23 citations · 23 across the 2 of their papers we have counts for
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cond-mat.mtrl-sci2024
Describe, Transform, Machine Learning: Feature Engineering for Grain Boundaries and Other Variable-Sized Atom Clusters
C. Braxton Owens, Nithin Mathew, Tyce W. Olaveson +5
Obtaining microscopic structure-property relationships for grain boundaries are challenging because of the complex atomic structures that underlie their behavior. This has led to r…
cond-mat.mtrl-sci2023
Facet and energy predictions in grain boundaries: lattice matching and molecular dynamics
Bruno Dobrovolski, C. Braxton Owens, Gus L. W. Hart +2
Many material properties can be traced back to properties of their grain boundaries. Grain boundary energy (GBE), as a result, is a key quantity of interest in the analysis and mod…