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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

On the effect of flux-surface shaping on trapped-electron modes in quasi-helically symmetric stellarators

Using a novel optimization procedure, it has been shown that the Helically Symmetric eXperiment stellarator can be optimized for reduced trapped-electron-mode (TEM) instability [Gerard et al., Nucl. Fusion 63, (2023) 056004]. Presently, with a set of 563 experimental candidate configurations, gyrokinetic simulations are performed to investigate the efficacy of available energy EA, quasi-helical symmetry, and flux-surface shaping parameters as metrics for TEM stabilization. It is found that lower values of EA correlate with reduced growth rates, but only when separate flux-surface shaping regimes are considered. Moreover, configurations with improved quasi-helical symmetry demonstrate a similar reduction in growth rates and less scatter compared to EA. Regarding flux-surface shaping, a set of helical shaping parameters is introduced that show increased elongation is strongly correlated with reduced TEM growth rates, however, only when the quasi-helical symmetry is preserved. Using a newly derived velocity-space-averaged TEM resonance operator, these trends are analyzed to provide insights into the physical mechanism of the observed stabilization. For elongation, stabilization is attributed to geometric effects that reduce the destabilizing particle drifts across the magnetic field. Regarding quasi-helical symmetry, the TEM resonance in the maximally resonant trapping well is shown to increase as the quasi-helical symmetry is broken, and breaking quasi-helical symmetry increases the prevalence of highly resonant trapping wells. While these results demonstrate the limitations of using any single metric as a linear TEM proxy, it is shown that quasi-helical symmetry and plasma elongation are highly effective metrics for reducing TEM growth rates in helical equilibria.

Physics↗
DOE OSTI2023

Novel method to control explosive shock sensitivity: Formulations, experiments and modeling

The microstructure of a heterogeneous high explosive (HE) affects its shock initiation sensitivity and detonation performance. Alteration of the void content and/or void structure (i.e., bulk heating or mechanical damage) therefore changes the shock initiation behavior. Controlling and predicting the change in shock sensitivity after an HE has undergone microstructural changes addresses an important and challenging goal for the design and understanding of novel energetic material formulations. In this study, we aimed to develop HE systems to precisely tune shock sensitivity by a thermal treatment prior to use. Specifically, we incorporated a small fraction (1 wt% or less) of thermally expandable microspheres (TEMs) during the formulation process of various plastic-bonded explosives (PBX). TEMs typically consist of a thermoplastic acrylonitrile shell (10-50 µm diameter), which encapsulates an inert low boiling hydrocarbon. Upon heating, the TEMs expand as the shell softens while the hydrocarbon gasifies, increasing the internal pressure and expanding the particle by as much as 120 vol% (irreversibly). Here, we present our progress on shock sensitivity comparisons of HE formulations doped with TEMs after heating and expansion. Experiments, using Composition C-4 thermally cycled to 120°C, showed an increase in shock sensitivity. Additionally, mesoscale modeling revealed that the TEM itself does not act as a hotspot, but instead has a secondary effect on the response of nearby voids. We conclude that TEMs indeed do provide a method to tune shock sensitivity. Further, our results emphasize the non-uniformity of shock waves at the mesoscale, and that upstream defects influence the reactivity of downstream defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Ground-based_transient_electromagnetic_data_and_resistivity_models_for_SubTER_BelleCreek_2017-2018

Ground-based transient electromagnetic (TEM) data were acquired in selected locations around Belle Creek, Montana to define the resistivity structure of the near surface. Data were acquired using the ABEM WalkTEM system (Guideline Geo Ab, Sundbyberg, Sweden). TEM data were processed and numerically inverted to derive one-dimensional resistivity structure using SPIA (Aarhus Geosoftware, Aarhus, Denmark). This release includes raw and processed TEM data and resistivity models for each data location using the following structure: Ground-based_transient_electromagnetic_data_and_resistivity_models_for_SubTER_BelleCreek_2017-2018.xml SBC_TEM_2019_SoundingLocationsModels.gdb.zip - file geodatabase with all models and plots attached. This is a mirror of the contents of the model directory. Ground-based_transient_electromagnetic_data_and_resistivity_models_for_SubTER_BelleCreek_2017-2018.zip Data SBC_USF - raw data USF_format_description.pdf - manual describing the USF file format SBC_SoundingID-USF_lookup.csv - table describing the USF file naming convention and channel mapping *.usf files - raw, unprocessed data files SBC_TEM - processed data AarhusInv_manual.pdf - manual describing the TEM file format *.tem files - processed data files Models SBC_Model_Plots - plots of the data and the models for each sounding location TEM_model_data_dictionary.csv - data dictionary describing tabulated models SBC_TEM_models.csv - tabulated models

geophysical surveying↗
DOE OSTI2024

code for "Improving the QBO forcing by resolved waves with vertical grid refinement in E3SMv2"

This is all code that used in the journal article "Improving the QBO forcing by resolved waves with vertical grid refinement in E3SMv2", including: Running and post processing E3SM: Run E3SM: run_E3SM.2023.scidac.MMF.amip.py Regrid: regrid.E3SM.py post processing, diagnostics, archive: run_post.2023.scidac.MMF.py TEM calculation, including filter TEM, E3SM: calculate.TEM.v2.py calculate.TEM.monthly_mean.v1.py TEM, ERA5: ERA5_calculate_TEM_90.py merge TEM data: merge_TEM_E3SM_ERA5.py TEM, filter, E3SM: filter_TEM_E3SM.py TEM, filter, ERA5: filter_TEM_ERA5.py WK wave analysis code from (https://github.com/brianpm/wavenumber_frequency): wavenumber_frequency_functions.py calculate the wave spectra so easy to plot: wk_calculation.py Make figures some functions for plot: plot.py code for drawing paper plots: figures_for_paper.ipynb

Hannah, WalterM↗
DOE OSTI2025

Synthesizing intermetallic thermoelectric materials using metal flux growth method

With zero energy poverty by 2050 goals, exploring innovative energy technologies is essential. Thermoelectric materials (TEMs) have the potential to harness waste heat and convert it to electricity (e.g., for spacecraft power, sensors, and cryogenic cooling). Two limitations of thermoelectric compounds are their low efficiency and limited pool of materials. Optimizing the efficiency of TEMs is challenging due to the interdependent relationship between electrical and thermal conductivity. A deeper understanding of electronic properties and lattice thermal conductivity is necessary to “understand, predict and ultimately control” the thermoelectric properties of TEMs. Understanding the influence of light-atom-doping and intrinsic defects on the electronic properties of the f-element containing TEMs are important questions that need to be answered to design and synthesize TEMs with optimal parameters. The purpose of this work is to understand how doping f-element based TEMs with light elements, such as carbon and boron, would impact the crystal structure, bond lengths, band gaps, and thermoelectric characteristics. High-quality f¬-element containing intermetallic single crystals are grown in metal flux media. In molten metal flux growth method, one or more low-melting metals such as aluminum, gallium, tin, and bismuth are used in excess as the reaction medium. As these are solution-state reactions, we can use lower temperatures than solid-state reactions and isolate the kinetic products instead of the thermodynamically stable compound. Then these are characterized using X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, magnetization, electrical and thermal conductivities, and thermoelectric power.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2023

Pulsed-Beam Transmission Electron Microscopy and Radiation Damage

Here, we review the use of pulsed electron-beams in transmission electron microscopes (TEMs) for the purpose of mitigating specimen damage. We begin by placing the importance of TEMs with respect to materials characterization into proper context, and we provide a brief overview of established methods for reducing or eliminating the deleterious effects of beam-induced damage. We then introduce the concept of pulsed-beam TEM, and we briefly describe the basic methods and instrument configurations used to create so-called temporally structured electron beams. Following a brief overview of the use of high-dose-rate pulsed-electron beams in cancer radiation therapy, we review historical speculations and more recent compelling but mostly anecdotal findings of a pulsed-beam TEM damage effect. This is followed by an in-depth technical review of recent works seeking to establish cause-and-effect relationships, to conclusively uncover the presence of an effect, and to explore the practicality of the approach. These studies, in particular, provide the most compelling evidence to date that using a pulsed electron beam in the TEM is indeed a viable way to mitigate damage. Throughout, we point out current gaps in understanding, and we conclude with a brief perspective of current needs and future directions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multi-scale imaging of high-pressure hydrogen induced damage in EPDM rubber using X-ray microcomputed tomography, helium-ion microscopy and transmission electron microscopy

Ethylene propylene diene (EPDM) rubber has gained increasing interest for use in hydrogen infrastructure due to its excellent sealing performance and low temperature properties. However, severe structural damage has been observed in EPDM O-rings after exposure to high-pressure hydrogen. The origination and propagation mechanisms of this damage are poorly understood. Here, to address this knowledge gap, multi-scale imaging leveraging X-ray micro-computed tomography (micro-CT), helium ion microscopy (HeIM), and transmission electron microscopy (TEM) were used in this work to study a series of sulfur-cured ethylene propylene diene (EPDM) rubber materials with varying additives that were exposed to different hydrogen environments. Micro-CT captured the substantial structural damage due to hydrogen exposure; it revealed an association between zinc oxide (ZnO) particles and damage initiation. Further studies by TEM and scanning TEM with energy dispersive X-ray spectroscopy (EDS) were focused on these particles at the micro-to nano-scale range. TEM indicated that hydrogen causes void formation at the interface between ZnO and the rubber matrix. HeIM enabled imaging of surface morphology of the material at high resolution pre- and post-hydrogen exposure while providing information on chemical composition and that cannot be captured by either micro-CT or TEM.

08 HYDROGEN↗
DOE OSTI2023

An artificial intelligence’s interpretation of complex high-resolution in situ transmission electron microscopy data

Complicated nano- and atomic-scale processes with sub-angstrom spatial resolution and millisecond time resolution visualized by in situ transmission electron microscopy (TEM) are often highly dynamical and time consuming to analyze and interpret. Here, we report how variational autoencoders (VAEs) can provide an artificial intelligence’s interpretation of high-resolution in situ TEM data by condensing and deconvoluting complicated atomic-scale dynamics into a latent space with reduced dimensionality. We designed a VAE model with high latent dimensions capable of deconvoluting information from complex high-resolution TEM data. We demonstrate how this model, with high latent dimensions trained on atomically resolved TEM images of lead sulfide (PbS) nanocrystals, is able to capture movements and perturbations of periodic lattices in both simulated and real in situ TEM data. Importantly, the VAE model shows the capability of detecting and deconvoluting dynamical nanoscale physical processes, such as the rotation of crystal lattices and intra-particle ripening during the annealing of semiconductor nanocrystals.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Quasilinear modelling of collisional trapped electron modes

The simplification of collision operators is necessary for quasilinear turbulence modelling used with integrated modelling frameworks, such as the gyrokinetic code QuaLiKiz. The treatment of collisions greatly impacts the accuracy of trapped electron mode (TEM) modelling, which is necessary to predict the electron heat flux and the balance between inward and outward particle fluxes. In particular, accurate particle flux predictions are necessary to successfully model density peaking in the tokamak core. We explored two ways of improving collisional TEM model reduction for tokamak core plasmas. First, we carried out linear GENE simulations to study the complex interplay between collisions and trapped electrons. We then used these simulations to define an effective trapped fraction to characterize the collisional TEM based on two key parameters, the local inverse-aspect ratio $\epsilon$ and the collisionality $\nu ^\ast$. One aspect missing from analytical TEM research is that the collisional frequency and the bounce-transit frequency are both velocity dependent; this effective trapped fraction takes both into account. In doing so, we determined that two parameters are not enough to model the collisional TEM, as an additional third free parameter was necessary. We determined that this model, as currently formulated, is not suitable for integrated modelling purposes. Second, we directly improved QuaLiKiz's Krook operator, which relies on two free parameters. We determined that these parameters required adjustments against higher-fidelity collisional models. In order to improve density profile predictions when paired with integrated models, we refined the Krook operator by using GENE simulations as a higher-fidelity point of comparison. We then demonstrate strong improvement of density peaking predictions of QuaLiKiz within the integrated modelling framework JETTO.

fusion plasma↗
DOE OSTI2025

Identification of the glassy state in nanoparticles by transmission electron microscopy

Identification of amorphous phases in nanoparticles by atomic-resolution transmission electron microscopy (TEM) requires analyses such as tilt-angle-dependent TEM imaging and single-nanoparticle electron diffraction, rather than relying on a single TEM image. Here, the disordered structures of amorphous nanoparticles offer unique atomic configurations and properties that differ from the properties of their crystalline counterparts. These characteristics have motivated the exploration of such materials for mechanical, sensing and catalytic applications. In addition, the formation of amorphous metal nanoparticles is an important endeavour to understand the process of vitrification and the nature of the glassy state. Atomic-resolution transmission electron microscopy (TEM) is increasingly being used as a tool for characterizing structures of nanoparticles produced by vitrification. In this Comment, we discuss the pitfalls of using TEM for ascertaining whether nanoparticles are amorphous. We also make recommendations of best practices.

Alcorn, Francis M. [Sandia National Laboratories (↗
DOE OSTI2022

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

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

Global gyrokinetic simulations of electrostatic microturbulent transport in LHD stellarator with boron impurity

Abstract Global gyrokinetic simulations of electrostatic microturbulent transport for discharge # 166256 of the Large Helical Device stellarator in the presence of boron impurity show the co-existence of the ion temperature gradient (ITG) turbulence and trapped electron mode (TEM) turbulence before and during boron powder injection. ITG turbulence dominates in the core, whereas TEM dominates near the edge, consistent with the experimental observations. Linear TEM frequency increases from ∼ 80 kHz to ∼ 100 kHz during boron injection, and ITG frequency decreases from ∼ 20 kHz to ∼ 13 kHz, consistent with the experiments. The poloidal wave number spectrum is broad for both ITG (0–0.5 mm −1 ) and TEM (0–0.25 mm −1 ). The nonlinear simulations with boron impurity show a reduction in the heat conductivity compared to the case without boron. The comparison of the nonlinear transport before and during boron injection shows that the ion heat transport is substantially reduced in the region where the TEM is dominant. However, the average electron heat transport throughout the radial domain and the average ion heat transport in the region where the ITG is dominant are similar. The simulations with boron show the effective heat conductivity values qualitatively agree with the estimate obtained from the experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Suppressing trapped-electron-mode-driven turbulence via optimization of three-dimensional shaping

Abstract Turbulent transport driven by trapped electron modes (TEMs) is believed to drive significant heat and particle transport in quasihelically symmetric stellarators. Two three-dimensionally-shaped magnetic configurations with suppressed TEM-driven turbulence were generated through optimization that targeted quasihelical symmetry and the available energy of trapped electrons. Initial equilibria have flux surface shapes with a helically rotating negative triangularity (NT) and positive triangularity (PT). In gyrokinetic simulations, TEMs are suppressed in the reduced-TEM NT and PT configurations, showing that NT does not have the same beneficial turbulence properties over PT as seen in tokamaks. Heat fluxes from TEMs are also suppressed. Without temperature gradients and with a strong density gradient, the most unstable modes at low k y were consistent with toroidal universal instabilities (UIs) in the NT case and slab UIs in the PT case. Nonlinear simulations show that UIs drive substantial heat flux in both the NT and PT configurations. A moderate increase in β halves the heat flux in the NT configuration, while suppressing the heat flux in the PT geometry. Based on the present work, future optimizations aimed at reducing electrostatic drift wave-driven turbulent transport will need to consider UIs if β is sufficiently small.

Duff, J. M. (ORCID:0000000153086694)↗
DOE OSTI2024

In-situ heating-and-electron tomography for materials research: from 3D ( In-situ 2D) to 4D ( In-situ 3D)

In-situ observation has expanded the application of transmission electron microscopy (TEM) and has made a significant contribution to materials research and development for energy, biomedical, quantum, etc. Recent technological developments related to in-situ TEM have empowered the incorporation of three-dimensional observation, which was previously considered incompatible. In this review article, we take up heating as the most commonly used external stimulus for in-situ TEM observation and overview recent in-situ TEM studies. Then, we focus on the electron tomography (ET) and in-situ heating combined observation by introducing the authors’ recent research as an example. Assuming that in-situ heating observation is expanded from two dimensions to three dimensions using a conventional TEM apparatus and a commercially available in-situ heating specimen holder, the following in-situ heating-and-ET observation procedure is proposed: (i) use a rapid heating-and-cooling function of a micro-electro-mechanical system holder; (ii) heat and cool the specimen intermittently and (iii) acquire a tilt-series dataset when the specimen heating is stopped. This procedure is not too technically challenging and can have a wide range of applications. Essential technical points for a successful 4D (space and time) observation will be discussed through reviewing the authors’ example application.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Soft matter and nanomaterials characterization by cryogenic transmission electron microscopy

Soft matter has historically been an unlikely candidate for investigation by electron microscopy techniques due to damage by the electron beam as well as inherent instability under a high vacuum environment. Characterization of soft matter has often relied on ensemble-scattering techniques. The recent development of cryogenic transmission electron microscopy (cryo-TEM) provides the soft matter community with an exciting opportunity to probe the structure of soft materials in real space. Cryo-TEM reduces beam damage and allows for characterization in a native, frozen-hydrated state, providing direct visual representation of soft structure. This article reviews cryo-TEM in soft materials characterization and illustrates how it has provided unique insights not possible by traditional ensemble techniques. Soft matter systems that have benefited from the use of cryo-TEM include biological-based “soft” nanoparticles (e.g., viruses and conjugates), synthetic polymers, supramolecular materials as well as the organic–inorganic interface of colloidal nanoparticles. We conclude that while many challenges remain, such as combining structural and chemical analyses; the opportunity for soft matter research to leverage newly developed cryo-TEM techniques continues to excite.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Universal liquid sample device and process for high resolution transmission electron microscope imaging and multimodal analyses of liquid sample materials

Liquid sample imaging devices and processes are disclosed for high resolution TEM imaging and multimodal analyses of liquid sample materials in situ under high vacuum that are compatible with standard type TEM chip membranes and TEM sample holders allowing TEM liquid sample imaging to be performed wherever a TEM instrument is accessible and at a substantially reduced cost compared to prior art systems and approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Responses of Boreal Forest Ecosystems and Permafrost to Climate Change and Disturbances: A Modeling Perspective

The north circumpolar region contains a large amount of carbon. This carbon storage is vulnerable due to permafrost degradation and wildfire disturbances under ongoing and projected climate change. Climate warming and wildfires change soil organic horizons gradually or abruptly, and modify permafrost thermal-hydrology and biogeochemistry, ecosystem structures, functions, and capability of sequestrating rising atmospheric CO2. Land models do not fully take accounts of these interactions and its complexity in the high latitude. This chapter describes a terrestrial ecosystem model with dynamic organic soil module (DOS-TEM) and its unique freezing-thawing algorithm, and presents key results of its applications mainly in boreal forests of Alaska. The DOS-TEM explicitly considers interactions of soil thermal and hydrological processes, permafrost degradation and the direct and indirect effects of wildfire disturbances, in addition to soil–plant C and N cycles. We first introduce four modules of DOS-TEM, focusing on its disturbance module and coupling with a dynamic organic soil module. Then we describe and validate DOS-TEM’s freezing-thawing algorithm and development based on two-directional Stefan algorithm (TDSA). Finally, we apply the DOS-TEM at site and region scales, with a focus on model ability to dynamically simulate soil organic thickness under warming and wildfires, and consequent impacts on permafrost in the Yukon River Basin. We conclude that land surface model development is urgently needed to include other critical landscape processes, such as thermalkarst and other disturbances, to synchronize thermal-hydrological-biogeochemical processes, and to incorporate an advanced understanding of biospheric feedbacks to atmosphere and ecosystems. Such a complexity of modeling scope is plausible with advancement of high performance computing.

Yi, Shuhua↗
DOE OSTI2026

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

Bacteria rapidly adapt to environmental cues through morphological and ultrastructural changes that correlate with physiology and behavior. Cryogenic transmission electron microscopy (cryo‐TEM) can capture these phenotypic changes in near‐native, vitrified states, but manual analysis of low‐dose micrographs is labor intensive and limits throughput. Here, we present an end‐to‐end workflow that combines low‐dose cryo‐TEM imaging with a YOLOv11‐based instance‐segmentation model to automatically identify bacteria and quantify key structural features directly from the micrographs. This workflow enables (i) robust bacterial localization and counting from low‐magnification atlas/montage images, (ii) automated measurements of cell‐envelope (outer–inner membrane) thickness and anisotropy from higher‐magnification views, and (iii) detection and quantification of bacteria–flagella interactions, including overlap length and curvature metrics for interacting versus noninteracting flagella. Using Pantoea sp. YR343 grown under distinct media conditions, we show that the automated measurements agree with manual annotations while substantially reducing analysis time. Together, these tools provide a practical framework for scalable bacterial identification and quantitative phenotyping in low‐dose cryo‐TEM datasets and establish a foundation for extending cryo‐TEM image analysis toward higher‐throughput studies of microbial heterogeneity and biointerfaces.

YOLOv11↗