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cond-mat.mtrl-sci2020
An Experimentally Driven Automated Machine Learned lnter-Atomic Potential for a Refractory Oxide
Ganesh Sivaraman, Leighanne Gallington, Anand Narayanan Krishnamoorthy +4
Understanding the structure and properties of refractory oxides are critical for high temperature applications. In this work, a combined experimental and simulation approach uses a…
cond-mat.mtrl-sci2019
Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide
Ganesh Sivaraman, Anand Narayanan Krishnamoorthy, Matthias Baur +5
We propose a novel active learning scheme for automatically sampling a minimum number of uncorrelated configurations for fitting the Gaussian Approximation Potential (GAP). Our act…