also benefit any research that needs knowledge of internal mass transport qualities of gas diffusion media.

Sepe, M.↗
DOE OSTI2020

Bridging Scales to Model Reactive Diffusive Transport in Porous Media

Published by ECS. Two novel scale-bridging algorithms to model reaction-diffusion transport in porous media are presented. The algorithms are based on direct numerical simulations and couple the information of a micro-scale model, which accounts for the large field of view provided by micro X-ray computed tomography (X-ray CT), and a nano-scale model, which locally resolves transport in the fine structure extracted from nano X-ray CT. The micro-scale model is discretized in the through-plane direction into a 1D grid, where effective properties and internal boundaries are determined based on the results from the nano-scale model. The validated algorithms are used to examine transport of oxygen in precious group metal-free electrodes considering both zero- and first-order kinetics. Unlike conventional methods, the results show that the effective diffusivity is not a passive property but increases in regions where the reaction-rate coefficient is large. The proposed algorithms account for the multiscale coupling of reaction-diffusion transport and material microstructure, thus improving the predictions compared to conventional methods.

42 ENGINEERING↗
DOE OSTI2019

Secondary Pore Network Design Optimization Analytical Diffusion Model for Lithium Ion Battery

Fast ion transport along the electrode thickness is required for Lithium ion battery (LIB) to sustain continuous high-rate discharge or charge currents, which is a desired feature for the fast charging of electric vehicle batteries. Advance in LIB electrode manufacturing allows to control, to a certain extent, the electrode microstructure architecture in order to improve the macroscopic performances of these devices. For instance, several groups have experimentally tested architectures tailored specifically to increase the through plane ionic diffusion in regards for fast charge application by adding channels or groove-like large pores oriented along the electrode thickness. These voids do not replace the existing pores of the electrode microstructure but consist in a second, coarser, pore network, called the secondary pore network (SPN). The model quantifies the impact of SPN on ionic diffusion with a composite electrode through a simple analytical approach, considering various pore channel geometries and comparing to standard electrodes with identical gravimetric and identical volumetric specific theoretical capacity. The goal is to find optimal SPN design parameters according to three optimization objectives aiming to balance the improved overall through-plane, thanks to the coarse aligned channels, and the degraded in-plane diffusion, due to the porous matrix densification required to maintain gravimetric and volumetric specific theoretical capacity. The analytical model must be considered as a pre-screening tool to quickly investigate large design space, that can be refined later with more complex electrochemical CPU-expensive numerical models.

Usseglio Viretta, Francois↗
DOE OSTI2023

DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction

Limited-Angle Computed Tomography (LACT) is a non-destructive evaluation technique used in a variety of applications ranging from security to medicine. The limited angle coverage in LACT is often a dominant source of severe artifacts in the reconstructed images, making it a challenging inverse problem. We present DOLCE, a new deep model-based framework for LACT that uses a conditional diffusion model as an image prior. Diffusion models are a recent class of deep generative models that are relatively easy to train due to their implementation as image denoisers. DOLCE can form high-quality images from severely under-sampled data by integrating data-consistency updates with the sampling updates of a diffusion model, which is conditioned on the transformed limited-angle data. We show through extensive experimentation on several challenging real LACT datasets that, the same pre-trained DOLCE model achieves the SOTA performance on drastically different types of images. Additionally, we show that, unlike standard LACT reconstruction methods, DOLCE naturally enables the quantification of the reconstruction uncertainty by generating multiple samples consistent with the measured data.

Kim, Hyojin↗
DOE OSTI2021

Revealing momentum-dependent electron–phonon and phonon–phonon coupling in complex materials with ultrafast electron diffuse scattering

Abstract Despite their fundamental role in determining many important properties of materials, detailed momentum-dependent information on the strength of electron–phonon and phonon–phonon coupling across the entire Brillouin zone has remained elusive. Ultrafast electron diffuse scattering (UEDS) is a recently developed technique that is making a significant contribution to these questions. Here, we describe both the UEDS methodology and the information content of ultrafast, photoinduced changes in phonon-diffuse scattering from single-crystal materials. We present results obtained from Ni, WSe 2 , and TiSe 2 , materials that are characterized by a complex interplay between electronic (charge, spin) and lattice degrees of freedom. We demonstrate the power of this technique by unraveling carrier–phonon and phonon–phonon interactions in both momentum and time and following nonequilibrium phonon dynamics in detail on ultrafast time scales. By combining ab initio calculations with ultrafast diffuse electron scattering, insights into electronic and magnetic dynamics that impact UEDS indirectly can also be obtained. Graphic Abstract

Dürr, Hermann A. (ORCID:0000000196808730)↗
DOE OSTI2018

Optimization of Diffuser (Pre-Scatterer) Configurations for Slow Extraction Loss Reduction at Electrostatic Septa

Uncontrolled beam loss at the electrostatic septum is a performance limit for several existing or planned high power hadron accelerators delivering slow-extracted spills to fixed targets. A passive diffuser, or pre-scatterer, in a suitable configuration has been shown to reduce such beamloss significantly, with the actual gain factor depending on the parameters and details of the extraction process and hardware. In this paper, the optimization of diffuser configurations is investigated for a range of beam energies and extraction conditions, and the sensitivity to the available parameters explored via simulation results. The advantages and limitations of the diffuser are discussed and conclusions drawn concerning the specific case studies of the 8 GeV Fermilab debuncher ring and 400 GeV CERN SPS.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Thermophysical Property Measurements: Improved Density, Viscosity and Thermal Diffusivity Methods

The technical bases and methods developed at Argonne to measure thermophysical properties of molten salt mixtures are summarized and representative results provided to show the accuracy and precision achieved. Three key measurements addressed in this report are density, viscosity and thermal diffusivity. The densities of two eutectic FLiNaK mixtures were measured at temperatures to approximately 750 °C and the results are compared with literature values. The results are used to show how the effect of salt surface tension is taken into account in the density calculation and how the surface tension for other salt mixtures is being measured. Viscosity measurements of eutectic FLiNaK are shown to illustrate improvements to the measurement method being made to address and minimize the sources of error and uncertainties in the reported values. Thermal diffusivity measurements of FLiNaK are shown to illustrate the measurement method developed at Argonne and the achieved precision. The thermal diffusivity of the graphite used to make the cells that contain the salts during analyses was measured to assess the relative contribution to the response. The improved procedures developed in this work are being applied in property measurements of other salts of interest.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Grain Boundary Diffusion Characterized by KPFM

The nanometer scale characterization technique of Frequency Modulated Kelvin Probe Force Microscopy (FM-KPFM) will be used to assess a preliminary diffusion study on thin metal films that undergo accelerated aging. The KPFM technique provides a relatively easy, non-destructive methodology that does not require high-vacuum facilities to obtain nanometer spatial resolution of surface chemistry changes and will be exercised in an effort to explore its capacity to map surface potential contrast caused by Cu diffusion in a manner that allows for a qualitative assessment of diffusion rate kinetics. Supporting data will be obtained from traditional techniques: AES, XPS and UPS. An aging study was conducted on thin metal test specimens comprised of Ti or Cr/Cu/Au layer thicknesses of 50nm/500nm/500nm up to 4μm respectively. The accelerated aging process, was performed in air at aging temperatures of 60°C, 100°C, and 125°C for aging times of 8 hours, 24 hours, 96 hours (4 days), and 216 hours (9 days). A calibration method was developed using Au, Al and Ni standards to establish precision and repeatability of the KPFM technique. Average CPDs and standard deviations for each metal were found and summarized.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Cu/Al Through Au Diffusion Characterized by KPFM

The nanometer scale characterization technique of Frequency Modulated Kelvin Probe Force Microscopy (FM-KPFM) will be used to assess a diffusion study on thin metal films that undergo accelerated aging. The KPFM technique provides a relatively easy, non-destructive methodology that does not require high-vacuum facilities to obtain nanometer-scale spatial resolution of surface chemistry changes. The KPFM technique will be exercised in an effort to explore its capacity to map surface potential contrast caused by diffusion in a manner that allows for a qualitative assessment of diffusion of Cu or Al through Au. Supporting data will be obtained from traditional techniques: AES, XPS and UPS. An aging study was conducted on thin metal test specimens comprised of 500nm Cu or Al then 500nm Au on Si. The accelerated aging process was performed under inert conditions at aging temperatures of 100°C for Cu/Au film stack and 175°C for Al/Au film stack at aging times of 8 hours, 24 hours, 96 hours (4 days), and 216 hours (9 days).A calibration method was developed using Au, Al and Cu standards to establish precision and repeatability of the KPFM technique. The average Contact Potential Difference (CPD)s and standard deviations for each metal were found and summarized. Averages from surface roughness of the AFM topography images and roughness analysis of KPFM potential images which yield an average CPD of each area of unaged vs aged coupon surfaces were compared and show trends that indicate surface chemistry.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Time-Resolved PIV Measurements of Flow Field at the Exit of a Diffuser Mounted on a Rotating Detonation Combustor

Time-resolved particle image velocimetry at 30 kHz is applied to the exhaust flow field of a RDC system configured with a diffuser geometry and a converging-diverging (CD) nozzle. The RDC is operated with methane fuel and oxygen-enriched air, motivated by power generation applications. The measured flow-field is discretized into axial and non-axial velocity components. Results are shown to characterize the flow-field across a cord length at the exit plane. Instantaneous contours of the two velocity components, and 1D histograms of velocity components, and 2D histograms of total velocity and tilt angle are shown at multiple locations in the flow. Repeatability of the data is evaluated by comparing tests conducted at similar flow rates. Results are presented for a baseline test case, and test cases showing the effect of reactant higher flow rate and CD nozzle geometry. Finally, the results are compared to a previous RDC study without the diffuser to compare the effectiveness of the diffuser and CD nozzle designs in mitigating the flow periodicity at the combustor exit.

particle image velocimetry, pressure gain combusti↗
DOE OSTI2018

Fundamental Studies of Tritium Diffusivity and Formation on the Surfaces of Defective LiAlO 2 Pellets

One of the important components of tritium-producing burnable absorber rods (TPBAR) is the γLiAlO 2 layer used in the form of an annular ceramic pellet enriched with the 6 Li isotope. Within TPBAR architecture, this oxide is located between the zircaloy-4 liner and nickel-plated zircaloy-4 tritium getter. When irradiated in a pressurized water reactor (PWR), the 6 Li pellets absorb neutrons, simulating the nuclear characteristics of a burnable absorber rod, and produce tritium ( 3 H, T). The 3 H specie chemically reacts with the metal getter, leading to the formation of a metal hydride. Accurate analysis of the 3 H transport through the ceramic pellets and the barrier/cladding system is hampered by the lack of fundamental data about the hydrogen isotope solubility and diffusivity. In TPBAR architecture, between the γ-LiAlO 2 pellet and the Ni-plated Zircaloy-4 getter (or liner), there is a gas gap. After 3 H diffuses from bulk γ-LiAlO 2 to its surface, it is possible that different 3 H species (such as T, T 2 , T 2 O, and OT, etc.) are formed on this surface which can then get into the gas gap region. Furthermore, upon recombination and desorption molecular tritium can be formed on the γ-LiAlO 2 surface. Therefore, exploring the formation of 3 H-related species on γ-LiAlO 2 surface becomes very important as an integral part of the study of 3H solubility and diffusivity in the pellets.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Hydrogen Diffusivity Measurements of YH 1.87 Moderator Material with Incoherent Quasielastic Neutron Scattering

Yttrium hydride is an optimal choice of moderator material for thermal neutron spectrum reactors requiring small core volumes. The Transformation Challenge Reactor (TCR) program at Oak Ridge National Laboratory (ORNL) aims to develop an additively manufactured microreactor core by leveraging recent advances in materials, manufacturing, data analytics, and high-fidelity modeling and simulation. Yttrium hydride was selected as the moderator material for TCR due to its high moderating power, which enables the spatially efficient reactor design and thermal stability that is superior when compared with zirconium hydride. Hydrogen desorption from yttrium hydride is expected at elevated temperatures, posing safety and performance concerns. As a lifetime component in advanced reactors, appropriate strategies to mitigate hydrogen release from yttrium hydride over long-term reactor operation are required. Understanding hydrogen mobility in yttrium hydride provides the scientific basis for developing a hydrogen barrier for hydride moderator and predicting the hydrogen redistribution within the material during various operational conditions. This study investigated the hydrogen motion in YH 1.87 as a function of temperature ranging from 200 to 1,173 K using incoherent quasielastic neutron scattering (IQNS) at the Spallation Neutron Source (SNS). The results are presented and discussed in terms of hydrogen self-diffusion coefficients, activation energy for translational hydrogen motion, and hydrogen jump distances. Based on the IQNS data, YH 1.87 is found to be stable at high temperatures with no translational H motion below 1,023 K within the IQNS detection limits. In the temperature range of 1,073–1,173 K, hydrogen diffusivity in YH 1.87 is $D = 4.57 X 10^{⁻3} [m^2/s] exp (⁻\frac{1.73[eV]}{RT}$). The hydrogen concentration’s dependence on hydrogen diffusivity is also discussed in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A New Route to Quantum-Scale Structures through a Novel Enhanced Germanium Diffusion Mechanism

This project sought to develop a fundamental understanding of the mechanisms underlying a newly observed enhanced germanium (Ge) diffusion process in silicon germanium (SiGe) semiconductor nanostructures during thermal oxidation. Using a combination of oxidationdiffusion experiments, high resolution imaging, and theoretical modeling, a model for the enhanced Ge diffusion mechanism was proposed. Additionally, a nanofabrication approach utilizing this enhanced Ge diffusion mechanism was shown to be applicable to arbitrary 3D shapes, leading to the fabrication of stacked silicon quantum dots embedded in SiGe nanopillars. A new wet etch-based method for preparing 3D nanostructures for highresolution imaging free of obscuring material or damage was also developed. These results enable a new method for the controlled and scalable fabrication of on-chip silicon nanostructures with sub-10 nm dimensions needed for next generation microelectronics, including low energy electronics, quantum computing, sensors, and integrated photonics.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Nb3Sn growth on niobium in vapor diffusion process and its application to large RF surface

Nb3Sn-coated SRF cavities can potentially achieve superior performance in terms of quality factor, accelerating gradient, and operating temperature. Tin vapor diffusion process of Nb3Sn coating on Nb is a simple, yet efficacious technique to fabricate Nb3Sn-coated SRF cavities. The process comprises two¬ steps: ?nucleation? followed by ?deposition?. The crucible with Sn/SnCl2 and the substrate at a constant temperature of about 500 °C for several hours is the ?nucleation?; the crucible and the substrate at a constant temperature, typically, above 1000 °C is the ?deposition? step. Using custom-built sample coating chamber, we have coated over a hundred samples to systematically study the vapor diffusion process under varying process conditions and at different stages of the coating process. The surfaces, thus obtained, were investigated with surface studies techniques, such as SEM/EDS, AFM, XPS, SAM, SIMS, EBSD and TEM. Based on the experimental results, we will discuss nucleation and growth of Nb3Sn coating during vapor diffusion process.

Pudasaini, Uttar↗
DOE OSTI2024

Quantification of the Crack Evolution Process by Extracting Relevant Signal Components from Wave Propagation and Diffusive Transport Front Measurements

Wave propagation and diffusive transport phenomena in a geological rock sample undergoing crack evolution process are expected to interact with the mechanical discontinuities in the medium. The measurements of the signals associated with these phenomena can be used to assess and monitor the crack-driven micromechanical alterations in the rock. Different wave/diffusion phenomena, such as sonic propagation, pressure diffusion, and acoustic emission (AE), are sensitive to different elements of the mechanical discontinuities generated during the evolution of the crack clusters from initiation to coalescence. Sonic propagation, AE, and pressure diffusion monitoring have the potential to map the crack evolution because the transmitter-receiver arrays can be designed, arranged and tuned to (1) achieve maximum recovery of the scattered waveforms and travel times, (2) capture the later arrivals and multiple reflections, and (3) illuminate large rock volume. However, the structural/topological complexities of the mechanical discontinuities, complex distribution of the stress fields, complex mechanical alterations in media, and fluid redistribution in the crack system pose serious challenges for the detection and modeling of the crack evolution process (from here on, we will use the term ‘crack evolution process’ to mean that the crack evolution occurred under shallow crustal conditions). For purposes of accurately accounting such complexities and heterogeneities in the absence of reliable physical laws, simulation methods, and signal processing techniques, my early-career research proposal will develop and apply novel data-driven machine learning methods to: (1) extract signal components relevant to the various phases of crack evolution and (2) generate a 2D visual map of the crack evolution process.

58 GEOSCIENCES↗