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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Discrete generative diffusion models without stochastic differential equations: A tensor network approach

Diffusion models (DMs) are a class of generative machine learning methods that sample a target distribution by transforming samples of a trivial (often Gaussian) distribution using a learned stochastic differential equation. In standard DMs, this is done by learning a “score function” that reverses the effect of adding diffusive noise to the distribution of interest. Here we consider the generalisation of DMs to lattice systems with discrete degrees of freedom, and where noise is added via Markov chain jump dynamics. We show how to use tensor networks (TNs) to efficiently define and sample such “discrete diffusion models” (DDMs) without explicitly having to solve a stochastic differential equation. We show the following: (i) by parametrising the data and evolution operators as TNs, the denoising dynamics can be represented exactly; (ii) the auto-regressive nature of TNs allows to generate samples efficiently and without bias; (iii) for sampling Boltzmann-like distributions, TNs allow to construct an efficient learning scheme that integrates well with Monte Carlo. We illustrate this approach to study the equilibrium of two models with non-trivial thermodynamics, the d = 1 constrained Fredkin chain and the d = 2 Ising model. Published by the American Physical Society 2025

Causer, Luke (ORCID:0000000194243473)↗
DOE OSTI2020

Studies of charm quark diffusion inside jets using PbPb and pp collisions at $\sqrt{s_\mathrm{NN}} =$ 5.02 TeV

The first study of charm quark diffusion with respect to the jet axis in heavy ion collisions is presented. The measurement is performed using jets with $p^{jet}_T > 60 GeV / c$ and $D^0$ mesons with $p^D_T > 4 GeV / c$ in lead-lead (Pb-Pb) and proton-proton ($pp$) collisions at a nucleon-nucleon center-of-mass energy of $\sqrt{s_{NN}} = 5.02 TeV$, recorded by the CMS detector at the LHC. The radial distribution of $D^0$ mesons with respect to the jet axis is sensitive to the production mechanisms of the meson, as well as to the energy loss and diffusion processes undergone by its parent parton inside the strongly interacting medium produced in Pb-Pb collisions. When compared to Monte Carlo event generators, the radial distribution in $pp$ collisions is found to be well described by pythia, while the slope of the distribution predicted by sherpa is steeper than that of the data. In Pb-Pb collisions, compared to the $pp$ results, the $D^0$ meson distribution for $4 < p^D_T < 20 GeV / c$ hints at a larger distance on average with respect to the jet axis, reflecting a diffusion of charm quarks in the medium created in heavy ion collisions. At higher $p^D_T$, the Pb-Pb and $pp$ radial distributions are found to be similar.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Regularizing INR with Diffusion Prior for Self-Supervised 3D Reconstruction OF Neutron Computed Tomography Data

Recently, generative diffusion priors have made huge strides as inverse problem solvers, including the ability to be adapted for inference on out-of-distribution data. Concurrently, implicit neural representations (INRs) have emerged as fast and lightweight inverse imaging solvers that are amenable to hybrid approaches that combine learned priors with traditional inverse problem formulations. In this paper, we present a diffusive computed tomography (CT) inversion framework for regularizing INRs called Diffusive INR (DINR), designed to enable high-quality reconstruction from sparse-view neutron CT. Pretrained purely on synthetic data, DINR is evaluated on simulated and experimentally obtained observations of concrete microstructures, where traditional reconstruction methods suffer substantial degradation when the number of views is reduced. Our approach delivers superior performance, reduces reconstruction artifacts, and achieves gains in PSNR and SSIM, enabling accurate micro-structural characterization even under extreme data limitations compared to state-of-the-art sparse-view reconstruction techniques.

Hossain, Maliha [ORNL]↗
DOE OSTI2021

Dopant Diffusion Control for Improved Tandem Cells Grown by D-HVPE

GaInP top cell current-density presently limits the performance of HVPE-grown two-junction devices, in large part due to unwanted dopant diffusion. Here, we institute mitigation strategies to lower the diffusion of dopants from both the front contact and back surface field. Successful application of these strategies resulted in a short-circuit current density of 12.1 mA/cm 2 in a GaInP/GaAs cell, an improvement of 0.9 mA/cm2 over our previous best cell. The reduced Se diffusion results in a thinner unpassivated emitter, which can lead to higher series resistance. Despite the increased resistance we obtained an efficiency increase from 23.7% to 24.8%.

42 ENGINEERING↗
DOE OSTI2025

Importance Sampling Model-Based Diffusion for Trajectory Optimization

Trajectory optimization for robotic systems remains a challenging problem. This is especially true for robotic systems featuring nonlinear dynamics and many degrees of freedom. Data-based or model-free diffusion has recently been popularized in the fields of artificial intelligence and trajectory optimization. Model-Based Diffusion provides a data-free method of trajectory optimization, trained at runtime on a system dynamics model, suitable for high-dimensional models. This paper examines how importance sampling can enhance the performance of Model-Based Diffusion for trajectory optimization. Here, we quantify the benefits of importance sampling across three long horizon planning tasks. These results show as much as a 13x improvement in sample efficiency depending on environment and optimization parameters.

Golembeski, Seth [Georgia Institute of Technology,↗
DOE OSTI2022

Coupled diffusion-deformation-damage model for polymers used in hydrogen infrastructure

The soft materials used in the infrastructure of hydrogen storage and distribution systems are vulnerable because exposure to high-pressure hydrogen can lead to mechanical damage and property degradation. Some materials, such as polymers, can undergo mechanical failure due to a phenomenon wherein hydrogen gas diffuses through the polymer chains and occupies preexisting cavities or voids inside the polymer material. If the hydrogen gas pressure is reduced more quickly than hydrogen can diffuse back out of the polymer which is necessary for some applications, the trapped hydrogen gas instead escapes by rupturing the material, causing surface blistering or permanent damage. In this study, a continuum mechanics-based fully coupled diffusion-deformation model with damage is developed to predict the stress distribution and damage propagation while the polymer undergoes rapid decompression failure. The hyperelastic material model, along with the maximum principal strain failure theory, was chosen for this study as it represents the nonlinear material response with brittle failure observed in uniaxial tensile tests perfectly. EPDM polymer was chosen for this study because of its commercial availability and common use in hydrogen storage and distribution system. It has superior mechanical properties, high and low temperature resistance, and certain compounds work well in hydrogen gas. This work is useful for design engineers to alter the parameters while manufacturing polymer composites to increase their performance in a high-pressure hydrogen environment.

Kulkarni, Shank S.↗
DOE OSTI2024

Persistent enhancement of exciton diffusivity in CsPbBr 3 nanocrystal solids

In semiconductors, exciton or charge carrier diffusivity is typically described as an inherent material property. Here, we show that the transport of excitons among CsPbBr 3 perovskite nanocrystals (NCs) depends markedly on how recently those NCs were occupied by a previous exciton. Using transient photoluminescence microscopy, we observe a striking dependence of the apparent exciton diffusivity on excitation laser power that does not arise from nonlinear exciton-exciton interactions or thermal heating. We interpret our observations with a model in which excitons cause NCs to transition to a long-lived metastable configuration that markedly increases exciton transport. The exciton diffusivity observed here (>0.15 square centimeters per second) is considerably higher than that observed in other NC systems, revealing unusually strong excitonic coupling between NCs. The finding of a persistent enhancement in excitonic coupling may help explain other photophysical behaviors observed in CsPbBr 3 NCs, such as superfluorescence, and inform the design of optoelectronic devices.

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

Mapping structures and dynamics with frequency-correlated diffusion exchange

Understanding molecular motion in diffusion-driven complex environments is critical for designing sustainable materials and improving chemical processes. Here, we introduce a multidimensional nuclear magnetic resonance (NMR) method that captures how molecular populations exchange across different dynamic regimes. By extending the modulated gradient spin-echo technique to include frequency-frequency correlations, our approach reveals diffusion pathways that are otherwise obscured in heterogeneous systems. Implemented on a unilateral NMR magnet, the method eliminates gradient pulsing constraints and accesses dynamics in the kilohertz regime. We apply this technique to swelling and acid-catalyzed deconstruction of cross-linked and linear polymers to observe how structural heterogeneity evolves over time. By linking molecular motion to topology and chemical state, we extract physical metrics such as fractal surface dimensionality and reaction wavefront velocity, properties inaccessible with standard diffusion measurements. This work expands the capabilities of NMR for probing soft matter, with implications for polymer recycling and materials design.

Fricke, Sophia N. [University of California, Berke↗
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 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 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 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 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↗
DOE OSTI2024

Reference Materials for Laser and Xenon Flash Thermal Diffusivity Systems

This report presents the status of current standard reference materials for thermal diffusivity testing. In most thermal properties testing systems, it is common to use standard reference materials to show the reproducibility of the tests and certify the instrument is producing results within expected uncertainty range. The definition of reference materials or standards vary depending on the quality control protocols of the project. For thermal diffusivity, although there were standards available by the National Bureau of Standards (NBS) 40 years ago, there has been no recent NIST standard reference material (SRM). There are only a few sources that produce and provide traceable reference standards for thermal diffusivity. The certificate typically expires in 5 years and only applies to the specific lot of materials. Other reference materials are provided by the testing systems manufacturers. They are mostly well-known reference materials or materials used by the equipment manufacturers with historic data. However, most these reference materials no longer carry valid certificates. Various reference materials will be discussed along with the industry practice when only secondary standards are available.

36 MATERIALS SCIENCE↗