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Results for “diffusion maps”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Informing air–carbon ablation modeling with theoretical calculations of atomic oxygen and nitrogen interacting with carbon surfaces

To understand the gas–surface chemistry above the thermal protection system of a hypersonic vehicle, it is necessary to map out the kinetics of key elementary reaction steps. In this work, extensive periodic density functional theory (DFT) calculations are performed to elucidate the interaction of atomic oxygen and nitrogen with both the basal plane and edge sites of highly oriented pyrolytic graphite (HOPG). Reaction energies and barriers are determined for adsorption, desorption, diffusion, recombination, and several reactions. These DFT results are compared with the most recent finite-rate model for air–carbon ablation. Our DFT results corroborated some of the parameters used in the model but suggest that further refinement may be necessary for others. The calculations reported here will help to establish a predictive kinetic model for the complex reaction network present under hypersonic flight conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The Linkage Between Electro-Chemical Mechanical Instabilities in Battery Materials

Battery chemistry must be diversified to achieve a sustainable energy landscape by effectively utilizing renewable energy sources. Alkali metal-ion, all-solid-state, metal–air batteries, and multivalent batteries offer unique cost, safety, raw material abundance, energy, and power density solutions. However, realizing these “beyond Li-ion batteries” must uncover their working principles and performance & property relationships. In this aspect, mitigating chemo-mechanical instabilities in the structure and surface of the electrodes plays a crucial role in their performance. Unfortunately, the coupling between electrochemical and mechanical interactions is often poorly understood due to a lack of operando characterization. Here, this review article explains the working principles of curvature measurement and digital image correlation for measuring stress and strain generations in battery materials. We provided specific examples of how these operando mechanical measurements shed light on instabilities in alkali metal ion electrodes, solid electrolytes, Li-O 2 batteries, and aqueous Zn-ion batteries. Operando mechanical measurements offer an effective way to map changes in the physical fingerprint of the battery materials, therefore providing crucial information to elucidate instabilities in battery materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Durable High-Power Membrane Electrode Assemblies with Low Pt Loading

Recent progress in developing and implementing Pt-alloy cathode catalysts and thin (10-15 micron) low resistance membranes has enabled high performance state of art (SOA) membrane electrode assembly (MEA) with low Pt loading. However, these high performing MEAs do not meet durability requirements, especially at peak power, because of complex degradation mechanisms that are sensitive to the materials, MEA design, and fuel cell operating strategy. Specifically, power degradation of the cathode occurs via Pt and Co dissolution as well as deterioration of O 2 transport properties. Additionally, thin membranes are subject to failure due to manufacturing defects in the adjacent gas diffusion media and electrodes and the formation of membrane-attacking radical species caused by high gas crossover. In this project led by General Motors LLC (GM), the objective was to enhance the durability of SOA MEA through optimization of operating conditions, instead of new materials development. Along with our project partners, we have mapped the impact of operating conditions on the durability of SOA MEA. Output of the project include a low Pt loading SOA MEA that exceeds Department of Energy (DOE) 2020 target of >1 W/cm 2 at rated power and pathway to achieve >5000 h of durability. Durability studies in the project provide a detailed understanding of failure modes and operating condition sensitivity on cathode and membrane failure, critical for defining operating conditions and hybridization strategies that can guide system controls to maximize low-Pt MEA life. The project also generated and validated degradation models that will provide future research direction, critical for guiding future cycles of automotive MEA development.

08 HYDROGEN↗
DOE OSTI2024

ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a language diffusion model

Through evolution, nature has presented a set of remarkable protein materials, including elastins, silks, keratins and collagens with superior mechanical performances that play crucial roles in mechanobiology. However, going beyond natural designs to discover proteins that meet specified mechanical properties remains challenging. Here, we report a generative model that predicts protein designs to meet complex nonlinear mechanical property-design objectives. Our model leverages deep knowledge on protein sequences from a pretrained protein language model and maps mechanical unfolding responses to create proteins. Via full-atom molecular simulations for direct validation, we demonstrate that the designed proteins are de novo, and fulfill the targeted mechanical properties, including unfolding energy and mechanical strength, as well as the detailed unfolding force-separation curves. Our model offers rapid pathways to explore the enormous mechanobiological protein sequence space unconstrained by biological synthesis, using mechanical features as the target to enable the discovery of protein materials with superior mechanical properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Generative AI models for learning flow maps of stochastic dynamical systems in bounded domains

Simulating stochastic differential equations (SDEs) in bounded domains, presents significant computational challenges due to particle exit phenomena, which requires accurate modeling of interior stochastic dynamics and boundary interactions. Despite the success of machine learning-based methods in learning SDEs, existing learning methods are not applicable to SDEs in bounded domains because they cannot accurately capture the particle exit dynamics. We present a unified hybrid data-driven approach that combines a conditional diffusion model with an exit prediction neural network to capture both interior stochastic dynamics and boundary exit phenomena. Our ML model consists of two major components: a neural network that learns exit probabilities using binary cross-entropy loss with rigorous convergence guarantees, and a training-free diffusion model that generates state transitions for non-exiting particles using closed-form score functions. The two components are integrated through a probabilistic sampling algorithm that determines particle exit at each time step and generates appropriate state transitions. Here, the performance of the proposed approach is demonstrated via three test cases: a one-dimensional simplified problem for theoretical verification, a two-dimensional advection-diffusion problem in a bounded domain, and a three-dimensional problem of interest to magnetically confined fusion plasmas.

Bounded domains↗
DOE OSTI2025

Microstructural Characteristics, Mechanical Properties, and Corrosion Behavior of Field-Assisted Diffusion Welded Alloy 617

This study investigated the microstructural characteristics, mechanical response, and corrosion resistance of Alloy 617 diffusion welded by electric field-assisted sintering (EFAS). The microstructure exhibited good grain boundary (GB) migration across the interface and flat interface in the samples bonded at different conditions. Graded grain size was observed, with grain coarsening being more significant near sample surface due to EFAS-induced temperature gradient. Tensile testing revealed that the specimens fractured in the matrix away from the interface. The peak strength of 807 MPa was obtained in the samples welded at 1000°C. The materials obtained at 1100°C exhibited reduced tensile strength but improved ductility. Strain maps revealed by digital image correlation showed the flat interfaces were less ductile compared to the matrix. The hardness reduced near sample surfaces due to enlarged grains induced by temperature gradient. The interfaces with GB migration exhibited improved corrosion resistance in molten salt compared to the flat interfaces.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Active Galactic Nuclei Continuum Reverberation Mapping Based on Zwicky Transient Facility Light Curves

We perform a systematic survey of active galactic nuclei (AGNs) continuum lags using ~3 days cadence gri-band light curves from the Zwicky Transient Facility. We select a sample of 94 type 1 AGNs at z < 0.8 with significant and consistent inter-band lags based on the interpolated cross-correlation function method and the Bayesian method JAVELIN. Within the framework of the "lamp-post" reprocessing model, our findings are: (1) The continuum emission (CE) sizes inferred from the data are larger than the disk sizes predicted by the standard thin-disk model. (2) For a subset of the sample, the CE size exceeds the theoretical limit of the self-gravity radius (12 lt-days) for geometrically thin disks. (3) The CE size scales with continuum luminosity as R CE ∝ L 0.48±0.04 with a scatter of 0.2 dex, analogous to the well-known radius–luminosity relation of broad Hβ. These findings suggest a significant contribution of diffuse continuum emission from the broad-line region (BLR) to AGN continuum lags. We find that the R CE –L relation can be explained by a photoionization model that assumes ~23% of the total flux comes from the diffuse BLR emission. In addition, the ratio of the CE size and model-predicted disk size anticorrelates with the continuum luminosity, which is indicative of a potential nondisk BLR lag contribution evolving with the luminosity. Finally, a robust positive correlation between the CE size and black hole mass is detected.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Speciation mapping of the oxidation layer on aged uranium dioxide using scanning transmission x-ray spectromicroscopy

In this study, UO 2 was aged in humid air and prepared as a thin section using a focused ion beam (FIB) instrument. The specimen was measured using synchrotron radiation spectromicroscopy techniques at the Beamline 11.0.2 STXM end station of the Advanced Light Source (ALS). Non-negative matrix factorization (NMF) methods were used to identify and map three component x-ray absorption near-edge structure (XANES) spectra in the oxygen K-edge data, revealing a surface layer of U 4 O 9 with a thickness of 206 ± 21 nm, and the bulk of the sample remaining as UO 2 . Uranium N 4,5 -edge XANES spectromicroscopy supports these results. The diffusion-controlled parabolic rate constant for UO 2 oxidation to U 4 O 9 was calculated from the observed layer thickness and compared to literature values. Complementary transmission electron microscopy (TEM) was used to image the sample and identify the phases present in various regions, confirming the STXM results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Infrared Nanoimaging of Hydrogenated Perovskite Nickelate Memristive Devices

Solid-state devices made from correlated oxides, such as perovskite nickelates, are promising for neuromorphic computing by mimicking biological synaptic function. However, comprehending dopant action at the nanoscale poses a formidable challenge to understanding the elementary mechanisms involved. Here, we perform operando infrared nanoimaging of hydrogen-doped correlated perovskite, neodymium nickel oxide (H-NdNiO 3 , H-NNO), devices and reveal how an applied field perturbs dopant distribution at the nanoscale. This perturbation leads to stripe phases of varying conductivity perpendicular to the applied field, which define the macroscale electrical characteristics of the devices. Hyperspectral nano-FTIR imaging in conjunction with density functional theory calculations unveils a real-space map of multiple vibrational states of H-NNO associated with OH stretching modes and their dependence on the dopant concentration. Moreover, the localization of excess charges induces an out-of-plane lattice expansion in NNO which was confirmed by in situ X-ray diffraction and creates a strain that acts as a barrier against further diffusion. Our results and the techniques presented here hold great potential for the rapidly growing field of memristors and neuromorphic devices wherein nanoscale ion motion is fundamentally responsible for function.

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

A hybrid data–model approach to map soil thickness in mountain hillslopes

Abstract. Soil thickness plays a central role in the interactions between vegetation, soils, and topography, where it controls the retention and release of water, carbon, nitrogen, and metals. However, mapping soil thickness, here defined as the mobile regolith layer, at high spatial resolution remains challenging. Here, we develop a hybrid model that combines a process-based model and empirical relationships to estimate the spatial heterogeneity of soil thickness with fine spatial resolution (0.5 m). We apply this model to two aspects of hillslopes (southwest- and northeast-facing, respectively) in the East River watershed in Colorado. Two independent measurement methods – auger and cone penetrometer – are used to sample soil thickness at 78 locations to calibrate the local value of unconstrained parameters within the hybrid model. Sensitivity analysis using the hybrid model reveals that the diffusion coefficient used in hillslope diffusion modeling has the largest sensitivity among all input parameters. In addition, our results from both sampling and modeling show that, in general, the northeast-facing hillslope has a deeper soil layer than the southwest-facing hillslope. By comparing the soil thickness estimated between a machine-learning approach and this hybrid model, the hybrid model provides higher accuracy and requires less sampling data. Modeling results further reveal that the southwest-facing hillslope has a slightly faster surface soil erosion rate and soil production rate than the northeast-facing hillslope, which suggests that the relatively less dense vegetation cover and drier surface soils on the southwest-facing slopes influence soil properties. With seven parameters in total for calibration, this hybrid model can provide a realistic soil thickness map with a relatively small amount of sampling dataset comparing to machine-learning approach. Integrating process-based modeling and statistical analysis not only provides a thorough understanding of the fundamental mechanisms for soil thickness prediction but also integrates the strengths of both statistical approaches and process-based modeling approaches.

58 GEOSCIENCES↗
DOE OSTI2022

Effects of external kink and fishbone-like modes on energetic particle transport in tokamak plasmas

Transport and loss of beam injected energetic particles (EPs) due to three-dimensional perturbations, associated with the external kink (XK) instability and fishbone-like mode (FLM), are numerically investigated utilizing the guiding center following code ORBIT for static toroidal plasmas in HL-2A. The perturbation structure for the XK is computed by the MARS-F code and then mapped to the Boozer coordinates as defined in ORBIT. The simulation shows that the EP profile experiences a significant change in the middle of the plasma column, when the XK-induced radial magnetic field perturbation amplitude, normalized by the equilibrium field, exceeds a threshold value of about 10 -2 . The EP transport is found to be dominated by a diffusion process instead of convection. Furthermore, by scanning the perturbation frequency as a free parameter while maintaining the XK mode structure (thus mimicking the FLM as observed in DIII-D and JT-60U tokamaks), redistribution and loss of EPs are found to be substantially enhanced due to strong resonances between the FLM and EPs, when the mode frequency exceeds a threshold value of ~2 kHz for the case considered. For either XK or FLM, the response of passing EPs to the perturbation is dominant due to the assumed tangential neutral beam injection. Most lost EPs due to these instabilities are initially passing particles but are eventually lost through trapped orbits.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Synchrotron X-ray metrology of dopant distribution and oxidation state in high pressure CVD grown TM 2+ :ZnSe optical fibers

High pressure chemical vapor deposition (HPCVD) has shown to be a promising method for producing Cr 2+ :ZnSe and Fe 2+ :ZnSe mid-IR optical fiber lasers. The oxidation state of the dopants and their spatial homogeneity are critical for the characterization of effective fiber laser performance; however, this is challenging for small fiber cores and small doping concentrations. We demonstrate using synchrotron micro X-ray fluorescence (XRF) mapping to study the distribution of the dopants throughout the fiber cross-sections. Furthermore, we study the local chemical environment of these unique fiber structures using micro X-ray near edge absorption spectroscopy (XANES). Our study reveals that transition metal doped ZnSe deposited using HPCVD has nanoscale dopant aggregation although the material is chemically identical to the commercially produced diffusion doped laser crystals, as indicated by the presence +2 oxidation state of the dopants. This work demonstrates the power of synchrotron-based X-ray techniques for use as metrology tools for improving the performance of laser materials in fiber geometry.

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

Subdiffraction Imaging of Carrier Dynamics in Halide Perovskite Semiconductors: Effects of Passivation, Morphology, and Ion Motion

In this article, we spatially resolve photocarrier dynamics in halide perovskites using time-resolved electrostatic force microscopy (trEFM) to map surface potential equilibration during photoexcitation. We present a unified interpretation of trEFM, which measures the evolution of the surface potential in response to photoexcitation. We show that trEFM measurements correlate with surface recombination velocity and carrier lifetimes, validated with time-resolved photoluminescence imaging. We further validate the interpretation of trEFM through wavelength- and intensity-dependent measurements and with drift-diffusion simulations. We compare several passivation agents, including (3-aminopropyl)trimethoxysilane (APTMS), [3-(2-aminoethylamino)propyl]trimethoxysilane (AEAPTMS), and phenethylammonium iodide (PEAI). The results reveal heterogeneity in surface potential equilibration times that correlates with perovskite film morphology and nanoscale variations in recombination dynamics following surface passivation. Not only do our results highlight the potential for further improvement of passivation strategies, but also the necessity of high spatial and temporal resolution methods, like trEFM, to evaluate next-generation semiconductors.

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

The surroundings of the Milky Way globular cluster NGC 6809

ABSTRACT We study the outer regions of the Milky Way globular cluster NGC 6809 based on Dark Energy Camera observations, which reach nearly 6 mag below the cluster main-sequence (MS) turn-off. In order to unveil its fainter outermost structure, we built stellar density maps using cluster MS stars, once the contamination of field stars was removed from the cluster colour–magnitude diagram. We found that only the resulting stellar density map for the lightest stars exhibits some excesses of stars at opposite sides from the cluster centre that diminish soon thereafter at ∼ 0.32°.Studied globular clusters with apogalactic distances smaller than that of NGC 6809 (5.5 kpc) do not have observed tidal tails. The lack of detection of tidal tails in the studied inner globular cluster sample could be due to the reduced diffusion time of tidal tails by the kinematically chaotic nature of the orbits of these globular clusters, thus shortening the time interval during which the tidal tails can be detected. Further investigations with an enlarged cluster sample are needed to confirm whether chaotic and non-chaotic orbits are responsible for the existence of globular clusters with tidal tails and those with extra-tidal features that are different from tidal tails or without any signatures of extended stellar density profiles.

Piatti, Andrés E.↗
DOE OSTI2021

A vortex sheet based analytical model of the curled wake behind yawed wind turbines

Motivated by the need for compact descriptions of the evolution of non-classical wakes behind yawed wind turbines, we develop an analytical model to predict the shape of curled wakes. Interest in such modelling arises due to the potential of wake steering as a strategy for mitigating power reduction and unsteady loading of downstream turbines in wind farms. We first estimate the distribution of the shed vorticity at the wake edge due to both yaw offset and rotating blades. By considering the wake edge as an ideally thin vortex sheet, we describe its evolution in time moving with the flow. Vortex sheet equations are solved using a power series expansion method, and an approximate solution for the wake shape is obtained. The vortex sheet time evolution is then mapped into a spatial evolution by using a convection velocity. Apart from the wake shape, the lateral deflection of the wake including ground effects is modelled. Our results show that there exists a universal solution for the shape of curled wakes if suitable dimensionless variables are employed. For the case of turbulent boundary layer inflow, the decay of vortex sheet circulation due to turbulent diffusion is included. Finally, we modify the Gaussian wake model by incorporating the predicted shape and deflection of the curled wake, so that we can calculate the wake profiles behind yawed turbines. Model predictions are validated against large-eddy simulations and laboratory experiments for turbines with various operating conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Fracture Network Quantification during CO2 Injection

This is the presentation prepared for the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗
DOE OSTI2025

Fracture Network Quantification during CO2 Injection

This is the conference paper accompanying an oral presentation at the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗