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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

STRUCTURE AND MORPHOLOGY OF X-RAY-SELECTED ACTIVE GALACTIC NUCLEUS HOSTS AT 1 < z < 3 IN THE CANDELS-COSMOS FIELD

We analyze morphologies of the host galaxies of 35 X-ray-selected active galactic nuclei (AGNs) at z ∼ 2 in the Cosmic Evolution Survey field using Hubble Space Telescope/WFC3 imaging taken from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey. We build a control sample of 350 galaxies in total by selecting 10 non-active galaxies drawn from the same field with a similar stellar mass and redshift for each AGN host. By performing two-dimensional fitting with GALFIT on the surface brightness profile, we find that the distribution of the Sérsic index (n) of AGN hosts does not show a statistical difference from that of the control sample. We measure the nonparametric morphological parameters (the asymmetry index A, the Gini coefficient G, the concentration index C, and the M {sub 20} index) based on point-source-subtracted images. All the distributions of these morphological parameters of AGN hosts are consistent with those of the control sample. We finally investigate the fraction of distorted morphologies in both samples by visual classification. Only ∼15% of the AGN hosts have highly distorted morphologies, possibly due to a major merger or interaction. We find there is no significant difference in the distortion fractions between the AGN host sample and control sample. We conclude that the morphologies of X-ray-selected AGN hosts are similar to those of non-active galaxies and most AGN activity is not triggered by a major merger.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Effective Defect Detection Using Instance Segmentation for NDI

Ultrasonic testing is a common Non-Destructive Inspection (NDI) method used in aerospace manufacturing. However, the complexity and size of the ultrasonic scans make it challenging to identify defects through visual inspection or machine learning models. Using computer vision techniques to identify defects from ultrasonic scans is an evolving research area. In this study, we used instance segmentation to identify the presence of defects in the ultrasonic scan images of composite panels that are representative of real components manufactured in aerospace. We used two models based on Mask- RCNN (Detectron 2) and YOLO 11 respectively. Additionally, we implemented a simple statistical pre-processing technique that reduces the burden of requiring custom-tailored pre-processing techniques. Our study demonstrates the feasibility and effectiveness of using instance segmentation in the NDI pipeline by significantly reducing data pre-processing time, inspection time, and overall costs.

computer vision techniques↗
DOE OSTI2017

The Carnegie-Irvine Galaxy Survey. V. Statistical Study of Bars and Buckled Bars

Simulations have shown that bars are subject to a vertical buckling instability that transforms thin bars into boxy or peanut-shaped structures, but the physical conditions necessary for buckling to occur are not fully understood. We use the large sample of local disk galaxies in the Carnegie-Irvine Galaxy Survey to examine the incidence of bars and buckled bars across the Hubble sequence. Depending on the disk inclination angle ( i ), a buckled bar reveals itself as either a boxy/peanut-shaped bulge (at high i ) or as a barlens structure (at low i ). We visually identify bars, boxy/peanut-shaped bulges, and barlenses, and examine the dependence of bar and buckled bar fractions on host galaxy properties, including Hubble type, stellar mass, color, and gas mass fraction. We find that the barred and unbarred disks show similar distributions in these physical parameters. The bar fraction is higher (70%–80%) in late-type disks with low stellar mass ( M {sub *} < 10{sup 10.5} M {sub ⊙}) and high gas mass ratio. In contrast, the buckled bar fraction increases to 80% toward massive and early-type disks ( M {sub *} > 10{sup 10.5} M {sub ⊙}), and decreases with higher gas mass ratio. These results suggest that bars are more difficult to grow in massive disks that are dynamically hotter than low-mass disks. However, once a bar forms, it can easily buckle in the massive disks, where a deeper potential can sustain the vertical resonant orbits. We also find a probable buckling bar candidate (ESO 506−G004) that could provide further clues to understand the timescale of the buckling process.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Streamlining the Coupling of BISON and Dakota Through the NEAMS Workbench

Metallic nuclear fuels for use in advanced reactors are an active area of research and development. Robust, accurate metallic fuel performance models are necessary for the design, analysis, and licensing of such reactors. However, metallic fuel performance models require additional development; they are not as mature as uranium dioxide fuel performance models. To support further metallic fuel development, Oak Ridge National Laboratory and the University of Florida have streamlined the coupling of the BISON fuel performance code with Design Analysis Kit for Optimization and Terascale Applications (Dakota) statistical analysis tool through the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench. This work included performing three different sensitivity analyses on metallic nuclear fuel models in BISON. The analyses examined were a general model of the IFR-1 experiment, the X430 experiment T654 pin, and the X430 experiment T651 pin. The results suggest that BISON and Dakota can be integrated through NEAMS Workbench to perform sensitivity and uncertainty analyses and visualize the results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Intra- and inter-observer variability in breast tumour bed contouring and the controversial role of surgical clips

The purpose of this study was to evaluate whether the visualization of surgical clips (SCs) on the same set of planning computed tomography (CT) of breast cancer (BC) patients influences agreement on tumour bed (TB) delineation. Planning CT (CT{sub orig}) of 47 BC patients with SCs to visualize the TB was processed in order to blur SCs and create a virtual CT (CT{sub mod}). Four radiation oncologists (ROs, 2 juniors and 2 seniors) contoured TB on both the CT sets. Centre of mass distance (CMD), percentage overlap as Dice similarity coefficient (DSC), surface distance as average Hausdorff distance (AHD) and TB volume size were analysed. The intra-observer variability when contouring TB with and without SCs was statistically significant (p-values = 0.016, 0.0002 and ≪ 0.001 for CMD, AHD and DSC, respectively). Junior ROs showed worse reproducibility compared to seniors. The median DSC was < 0.7. The inter-observer variability with and without SCs was statistically significant (p < 0.001) for all metrics, with an increase of 48.7% in DSC and decrease of 50.7% and 57.1% in CMD and AHD, respectively, as relative median values, when SCs were visible. Regarding TB volumes, when SCs were visible, the intra-observer analysis revealed that 3/4 ROs delineated larger volumes, especially juniors. The inter-observer analysis showed that, in presence of visible SCs, the difference in TB volume among all the ROs fell from statistically significant to borderline significance (p = 0.052). TB contouring is confirmed to be an observer-dependent task. SCs decreased the intra and inter-observer variability but the overall agreement between ROs remained low.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Simulations of muon imaging with the LANL GMT detector for spent nuclear fuel cask content verification

Atmospheric muons are typically high energy, highly penetrating charged particles. They interact with matter primarily through multiple Coulomb scatterings. Muon scattering intensities can be used to characterize the density and atomic number of the matter that they pass through. Previously, the Los Alamos National Laboratory (LANL) muon tomography team performed muon imaging of the partially filled MC-10 spent nuclear fuel (SNF) cask at Idaho National Laboratory (INL). This experiment demonstrated the feasibility of muon imaging for the verification of spent fuel container contents. That original effort used the mini muon tracker array, consisting of two arrays of drift tubes on either side of the SNF cask. The reconstructed image quality was limited by statistics, largely due to low muon flux at high zenith angles. A LANL led team will perform new measurements with a larger array, the Giant Muon Tracker (GMT), to improve data collection rates and statistics. In this work, simulations were performed with the GMT near the partially filled INL MC-10 cask. For more general fuel diversion detection, a full MC-10 cask and casks with a singular missing fuel bundle were also simulated. To understand minimum measurement times needed for missing bundle identification, 100 000 to millions of tracked muons (corresponding to 1.4 days to several weeks measurement time) were analyzed. Simulated images were then analyzed visually and numerically to explore techniques designed to minimize the collection time needed to identify the diversion of fuel in each scenario.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

helios: An R package to process heating and cooling degrees for GCAM

helios is an open-source R package that estimates population-weighted heating and cooling degree-hours (HDH and CDH) and degree-days (HDD and CDD) at various temporal (e.g., energy dispatch segments, monthly, yearly) and spatial scales (e.g., U.S. states, global political regions, countries). The degree hour and degree day outputs from helios are used to inform electricity demand load in the Global Change Analysis Model (GCAM) as well as in GCAM-USA (which is the version of GCAM with U.S. state-level details). helios uses a workflow with four steps: processing raw data; calculating heating and cooling degrees; visualizing performance diagnostics; and outputing results in various formats. There are two sources of widely-used climate data compatible with helios: (1) hourly climate data with 12-km resolution that are dynamically downscaled with the Weather Research and Forecasting (WRF) model and projected using a thermal global warming (TGW) approach; and (2) daily climate data with 0.5-degree resolution from the Coupled Model Intercomparison Project (CMIP) that is bias-adjusted and statistical downscaled by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In summary, helios is a model that standardizes methodology of heating and cooling degrees-hours and degree-days using publicly available data and advance the understanding of the impact of spatial and temporal temperature variability on building energy services.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources

Background: Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods: HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals’ emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results: The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Galaxy and Mass Assembly (GAMA): Exploring the WISE Web in G12

We present an analysis of the mid-infrared Wide-field Infrared Survey Explorer (WISE) sources seen within the equatorial GAMA G12 field, located in the North Galactic Cap. Our motivation is to study and characterize the behavior of WISE source populations in anticipation of the deep multiwavelength surveys that will define the next decade, with the principal science goal of mapping the 3D large-scale structures and determining the global physical attributes of the host galaxies. In combination with cosmological redshifts, we identify galaxies from their WISE W1 (3.4 μm) resolved emission, and we also perform a star-galaxy separation using apparent magnitude, colors, and statistical modeling of star counts. The resulting galaxy catalog has ≃590,000 sources in 60 deg{sup 2}, reaching a W1 5σ depth of 31 μJy. At the faint end, where redshifts are not available, we employ a luminosity function analysis to show that approximately 27% of all WISE extragalactic sources to a limit of 17.5 mag (31 μJy) are at high redshift, z>1. The spatial distribution is investigated using two-point correlation functions and a 3D source density characterization at 5 Mpc and 20 Mpc scales. For angular distributions, we find that brighter and more massive sources are strongly clustered relative to fainter sources with lower mass; likewise, based on WISE colors, spheroidal galaxies have the strongest clustering, while late-type disk galaxies have the lowest clustering amplitudes. In three dimensions, we find a number of distinct groupings, often bridged by filaments and superstructures. Using special visualization tools, we map these structures, exploring how clustering may play a role with stellar mass and galaxy type.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Near Real-time Data Analysis of Core-collapse Supernova Simulations with Bellerophon

We present an overview of a software system, Bellerophon, built to support a production-level HPC application called CHIMERA, which simulates core-collapse supernova events at the petascale. Developed over the last four years, Bellerophon enables CHIMERA's geographically dispersed team of collaborators to perform data analysis in near real-time. Its n-tier architecture provides an encapsulated, end-to-end software solution that enables the CHIMERA team to quickly and easily access highly customizable animated and static views of results from anywhere in the world via a web- deliverable, cross-platform desktop application. In addition, Bellerophon addresses software engineering tasks for the CHIMERA team by providing an automated mechanism for performing regression testing on a variety of supercomputing platforms. Elements of the team's workflow management needs are met with software tools that dynamically generate code repository statistics, access important online resources, and monitor the current status of several supercomputing resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Radiation Dose–Dependent Hippocampal Atrophy Detected With Longitudinal Volumetric Magnetic Resonance Imaging

Purpose: After radiation therapy (RT) to the brain, patients often experience memory impairment, which may be partially mediated by damage to the hippocampus. Hippocampal sparing in RT planning is the subject of recent and ongoing clinical trials. Calculating appropriate hippocampal dose constraints would be improved by efficient in vivo measurements of hippocampal damage. In this study we sought to determine whether brain RT was associated with dose-dependent hippocampal atrophy. Methods and Materials: Hippocampal volume was measured with magnetic resonance imaging (MRI) in 52 patients who underwent fractionated, partial brain RT for primary brain tumors. Study patients had high-resolution, 3-dimensional volumetric MRI before and 1 year after RT. Images were processed using software with clearance from the US Food and Drug Administration and Conformité Européene marking for automated measurement of hippocampal volume. Automated results were inspected visually for accuracy. Tumor and surgical changes were censored. Mean hippocampal dose was tested for correlation with hippocampal atrophy 1 year after RT. Average hippocampal volume change was also calculated for hippocampi receiving high (>40 Gy) or low (<10 Gy) mean RT dose. A multivariate analysis was conducted with linear mixed-effects modeling to evaluate other potential predictors of hippocampal volume change, including patient (random effect), age, hemisphere, sex, seizure history, and baseline volume. Statistical significance was evaluated at α = 0.05. Results: Mean hippocampal dose was significantly correlated with hippocampal volume loss (r=−0.24, P=.03). Mean hippocampal volume was significantly reduced 1 year after high-dose RT (mean −6%, P=.009) but not after low-dose RT. In multivariate analysis, both RT dose and patient age were significant predictors of hippocampal atrophy (P<.01). Conclusions: The hippocampus demonstrates radiation dose–dependent atrophy after treatment for brain tumors. Quantitative MRI is a noninvasive imaging technique capable of measuring radiation effects on intracranial structures. This technique could be investigated as a potential biomarker for development of reliable dose constraints for improved cognitive outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

An Extensive Catalog of Early-type Dwarf Galaxies in the Local Universe: Morphology and Environment

We present an extensive catalog of 5405 early-type dwarf (dE) galaxies located in the various environments, i.e., clusters, groups, and fields, of the local universe (z < 0.01). The dEs are selected through visual inspection of the Legacy survey's g–r–z combined tricolor images. The inspected area, covering a total sky area of 7643 deg 2 , encompasses two local clusters (Virgo and Fornax), 265 groups, and the regions around 586 field galaxies of M K < -21 mag. The catalog aims to be one of the most extensive and publicly accessible collections of data on dEs, despite its complex completeness limits, which may not accurately represent its statistical completeness. The strength of the catalog lies in the morphological characteristics, including nucleated, tidal, and ultradiffuse dEs. The two clusters contribute nearly half (2437 out of 5405) of the dEs, and the 265 groups contribute 2103 dEs. There are 864 dEs in 586 fields, i.e., ~1.47 dEs per field. Using a standard definition commonly used in literature, we identify 100 ultradiffuse galaxies (UDGs), which compose ~2% of the dE population. We find that 40% of our sample dEs harbor a central nucleus, and among the UDG population, a majority (79%) are nonnucleated. About 1.3% of dEs suffer from ongoing tidal disturbance by nearby massive galaxies, and only 0.03% show a sign of recent dwarf–dwarf mergers. The association between dEs and their nearest bright neighbor galaxies suggests that dEs are more likely created where their neighbors are non-star-forming ones.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

MALDI Orbitrap Mass Spectrometry Profiling of Dysregulated Sulfoglycosphingolipids in Renal Cell Carcinoma Tissues

Matrix-assisted laser desorption/ionization coupled with Orbitrap mass spectrometry (MALDI-Orbitrap-MS) is used for the clinical study of patients with renal cell carcinoma (RCC), as the most common type of kidney cancer. Significant changes in sulfoglycosphingolipid abundances between tumor and autologous normal kidney tissues are observed. First, sulfoglycosphingolipid species in studied RCC samples are identified using high mass accuracy full scan and tandem mass spectra. Subsequently, optimization, method validation, and statistical evaluation of MALDI-MS data for 158 tissues of 80 patients are discussed. More than 120 sulfoglycosphingolipids containing one to five hexosyl units are identified in human RCC samples based on the systematic study of their fragmentation behavior. Many of them are recorded here for the first time. Multivariate data analysis (MDA) methods, i.e., unsupervised principal component analysis (PCA) and supervised orthogonal partial least square discriminant analysis (OPLS-DA), are used for the visualization of differences between normal and tumor samples to reveal the most up- and downregulated lipids in tumor tissues. Obtained results are closely correlated with MALDI mass spectrometry imaging (MSI) and histologic staining. Important steps of the present MALDI-Orbitrap-MS approach are also discussed, such as the selection of best matrix, correct normalization, validation for semiquantitative study, and problems with possible isobaric interferences on closed masses in full scan mass spectra. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Labile Fe(III) supersaturation controls nucleation and properties of product phases from Fe(II)-catalyzed ferrihydrite transformation

We report Fe(II)-catalyzed ferrihydrite (Fh) transformation to more crystalline iron (oxyhydr)oxide phases is a widely occurring geochemical process which has been extensively studied as a function of Fe(II)/Fh ratios at fixed Fh loadings. However, recent isolation of an intermediate Fe(III) species resulting from Fe(II)-Fh contact that facilitates transformation by dissolution/reprecipitation suggests that the kinetics and properties of product phases will instead depend mostly on its rate of accumulation to a critical concentration, consistent with principles in the classical nucleation theory (CNT). This suggests a dependence both on the loading of Fe(II) on the surface, which controls the rate of labile Fe(III) formation, as well as the available volume of solution, which also impacts how fast it can achieve its critical concentration to nucleate product phases. To specifically examine the latter effect, here we studied transformation of 15 mg Fh in 1 mM FeSO 4 solutions at pH 7.2 in batch suspensions of 30 mL, 150 mL, and 450 mL volumes. Time-dependent concentrations of aqueous Fe(II), surface-associated Fe(II), and resulting labile Fe(III) were monitored along with bulk solids characterization as a function of time. Transmission electron microscopy (TEM) was used to visualize the evolution of phases at identical locations on TEM grids. The collective results show that the rates of Fh loss and emergence of product lepidocrocite (Lp) and goethite (Gt) as well as their phase proportions, nucleation mode and morphological properties depend directly on the rate of accumulation of the labile Fe(III) precursor to its critical concentration, which in our experiments was controlled simply by varying the available volume of solution into which it enters. Statistical analyses of TEM image data suggest that while both heterogeneous and homogeneous nucleation occurred in all experiments, the former was increasingly favored at lower Fh/solution ratio due to its lower nucleation barrier being more favorable at attendant lower supersaturations of Fe(III).

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

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗
DOE OSTI2017

Dynamics of unstably stratified free shear flows: an experimental investigation of coupled Kelvin–Helmholtz and Rayleigh–Taylor instability

The dynamics of the coupled Kelvin–Helmholtz (KH) and Rayleigh–Taylor (RT) instability (referred to as KHRT instability or KHRTI) is studied using statistically steady experiments performed in a multi-layer gas tunnel. Experiments are performed at four density ratios ranging in Atwood number $A_{t}$ from 0.035 to 0.159, with varying amounts of shear and $\unicode[STIX]{x0394}U/U$ ranging from 0 to 0.48, where $\unicode[STIX]{x0394}U$ is the speed difference between the two flow streams being investigated and $U$ is the mean velocity of these two streams. Three types of diagnostics – back-lit visualization, hot-wire anemometry and particle image velocimetry (PIV) – are employed to obtain the mixing widths, velocity field and density field. The flow is found to be governed by KH dynamics at early times and RT dynamics at late times. This transition from KH-instability-like to RT-instability-like behaviour is quantified using the Richardson number. Transitional Richardson number magnitudes obtained for the present KHRT flows are found to be in the range 0.17–0.56 similar to the critical Richardson numbers for stably stratified free shear flows. Comparing the evolution of density and velocity mixing widths, the density mixing layer is found to be approximately two times as thick as the velocity mixing layer. Scaling of velocity fluctuations is attempted using combinations of KH and RT scales. It is found that the proposed KHRT velocity scale, obtained using the combined mixing-layer growth equation, is appropriate for intermediate stages of the flow when both KH and RT dynamics are comparable. Probability density functions (p.d.f.s) for different fluctuating quantities are presented. Multiple peaks in p.d.f.s are qualitatively explained from the development of coherent KH roll-ups and their subsequent transition into turbulent pockets. The evolution of energy spectra indicates that density fluctuations start to show an inertial subrange from earlier times compared to velocity fluctuations. The spectra exhibit a slightly steeper slope than the Kolmogorov–Obukhov five-thirds law.

Mechanics↗
DOE OSTI2020

Multivariate Regression of Pyrotechnic Igniter Output

Multivariate multiple regression models are applied to simplified pyrotechnic igniters for the first time to understand how changes in manufactured parameters can affect the output gas dynamic response and the timing of ignition events. The statistical modeling technique is applied to demonstrate quantification of the effects of a set of independent variables measured in the as-fabricated igniters on a set of responses experimentally measured from the functioned igniters. Two independent process variables were intentionally varied following a full factorial experimental design while several other independent variables varied within their normal manufacturing variability range. The four igniter performance responses consisted of the timing of sequential events during igniter function and visual gas dynamic output in the form of shock wave strength observed with high-speed schlieren imaging. Linear regression models built using the measurements throughout the manufacturing processes and the output variance provide insight into the critical device parameters that dominate performance

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Multiscale Cryo Electron Microscopy Reveals Interfacial Degradation and Stabilization in Battery Electrodes

Electrochemical interfaces are dynamic systems, evolving based on their local environment and reactant surface structures. The electrode-electrolyte interface in Li-ion batteries can be protective, limiting parasitic reactions with the electrolyte to passivate the surface [1]. Additionally, this interphase has an impact on the Li-ion transport through that layer based on its composition, bonding environment, and thickness. These parameters are challenging to collect and may vary depending on the electrode surface site investigated relative to its spatial position in a coin cell. This study will detail a multiscale cryogenic electron microscopy approach where millimeter-scale cross-sections through the coin cell batteries were made using a cryogenic stage within a fs-laser plasma focused ion beam (laser PFIB) with complementary energy dispersive X-ray spectroscopy able to detect variations in the composition at electrode interfaces [2]. Microscale cross-sectioning and lamella sample preparation of battery electrodes was conducted at the Center for Integrated Nanotechnologies using a Ga-ion focused ion beam (FIB) with air-free and cryo-transfer [3], followed by nanoscale mapping of composition and bonding within the CEI through cryo-scanning transmission electron microscopy (cryo-STEM) electron energy loss spectroscopy [4]. This multiscale approach enabled identification of millimeter-scale features of a battery stack with visualization of degradation in electrodes such as cracks in cathode particles, gas evolution, and SEI evolution; microscale interfacial characteristics, such as heterogeneity in the SEI or barrier layer and identification of electrolyte networks to the electrode surfaces; and nanoscale measurement of the CEI thickness, mapping of transition metal bonding within the cathode particles to identify loss of active materials, and identification of beneficial electrolyte additives incorporated into the CEI structure. This multiscale approach allows for a statistical understanding of the primary mechanisms and parasitic degradation pathways that impact performance by limiting the ion transport pathways within Li+ batteries.

36 MATERIALS SCIENCE↗