activity
20232026
most citedMachine-learning interatomic potentials from a users perspective: A comparison of accuracy, speed and data efficiency

24 citations · 26 across the 8 of their papers we have counts for

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cond-mat.mtrl-sci2023

Modelling atomic and nanoscale structure in the silicon-oxygen system through active machine learning

Linus C. Erhard, Jochen Rohrer, Karsten Albe +1

Silicon-oxygen compounds are among the most important ones in the natural sciences, occurring as building blocks in minerals and being used in semiconductors and catalysis. Beyond…