Deep learning modeling in microscopy imaging: A review of materials science applications
The accurate analysis of microscopy images representing various materials obtained in
scanning probe microscopy, scanning tunneling microscopy, and transmission electron …
scanning probe microscopy, scanning tunneling microscopy, and transmission electron …
A review of application of machine learning in design, synthesis, and characterization of metal matrix composites: current status and emerging applications
In this article we provide an overview on the current and emerging applications of machine
learning (ML) in the design, synthesis, and characterization of metal matrix composites …
learning (ML) in the design, synthesis, and characterization of metal matrix composites …
Detecting lithium plating dynamics in a solid-state battery with operando X-ray computed tomography using machine learning
Y Huang, D Perlmutter, A Fei-Huei Su… - npj Computational …, 2023 - nature.com
Operando X-ray micro-computed tomography (µCT) provides an opportunity to observe the
evolution of Li structures inside pouch cells. Segmentation is an essential step to …
evolution of Li structures inside pouch cells. Segmentation is an essential step to …
Physics-informed neural network frameworks for crack simulation based on minimized peridynamic potential energy
L Ning, Z Cai, H Dong, Y Liu, W Wang - Computer Methods in Applied …, 2023 - Elsevier
Physics-informed neural networks (PINNs), which are promising tools for solving nonlinear
equations in the absence of labeled data, have been successfully applied for continuum …
equations in the absence of labeled data, have been successfully applied for continuum …
Accelerated materials design using batch Bayesian optimization: A case study for solving the inverse problem from materials microstructure to process specification
Microstructure-based process design is one of the main ingredients for materials design,
under the integrated computational materials engineering paradigm, which relies on …
under the integrated computational materials engineering paradigm, which relies on …
Machine learning pipeline for segmentation and defect identification from high-resolution transmission electron microscopy data
CK Groschner, C Choi, MC Scott - Microscopy and Microanalysis, 2021 - academic.oup.com
In the field of transmission electron microscopy, data interpretation often lags behind
acquisition methods, as image processing methods often have to be manually tailored to …
acquisition methods, as image processing methods often have to be manually tailored to …
Deep learning for three-dimensional segmentation of electron microscopy images of complex ceramic materials
Y Hirabayashi, H Iga, H Ogawa, S Tokuta… - npj Computational …, 2024 - nature.com
The microstructure is a critical factor governing the functionality of ceramic materials.
Meanwhile, microstructural analysis of electron microscopy images of polycrystalline …
Meanwhile, microstructural analysis of electron microscopy images of polycrystalline …
A unified microstructure segmentation approach via human-in-the-loop machine learning
Microstructure segmentation, a technique for extracting structural statistics from microscopy
images, is an essential step for establishing quantitative structure–property relationships in a …
images, is an essential step for establishing quantitative structure–property relationships in a …
Complexity and evolution of a three-phase eutectic during coarsening uncovered by 4D nano-imaging
We investigate the coarsening dynamics of the three-phase eutectic Al-Ag 2 Al-Al 2 Cu at
723 K via in situ transmission X-ray nano-tomography. Unlike previous investigations that …
723 K via in situ transmission X-ray nano-tomography. Unlike previous investigations that …
Homogenization-informed convolutional neural networks for estimation of li-ion battery effective properties
Lithium-ion batteries (LIB) are inherently multiscale and multiphysics systems. Coarse-
grained models, which represent electrode components as overlapping continua, allow one …
grained models, which represent electrode components as overlapping continua, allow one …