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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Computationally Guided Development of Components for High Energy Density Solid-State Lithium-Sulfur Batteries

All electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The most challenging of these technical barriers to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria1. The performance metrics for eVTOL craft, such as specific energy, specific power, and safety, exceed those of electric automobiles by a factor of two to four. Current state-of-the-art (SOA) lithium-ion batteries are incapable of meeting the key performance criteria of energy and safety for eVTOL. Therefore, next generation advanced chemistries and designs must be developed to meet required performance metrics for electric aviation2. Beyond lithium-ion chemistries, such as lithium-sulfur, show promise in their high energy, while limitations exist in their power and cyclability due to low electrical conductivity and high intermediate solubility in organic liquid electrolytes. Several strategies to overcome the low electrical conductivity involve the use of selenium as a dopant in the active sulfur material, along with the incorporation of 2-dimensional electron-conducting holey-graphene to improve the composite cathodes electronic conductivity. Furthermore, combining this chemistry with a solid-electrolyte avoids the components’ dissolution issues3. However, the development of composite solid-state cathodes is non-trivial as several components must be intimately mixed so that the active component has sufficient access to both electrons and lithium ions to undergo full electrochemical conversion. Mathematical modeling of battery components can assist experimental design through a robust and rigorous combination of computational modeling techniques covering multiple length scales. The objective is to leverage modern computational materials methods combined with battery multiphysics tools to develop radically advanced compatible cathode and electrolyte materials, build and test solid state lithium-sulfur cells and packs. A NASA-based cross-organizational team of high-powered experts combined integrated computational predictive modeling, fundamental chemistry analysis, advanced material science, and battery cell development to tackle this very challenging, multidisciplinary problem. This presentation will show a multiscale computational modeling approach that has produced a novel particle dynamics method called Solid Electrolyte Sphere Approximation Model (SESAM). SESAM modeling targets the 1-10 µm scale structures and provides electromechanical and grain interactions for predictive design guidelines for the manufacturing of solid-state components. Parameters such as particle size and volume fraction of the constituent materials were modeled and experimentally fabricated to optimize electrochemical performance through improved microstructure design. Experimental feedback was provided through ionic and electronic conductivity assessment and structural analysis of developed materials and cell components.

battery↗
DOE OSTI2013

Efficient simulation of press hardening process through integrated structural and CFD analyses

Press hardened steel parts are being increasingly used in automotive structures for their higher strength to meet safety standards while reducing vehicle weight to improve fuel consumption. However, manufacturing of sheet metal parts by press hardening process to achieve desired properties is extremely challenging as it involves complex interaction of plastic deformation, metallurgical change, thermal distribution, and fluid flow. Numerical simulation is critical for successful design of the process and to understand the interaction among the numerous process parameters to control the press hardening process in order to consistently achieve desired part properties. Until now there has been no integrated commercial software solution that can efficiently model the complete process from forming of the blank, heat transfer between the blank and tool, microstructure evolution in the blank, heat loss from tool to the fluid that flows through water channels in the tools. In this study, a numerical solution based on Altair HyperWorks® product suite involving RADIOSS®, a non-linear finite element based structural analysis solver and AcuSolve®, an incompressible fluid flow solver based on Galerkin Least Square Finite Element Method have been utilized to develop an efficient solution for complete press hardening process design and analysis. RADIOSS is used to handle the plastic deformation, heat transfer between the blank and tool, and microstructure evolution in the blank during cooling. While AcuSolve is used to efficiently model heat loss from tool to the fluid that flows through water channels in the tools. The approach is demonstrated through some case studies.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Microstructural characterization of high-manganese austenitic steels with different stacking fault energies

Microstructures of tensile-deformed high-manganese austenitic steels exhibiting twinning-induced plasticity were analyzed by electron backscatter diffraction pattern observation and X-ray diffraction measurement to examine the influence of differences in their stacking fault energies on twinning activity during deformation. The steel specimen with the low stacking fault energy of 15 mJ/m{sup 2} had a microstructure with a high population of mechanical twins than the steel specimen with the high stacking fault energy (25 mJ/m{sup 2}). The <111> and <100> fibers developed along the tensile axis, and mechanical twinning occurred preferentially in the <111> fiber. The Schmid factors for slip and twinning deformations can explain the origin of higher twinning activity in the <111> fiber. However, the high stacking fault energy suppresses the twinning activity even in the <111> fiber. A line profile analysis based on the X-ray diffraction data revealed the relationship between the characteristics of the deformed microstructures and the stacking fault energies of the steel specimens. Although the variation in dislocation density with the tensile deformation is not affected by the stacking fault energies, the effect of the stacking fault energies on the crystallite size refinement becomes significant with a decrease in the stacking fault energies. Moreover, the stacking fault probability, which was estimated from a peak-shift analysis of the 111 and 200 diffractions, was high for the specimen with low stacking fault energy. Regardless of the difference in the stacking fault energies of the steel specimens, the refined crystallite size has a certain correlation with the stacking fault probability, indicating that whether the deformation-induced crystallite-size refinement occurs depends directly on the stacking fault probability rather than on the stacking fault energies in the present steel specimens. - Highlights: {yields} We studied effects of stacking fault energies on deformed microstructures of steels. {yields} Correlations between texture and occurrence of mechanical twinning are discussed. {yields} Evolutions of dislocations and crystallite are analyzed by line profile analysis.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Thermal stability of the microstructure of an aged Nb-Zr-C alloy

The effects of thermal aging with and without an applied stress on the microstructure of a Nb-Zr-C alloy containing 0.9 wt percent Zr and 0.06 percent C were studied. Chemical analysis, metallographic examination, energy dispersive X-ray spectra of the bulk material, and chemical and X-ray analyses of the phase-extracted residue were used to characterize the microstructure. The samples examined were from a creep strength study involving hot and cold working, and various combinations of exposure to temperatures ranging from 1350 to 1755 K with and without applied load times as long as 34,000 plus hours. The results showed that the initial microstructure consisted primarily of orthorombic precipitates of Nb sub C which were partially or completely transformed to face-centered cubic carbides of Nb and Zr, (Zr, Nb)C, upon prolonged exposure to elevated temperatures. Furthermore, it was found that the microstructure of the alloy is extremely stable owing to the very finely distributed precipitates throughout its matrix and along the grain boundaries. The lattice parameters of the cubic carbides were determined to vary from 0.458 to 0.465 nm as the Zr/Nb ratio varied from 38/62 to 75/25.

Uz, Mehmet↗
DOE OSTI2012

Full quantitative phase analysis of hydrated lime using the Rietveld method

Full quantitative phase analysis (FQPA) using X-ray powder diffraction and Rietveld refinements is a well-established method for the characterization of various hydraulic binders such as Portland cement and hydraulic limes. In this paper, the Rietveld method is applied to hydrated lime, a non-hydraulic traditional binder. The potential presence of an amorphous phase in this material is generally ignored. Both synchrotron radiation and a conventional X-ray source were used for data collection. The applicability of the developed control file for the Rietveld refinements was investigated using samples spiked with glass. The results were cross-checked by other independent methods such as thermal and chemical analyses. The sample microstructure was observed by transmission electron microscopy. It was found that the consistency between the different methods was satisfactory, supporting the validity of FQPA for this material. For the samples studied in this work, the amount of amorphous material was in the range 2-15 wt.%.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Utah FORGE: Well 16A(78)-32 Core Analysis Results

This dataset features petrographic, X-Ray Diffraction (XRD), and Scanning Electron Microscopy Analyses of core samples from well 16A(78)-32, which serves as the injection well for the Utah FORGE Enhanced Geothermal System (EGS) project. In addition to an overview of the analysis, the following items have been included here: images of 21 entire thin sections in plane-polarized and cross-polarized light from 16 depths, scanning electron microscope back scatter electron photomosaic maps of 21 thin sections from 16 depths, bulk XRD data from 16 depths, clay-sized XRD patterns from 16 depths, an optical petrography report, and scanning electron microscopy and energy dispersive spectroscopy analyses of eight selected samples.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Very High Cycle Fatigue of a Cast Aluminum Alloy: Size Effect and Crack Initiation

Fatigue properties of an Al-Si-Cu cast alloy were investigated with life up to very high cycle fatigue regime. Particular attention was given to specimen size effect and fatigue crack initiation mechanism. Uniaxial fatigue tests with constant amplitudes were carried out by using ultrasonic fatigue testing machine operating at 20 kHz, compared to the results obtained by using conventional hydraulic fatigue machine at 35 Hz. In order to evaluate the size effect, two sets of specimens with different dimensions were used. The results show that the fatigue strength of the studied alloy decreases with the increase in specimen size. Scanning electron microscopy observation of fracture surfaces revealed that most fatigue cracks initiated from microstructural defects such as porosity located on specimen surface or in subsurface. Weibull statistical analysis of fatigue data accounting for size effect was performed to predict the fatigue life of the Al-Si-Cu alloy in the very high cycle regime. Good agreement was found between the fatigue life prediction and the experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Microstructure study of U–35 wt.% Zr alloy after quick annealing at 650 °C

Uranium-35wt.%zirconium (U-35wt.%Zr) alloy was annealed for 1 hour and 24 hours at 650 ºC and characterized to understand the early stage microstructure evolution. Dendritic microstructure with fine (~300 nm in length) α-U precipitates clustered between dendrite branches were observed in the 1-hour annealed sample. After 24-hour annealing 650 ºC, the α-U precipitates coarsened, and the dendritic microstructure disappeared due to microstructure homogenization. Furthermore, microchemical homogenization observed with Energy-Dispersive X-ray Spectroscopy analysis suggests that α-U precipitates are approaching thermodynamic equilibrium in the 24-hour annealed sample. The findings from this study have potential impacts on the manufacturing and computer modeling of metallic nuclear fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Formation and Properties of Locally Tensile Strained Ge Microstructures for Silicon Photonics

The formation and properties of locally tensile strained Ge microstructures (“microbridges”) based on Ge layers grown on silicon substrates are investigated. The elastic-strain distribution in suspended Ge microbridges is analyzed theoretically. This analysis indicates that, in order to attain the maximum tensile strain within a microbridge, the accumulation of strain in all corners of the fabricated microstructure has to be minimized. Measurements of the local strain using Raman scattering show significant enhancement of the tensile strain from 0.2–0.25% in the initial Ge film to ~2.4% in the Ge microbridges. A considerable increase in the luminescence intensity and significant modification of its spectrum in the regions of maximum tensile strain in Ge microbridges and in their vicinity as compared to weakly strained regions of the initial Ge film is demonstrated by microphotoluminescence spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Hot Deformation Behavior and Microstructural Evolution of Antibacterial Austenitic Stainless Steel Containing 3.60% Cu

Hot deformation behavior of as-cast antibacterial austenitic stainless steel containing 3.60% copper was investigated in a temperature range of 900-1150 °C and strain rate range of 0.01-20 s{sup −1}. At strain rates higher than 1 s {sup −1}, the flow stress curves were corrected considering adiabatic heating. Kinetic analysis indicated that the hot deformation activation energy of steel was 376.02 kJ mol{sup −1}. The microstructural evolution under different temperatures was observed by optical microscopy. The nucleation sites for recrystallization and different orientations and twin ratios under different strain rates were analyzed by electron backscatter diffraction. The results showed that hot deformation was dominated by continuous dynamic recrystallization in the high-temperature and high-strain-rate region (1050-1150 °C, 1-20 s{sup −1}). On increasing the temperature and strain rate, the degree of recrystallization and twinning increased simultaneously. These phenomena promoted one another. Thus, the volume fraction of the recrystallized and twinned grains increased with the addition of Cu.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Characterization of Fe-6Si Soft Magnetic Alloy Produced by Laser-Directed Energy Deposition Additive Manufacturing

Abstract Commercial electrical steels, Fe-Si alloys with < 4 wt.% Si, are inexpensive and efficient materials for electrical power conversion. Further efficiency improvements require increasing the silicon concentration to 6 wt.%, at which point the material becomes brittle and difficult to form by conventional rolling and sheet fabrication methods. Additive manufacturing stands to overcome challenges with commercial manufacturing techniques by leveraging near-net-shape fabrication. The wide array of process conditions provides additive manufacturing with increased flexibility, enabling control over the microstructure and mechanical properties. This work explores the microstructures and magnetic properties of ring-shaped Fe-Si alloys produced using concentric and cross-hatch tool paths on a laser-directed energy deposition additive manufacturing system. Concentric-built samples exhibit elongated grain structures while cross-hatch-built samples comprise lower aspect ratio grain structures. Thermal finite element analysis simulations model the stress conditions produced by the different scan path geometries. Microhardness measurements probe the mechanical properties as a function of anneal temperature, providing a qualitative understanding of the intergranular defect density. Soft magnetic properties measured under quasistatic and AC conditions show frequency- and microstructure-dependent coercivity and permeability. Finally, analysis of the core loss quantifies how the build strategies and thermal treatments influence efficiency in electrical power conversion applications. Understanding the influences of scan path geometry and thermal treatment provides a pathway towards application of additively manufactured soft magnetic materials.

Adamczyk, Jesse M.↗
DOE OSTI2014

Synthesis of one-dimensional porous Co{sub 3}O{sub 4} nanobelts and their ethanol gas sensing properties

Graphical abstract: 1D porous porous Co{sub 3}O{sub 4} nanobelts were synthesized via a facile route without use of any surfactants or organic solvent, exhibiting ethanol gas sensing properties superior to the commercial Co{sub 3}O{sub 4} powders. - Highlights: • One-dimensional porous Co{sub 3}O{sub 4} nanobelts were synthesized. • The belt-like morphology can be finely controlled via adjusting the reaction parameters. • The evolution process of porous Co{sub 3}O{sub 4} nanobelts was investigated. • Porous Co{sub 3}O{sub 4} nanobelts exhibit superior ethanol gas sensing properties. - Abstract: In this paper, one-dimensional porous Co{sub 3}O{sub 4} nanobelts were synthesized via a facile template-free hydrothermal method and subsequent the thermal decomposition. Their microstructures and morphologies were characterized by X-ray diffraction, scanning electron microscopy, transmission electron microscopy, thermogravimetric analysis, fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy and N{sub 2} adsorption–desorption techniques. The results indicate that the reaction parameters such as the molar ratio of Co(NO{sub 3}){sub 2}·6H{sub 2}O to C{sub 2}H{sub 4}N{sub 4}, the amount of Co(NO{sub 3}){sub 2}·6H{sub 2}O, the hydrothermal temperature and time play crucial rules in controlling the microstructures and morphologies of the as-prepared cobalt precursors. A possible formation mechanism was proposed. Moreover, the obtained porous Co{sub 3}O{sub 4} nanobelts exhibit ethanol gas sensing properties superior to the commercial Co{sub 3}O{sub 4} powders at a working temperature of 200 °C, suggesting their potential applications as nanosensors.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Advanced 3D characterisation of iodine induced stress corrosion cracks in zirconium alloys

Highlights: • Macroscopic crack direction is affected by metallurgical state. • High resolution XCT reveals complex crack morphology. • 3D-EBSD used to fully characterise attacked grain boundaries. • Evidence of iodine segregation ahead of a crack tip. - Abstract: In this study, a range of advanced techniques have been used to characterise iodine-induced stress corrosion cracks, and investigate their interaction with microstructure in zirconium alloys used as cladding material in nuclear power reactors. C-ring samples, machined from cladding tubes in a recrystallised and cold worked condition, were subjected to compressive stress while submerged in an iodine-ethanol solution to simulate stress corrosion cracks arising from pellet cladding interaction. The complex morphology of these stress corrosion cracks was imaged in 3D using X-ray computed tomography (XCT), and subsequent analysis using both 2D and 3D electron backscatter diffraction (EBSD) allowed for the interaction of these cracks with microstructure to be investigated. Intergranular cracking modes were observed to dominate in the recrystallised microstructure, resulting in cracking in the radial direction with variations on the order of the grain size. Crack propagation in the cold worked microstructure was observed to be correlated with the direction of the elongated grains, resulting in a more tangential crack path with less local variation and a microstructure potentially more susceptible to iodine-induced stress corrosion cracking. 3D-EBSD using serial sectioning allows for the determination of the full five-parameter grain boundary description, and opens up the possibility of a statistical analysis of susceptible boundaries to SCC. Nanoscale secondary ion mass spectrometry (NanoSIMS) was also used to map the chemical distribution in the crack tip region and provides possible evidence of iodine segregation ahead of the crack tip. The results provide new insight into crack propagation mechanisms in recrystallised and cold worked microstructures, and pave the way for a more mechanistic understanding of crack propagation through advanced characterisation of iodine-induced stress corrosion cracks in zirconium alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Critical impact of experimentally-driven strut level anisotropic material models in advanced stress analysis of additively manufactured lattice structures

The rapid acceleration in materials discovery may overshadow the importance of thoroughly understanding the mechanical performance of newly developed materials in demanding environments. The recent interest in combining parametric studies with machine learning techniques to explore how changes in specific processing parameters or model inputs affect the overall behavior of a material system can only be truly beneficial if the governing constitutive relations describing material behavior are accurately established. In this study, we demonstrate the critical impact of accurately representing strut-level anisotropic material behavior in advanced stress analysis of additively manufactured lattice structures (AMLS). We introduce a systematic experimental and modeling approach for developing strut-level anisotropic elastoplastic material models that account for the influence of microstructural features such as porosity, texture, and surface roughness on the development of local anisotropic mechanical properties, which vary with strut orientation relative to the build direction (BD). As a result the presented material model captures and relates the statistics of spatially varying struts’ microstructural features to the local stress distribution. Our findings suggest that incorporating strut-level anisotropic material behavior into unit cell analysis significantly influences the load distribution and evolution of local stresses within the structure. Therefore, accounting for this anisotropy is critical for developing an understanding of unit cell behavior and performance, including subsequent topology/component design optimization based on this analysis.

Sahoo, Subhadip [University of Arizona]↗
DOE OSTI2011

Nanoindentation Studies Of Hard Nanocomposite Ti-B-N Thin Films

Titanium boron nitride (Ti-B-N) films were deposited by reactive magnetron sputtering using single Titanium diboride (TiB{sub 2}) target in different Ar-N{sub 2} gas mixtures. The influence of N{sub 2}:Ar ratio on the microstructure and mechanical properties of the deposited films have been investigated. Atomic force microscopy analysis indicated the grain size decreases with incorporation of nitrogen in the films. Nanoindentation studies have shown the hardness decreases with nitrogen incorporation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗
DOE OSTI2014

Microstructure of multistage annealed nanocrystalline SmCo 2 Fe 2 B alloy with enhanced magnetic properties

The microstructure and chemistry of SmCo 2 Fe 2 B melt-spun alloy after multistage annealing was investigated using high resolution transmission electron microscopy (HRTEM) and 3D atom probe tomography. The multistage annealing resulted in an increase in both the coercivity and magnetization. The presence of Sm(Co,Fe) 4 B (1:4:1) and Sm 2 (Co,Fe) 17 B x (2:17:x) magnetic phases were confirmed using both techniques. Fe 2 B at a scale of -5 nm was found by HRTEM precipitating within the 1:4:1 phase after the second-stage annealing. Ordering within the 2:17:x phase was directly identified both by the presence of antiphase boundaries observed by TEM and the interconnected isocomposition surface network found in 3D atom probe results in addition to radial distribution function analysis. The variations in the local chemistry after the secondary annealing were considered pivotal in improving the magnetic properties.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2021

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

Abstract Automatic segmentation of key microstructural features in atomic-scale electron microscope images is critical to improved understanding of structure–property relationships in many important materials and chemical systems. However, the present paradigm involves time-intensive manual analysis that is inherently biased, error-prone, and unable to accommodate the large volumes of data produced by modern instrumentation. While more automated approaches have been proposed, many are not robust to a high variety of data, and do not generalize well to diverse microstructural features and material systems. Here, we present a flexible, semi-supervised few-shot machine learning approach for segmentation of scanning transmission electron microscopy images of three oxide material systems: (1) epitaxial heterostructures of SrTiO 3 /Ge, (2) La 0.8 Sr 0.2 FeO 3 thin films, and (3) MoO 3 nanoparticles. We demonstrate that the few-shot learning method is more robust against noise, more reconfigurable, and requires less data than conventional image analysis methods. This approach can enable rapid image classification and microstructural feature mapping needed for emerging high-throughput characterization and autonomous microscope platforms.

36 MATERIALS SCIENCE↗