252 citations · 559 across the 12 of their papers we have counts for
4 papers · 1 filter
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…
Applied Machine Learning to Predict Stress Hotspots II: Hexagonal close packed materials
Ankita Mangal, Elizabeth A. Holm
Stress hotspots are regions of stress concentrations that form under deformation in polycrystalline materials. We use a machine learning approach to study the effect of preferred s…
Understanding the anomalous thermal behavior of sigma 3 grain boundaries in a variety of FCC metals
Ian Chesser, Elizabeth Holm
We present a case study of the complex temperature dependence of grain boundary mobility. The same general incoherent twin boundary in different FCC metals is found to display anti…