252 citations · 559 across the 12 of their papers we have counts for
12 papers
On the Variability of Grain Boundary Mobility in the Isoconfigurational Ensemble
Anqi Qiu, Ian Chesser, Elizabeth Holm
Recent grain growth experiments have revealed that the same type of grain boundary can have very different mobilities depending on its local microstructure. In this work, we use mo…
Optimal transportation of grain boundaries: A forward model for predicting migration mechanisms
Ian Chesser, Elizabeth Holm, Brandon Runnels
It has been hypothesized that the most likely atomic rearrangement mechanism during grain boundary (GB) migration is the one that minimizes the lengths of atomic displacements in t…
Microstructure Generation via Generative Adversarial Network for Heterogeneous, Topologically Complex 3D Materials
Tim Hsu, William K. Epting, Hokon Kim +5
Using a large-scale, experimentally captured 3D microstructure dataset, we implement the generative adversarial network (GAN) framework to learn and generate 3D microstructures of…
Overview: Computer vision and machine learning for microstructural characterization and analysis
Elizabeth A. Holm, Ryan Cohn, Nan Gao +4
The characterization and analysis of microstructure is the foundation of microstructural science, connecting the materials structure to its composition, process history, and proper…
High throughput quantitative metallography for complex microstructures using deep learning: A case study in ultrahigh carbon steel
Brian L. DeCost, Bo Lei, Toby Francis +1
We apply a deep convolutional neural network segmentation model to enable novel automated microstructure segmentation applications for complex microstructures typically evaluated m…
A comparative study of feature selection methods for stress hotspot classification in materials
Ankita Mangal, Elizabeth A. Holm
The first step in constructing a machine learning model is defining the features of the data set that can be used for optimal learning. In this work we discuss feature selection me…