Universal prediction of strain footprints via simulation, statistics, and machine learning: low-Σ grain boundaries
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DOI: 10.1016/j.actamat.2021.116850
Abstract: Abstract Interface engineering usually imposes a trade-off between catalytic activity, product selectivity, and property tunability, facilitating multiple product yields. Due to their structural disorder, metal grain boundaries (GBs) can be constructed to satisfy all of… read more here.
Keywords: grain boundaries; gbs; strain footprints; machine learning ... See more keywords