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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Relationship of Chemical Composition and Moisture Sensitivity in LiNi x Mn y Co 1-x-y O 2 for Lithium-Ion Batteries

Chemical composition–moisture sensitivity relationship of LiNi x Mn y Co 1-x-y O 2 (NMC) cathode materials was investigated by exploring crystal structures, surface properties, and electrochemical performance behaviors of various commercial NMC powders: LiNi 1/3 Mn 1/3 Co 1/3 O 2 (NMC111), LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532), LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622), and LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811). The NMC powders were stored in different moisture conditions: moisture-free, humidified air, or immersed in water. Rietveld refinement analysis of X-ray diffraction (XRD) data and scanning electron microscopy (SEM) were used to characterize the crystal structure changes and the evolution of particle surfaces morphologies. The effect of moisture contamination on the electrochemical properties of NMC cathodes was studied by galvanostatic cycling and electrochemical impedance spectroscopy (EIS). The moisture contamination resulted in either structural disorder or unwanted surficial deposition products, which increased a charge-transfer impedance and consequent performance degradation of battery cells. The results showed that NMC’s moisture vulnerability increased with Ni content (x) despite protective coatings on commercial particles, which stressed the necessity of alternative surface passivation strategies of Ni-rich NMC for broad applications such as electric vehicles and electrified aircraft propulsion.

25 ENERGY STORAGE↗
DOE OSTI2022

Automatic Calibration of a Geomechanical Model from Sparse Data for Estimating Stress in Deep Geological Formations

Summary In this study, we demonstrate geomechanical modeling with fully automatic parameter calibration to estimate the full geomechanical stress fields of a prospective US carbon dioxide (CO2) storage site, based on sparse measurement data. The goal is to compute full stress tensor field estimates (principal stresses and orientations) that are maximally compatible with observations within the constraints of the model assumptions, thereby extending pointwise, incomplete partial stress measurement to a simulated full formation stress field, as well as a rough assessment of the associated error. We use the Perch site, located in Otsego County, Michigan, USA, as our case study. The input data consist of partial stress tensor information inferred from in-situ borehole tests, geophysical well logs, and processing of seismic data. A static earth model (SEM) of the site was developed, and geomechanical simulation functionality of the open-source MATLAB Reservoir Simulation Toolbox (MRST) was used to model the stress field. Adjoint-based nonlinear optimization was used to adjust boundary conditions and material properties to calibrate simulated results of observations. Results were interpreted through a Bayesian framework. The focus of this paper is to demonstrate how the fully automatic calibration procedure works and discuss the results obtained; it does not attempt a detailed analysis of the stress field in the context of the proposed CO2 storage initiatives. Our work is part of a larger effort to noninvasively determine in-situ stresses in deep formations considered for CO2 storage. Guided by previously published research on geomechanical model calibration, our work presents a novel calibration approach supporting a potentially large number of linear or nonlinear calibration parameters to produce results optimally agreeing with available measurements and thus extend partial pointwise estimates to full tensor fields compatible with the physics of the site.

Engineering↗
NASA NTRS1988

Constraints on the origin of Archean trondhjemites based on phase relationships of Nuk gneiss with H2O at 15 kbar

Constraints on the origin of Archean trondhemites were investigated by studying the T-X(H2O) phase relationships, as a function of water content, of the trondhjemitic Nuk gneiss (the principal component of the second phase of Archean igneous activity in the Godthab region, Greenland) with water at 15-kbar pressure. High-pressure experiments were completed in a piston-cylinder apparatus wih samples enclosed in gold capsules, and phase assemblages exposed on polished surfaces of run products and analyzed using optical microscope, SEM, and electron microprobe. The data obtained were found to be consistent with the multistage development model for the Archean crust in Finland, developed by Jahn et al. (1984), which calls for at least three stages of crustal development.

Johnston, A. Dana↗
DOE OSTI2025

Bridging multimodal microscopy for advanced characterization on nuclear fuel using machine learning

Uranium dioxide (UO 2 ), widely used as driver fuel in light water reactors, experiences microstructure and property change by nuclear fission reactions. This paper bridges the characterization of fresh UO 2 fuel at different length scales, serving as a baseline for future post irradiation examination of irradiated UO 2 fuel. To characterize the microstructural change of nuclear fuel, modern approaches cover a wide range of length scales through different characterization techniques, such as mm scale for Synchrotron-based X-ray computed tomography (SXCT) and microscale for focused ion beam (FIB) and scanning electron microscopy (SEM). It is challenging to bridge the data and knowledge of the same sample in different length scales. This paper proposed a deep learning framework leveraging transfer learning to detect microstructural defects, trained from a sparse FIB, SEM, and SXCT images. The proposed model achieved superior performance in defect segmentation on multiscale microscopic data compared to four of the latest deep learning models.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Energy Leaders: The Catalyst for Strategic Energy Management

This study investigates the crucial role energy leaders play in driving strategic energy management (SEM) and accelerating cost savings within a manufacturing organization and consequently, the industrial sector. Whereas energy efficiency can be seen as an innovative business practice with irrefutable cost benefits, its effective implementation requires strategic leadership and a structured approach. This research analyzes data collected from 120 participants representing 71 companies attending the Energy Bootcamp events organized by the U.S. Department of Energy’s (DOE) Better Plants program. The collected data focused on the state of SEM implementation, the presence and responsibilities of energy leaders, and the formation and function of energy teams. The findings reveal a significant gap between the perceived importance of SEM and its actual adoption, highlighting the need for strong leadership to drive behavioral changes by championing energy efficiency initiatives. Results indicate that effective energy leaders possess a diverse skill set, including the ability to secure top management buy-in, foster a culture of energy consciousness, and collaborate across departments. This study emphasizes the importance of empowering energy leaders with clearly defined roles and responsibilities as well as the authority to build and lead cross-functional energy teams. Furthermore, integrating energy management into existing organizational structures and leveraging readily available resources are identified as key factors for successful implementation. This research underscores how dedicated leadership and effective SEM practices help achieve industrial energy efficiency goals, providing practical insights for organizations seeking to improve performance and contribute to a resilient future.

energy leader↗
NASA NTRS1992

Effects of the LDEF environment on the Ag/FEP thermal blankets

This presentation was made by Francois Levadou at the NASA Langley Research Center LDEF materials workshop, November 19-22, 1991. It represents the results to date on the examination of silvered teflon thermal blankets primarily from the Ultra-heavy Cosmic Ray Experiment and also from the blanket from the Park Seed Company experiment. ESA/ESTEC and Boeing conducted a number of independent measurements on the blankets and in particular on the exposed fluorinated ethylene-propylene (FEP) layer of the blankets. Mass loss, thickness, and thickness profile measurements have been used by ESA, Boeing, and NASA LeRC to determine recession and average erosion yield under atomic oxygen exposure. Tensile strength and percent elongation to failure data, surface characterization by ESCA, and SEM images are presented. The Jet Propulsion Laboratory analysis of vacuum radiation effects is also presented. The results obtained by the laboratories mentioned and additional results from the Aerospace Corporation on samples provided by Boeing are quite similar and give confidence in the validity of the data.

Levadou, Francois↗
DOE OSTI2026

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗
NASA NTRS1995

Space Experiment Module: A new low-cost capability for education payloads

The Space Experiment Module (SEM) concept is one of a number of education initiatives being pursued by the NASA Shuttle Small Payloads Project (SSPP) in an effort to increase educational access to space by means of Space Shuttle Small Payloads and associated activities. In the SEM concept, NASA will provide small containers ('modules') which can accommodate small zero-gravity experiments designed and constructed by students. A number, (nominally ten), of the modules will then be flown in an existing Get Away Special (GAS) carrier on the Shuttle for a flight of 5 to 10 days. In addition to the module container, the NASA carrier system will provide small amounts of electrical power and a computer system for controlling the operation of the experiments and recording experiment data. This paper describes the proposed SEM carrier system and program approach.

Goldsmith, Theodore C.↗
DOE OSTI2025

Layer-by-layer growth of graphene oxide multilayers using robust interlayer linking chemistry. 1. Zr-bisphosphates

Graphene oxide (GO) holds substantial interest because of its utility in applications ranging from chemical sensing to catalysis and energy storage. We report on the layer-by-layer formation of graphene oxide phosphate (P-GO) multilayers on silica and oxidized silicon supports, with the layers connected via Zr-bisphosphate (ZP) linking chemistry. Layers were grown either directly by ZP linkages between P-GO sheets, or with the use of 1,4-phenylene bisphosphate (BP1) or [1,1′-biphenyl]4,4′-diyl bisphosphate (BP2). The layers have been characterized using optical null ellipsometry, X-ray photoelectron spectroscopy (XPS), UV-visible absorption spectroscopy and scanning electron microscopy (SEM). There is a linear dependence of assembly thickness on the number of layers deposited and the integrated area of the optical absorbance bands also increases linearly with number of layers deposited. XPS data provides information on interlayer linking stoichiometry. SEM images provide insight into the morphology of the adlayers, suggesting the structure and length of the interlayer linking moieties used in the multilayer assembly play a significant role in the organization of the resulting system.

Mukherjee, Neelanjana [Michigan State University, ↗
NASA NTRS2015

Microstructure-Sensitive Investigation of Fracture Using Acoustic Emission Coupled With Electron Microscopy

A novel technique using Scanning Electron Microscopy (SEM) in conjunction with Acoustic Emission (AE) monitoring is proposed to investigate microstructure-sensitive fatigue and fracture of metals. The coupling between quasi in situ microscopy with actual in situ nondestructive evaluation falls into the ICME framework and the idea of quantitative data-driven characterization of material behavior. To validate the use of AE monitoring inside the SEM chamber, Aluminum 2024-B sharp notch specimen were tested both inside and outside the microscope using a small scale mechanical testing device. Subsequently, the same type of specimen was tested inside the SEM chamber. Load data were correlated with both AE information and observations of microcracks around grain boundaries as well as secondary cracks, voids, and slip bands. The preliminary results are in excellent agreement with similar findings at the mesoscale. Extensions of the application of this novel technique are discussed.

Wisner, Brian↗
NASA NTRS2018

Effect of Thin-Film Adhesives on Mode I Interlaminar Fracture Toughness in Carbon Fiber Composites with Shape Memory Alloy Inserts

A single sheet of NiTi shape memory alloy (SMA) was introduced within a unidirectional HexPly® 8552/IM7 (Hexcel®) polymer matrix composite (PMC) panel in conjunction with multiple thin-film adhesives to promote the interfacial bond strength between the SMA and PMC. A double cantilever beam (DCB) test was performed in accordance with the ASTM D5528 method for evaluation of Mode I interlaminar fracture toughness of unidirectional fiber-reinforced PMCs. The modal acoustic emissions (MAEs) were monitored during testing with two acoustic sensors attached to the specimens. The composite panels were subjected to a C-scan before testing and examined using optical and scanning electron microscopy (SEM) techniques after part failure. The data were used in conjunction with modified beam theory (MBT), the compliance calibration (CC) method, and the modified compliance calibration (MCC) method. The Mode I interlaminar toughness (G(sub IC)) values for control specimens were higher than previously reported and are attributed to extensive fiber bridging during testing. The presence of adhesives with SMA inserts stabilized crack propagation during DCB testing. The results reveal a new phenomenon of SMA bridging, whereby crack propagation would switch from one side of the SMA insert to the other, thus increasing the load and G(sub IC) values of specimens containing SMA.

shape memory alloys↗
NASA NTRS1978

Scanning microscopy in microcircuit failure analysis

A three-phase microcircuit failure analysis procedure is presented. In the first phase, the device is nondestructively tested and the data obtained is correlated with the circumstances surrounding the failure event. The device is then subjected to a limited nondestructive analysis dominated by optical and scanning electron microscopy (SEM). Knowing that microcircuits usually fail from manufacturing defects or misuse, the analyst looks for one of the probable mechanisms. The SEM has two special operating modes that provide unique data for nondestructive analysis: voltage contrast and conductive current. These are used with other SEM modes and surface analysis techniques to analyze complicated microcircuits. The last phase includes the destructive procedures. The end product of these analyses is a corrective action that will yield a highly reliable system.

Nicolas, D. P.↗
DOE OSTI2025

AutoEMX v1.

The invention consists in the full automation of compositional analysis of inorganic powder samples by scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS). The measurements and analysis are controlled via python-based software, Auto-SEMEDS. Auto-SEMEDS fully automates the SEM-EDS measurements, and analyses the collected data via the use of machine-learning (ML) algorithms, which have never been used before for such scope. Auto-SEMEDS enables the identification in fully-automated fashion of the individual material phases present in a powder sample. Similar technologies, such as commercial SEM-EDS software, can automatically classify particles based on their composition, but they have significant limitations. These solutions typically provide inaccurate composition measurements and struggle to identify single phases in lab samples, where phases are often closely intermixed. In contrast, Auto-SEMEDS achieves unprecedented accuracy in composition measurements of powder samples, and furthermore leverages machine learning algorithms to effectively discern intermixed phases. Notably, while previous studies have demonstrated accurate measurements on individual particles, Auto-SEMEDS stands out by successfully analyzing mixture of different phases, a capability that has not been reported in the literature until now.

Giunto, Andrea [Lawrence Berkeley National Laborat↗
NASA NTRS1993

The EET87513 clast N: A CM2 fragment in an HED polymict breccia

Xenoliths of material resembling carbonaceous chondrites have been found in several HED polymict breccias. Most workers concluded that these clasts are related to CM2 meteorites on the basis of texture, bulk composition, and mineralogy. Data on clast N, a carbonaceous chondrite fragment from the howardite EET87513 large enough (approximately 4x5mm on the surface of the slab from which it was separated) to extract bulk samples for INAA and oxygen isotope analysis and to provide a thin section for electron microprobe, SEM, and TEM analysis is reported. Preliminary data for this clast were previously reported. INAA was performed at Oregon State University and bulk oxygen isotopic composition was determined at the University of Chicago. These data confirm that EET87513 clast N is a fragment of CM2 material.

Buchanan, P. C.↗
NASA NTRS1984

Petrographic studies of refractory inclusions from the Murchison meteorite

Textural and mineral-chemical data on freeze-thaw disaggregated refractory inclusions from the Murchison meteorite are reported. The data were obtained with neutron activation analysis, SEM, and spectroscopy, the study revealed corundum-bearing inclusions, spinel-hibonite aggregates and spherules, and spinel-pyroxene and elivine-pyroxene inclusions. One of the three spinel-, pyroxene-, forsterite-rich inclusions had an amoeba-shaped spinel-pyroxene core, implying vapor-to-solid condensation and therefore crystallization from a melt. It is concluded that the meteorite formation encompassed diverse nebular materials, and that further studies of the meteorite will enhance the data base on the planetary nebular processes.

Macpherson, G. J.↗
NASA NTRS2005

The Space Shuttle Columbia Accident Investigation and Reconstruction: Two Years Later

The Space Shuttle Columbia was lost during re-entry over two years ago. Since the release of the official materials-related findings in August of 2003, additional testing and analysis of select pieces of debris has continued. Microanalytical techniques, including EMPA, ESCA, and x-ray elemental dot mapping, were employed during the initial investigation; the results related the microstructural characteristics of deposit layers to the breach location in the leading edge of the left wing. Such characteristics included deposition order, composition, and distribution. Subsequent to the original efforts, new analytical data and information, not available at the time of the primary investigation, has been generated. This data was obtained via a low-vacuum SEM, fitted not only with a light-element EDS detector, but an XRF tube as well. Essentially, for elements up to sodium, classic EDS was utilized; above sodium, XRF was used. Predominantly, the elements of interest were aluminum, titanium, chromium, iron, nickel, and copper. The findings of both old and new data are compared, and their application to the overall accident investigation detailed.

McDanels, Steven J.↗