most citedAccelerating crystal structure prediction by machine-learning interatomic potentials with active learning

403 citations · 409 across the 2 of their papers we have counts for

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2 papers

cond-mat.mtrl-sci2018★ 403 cited

Accelerating crystal structure prediction by machine-learning interatomic potentials with active learning

Evgeny V. Podryabinkin, Evgeny V. Tikhonov, Alexander V. Shapeev +1

In this letter we propose a new methodology for crystal structure prediction, which is based on the evolutionary algorithm USPEX and the machine-learning interatomic potentials act…

cond-mat.mes-hall2016★ 6 cited

Electron correlations and silicon nanocluster energetics

N. L. Matsko, Yu. A. Uspenskii, E. V. Tikhonov +2

The first-principle prediction of nanocluster stable structure is often hampered by the existence of many isomer configurations with energies close to the ground state. This fact a…