Machine-learning informed prediction of high-entropy solid solution formation: Beyond the Hume-Rothery rules
Abstract
The empirical rules for the prediction of solid solution formation proposed so far in the literature usually have very compromised predictability. Some rules with seemingly good predictability were, however, tested using small data sets. Based on an unprecedented large dataset containing 1252 multicomponent alloys, machine-learning methods showed that the formation of solid solutions can be very accurately predicted (93%). The machine-learning...
Paper Details
Title
Machine-learning informed prediction of high-entropy solid solution formation: Beyond the Hume-Rothery rules
Published Date
May 7, 2020
Journal
Volume
6
Issue
1
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