14 citations · 18 across the 3 of their papers we have counts for
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cond-mat.mtrl-sci2023★ 3 cited
Predicting emergence of crystals from amorphous matter with deep learning
Muratahan Aykol, Amil Merchant, Simon Batzner +2
Crystallization of the amorphous phases into metastable crystals plays a fundamental role in the formation of new matter, from geological to biological processes in nature to synth…
cond-mat.mtrl-sci2023★ 1 cited
Accurate Surface and Finite Temperature Bulk Properties of Lithium Metal at Large Scales using Machine Learning Interaction Potentials
Mgcini Keith Phuthi, Archie Mingze Yao, Simon Batzner +4
The properties of lithium metal are key parameters in the design of lithium ion and lithium metal batteries. They are difficult to probe experimentally due to the high reactivity a…