activity
20182026
most citedNeuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport

526 citations · 2k across the 23 of their papers we have counts for

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Showing 2023Show all

2 papers · 1 filter

cond-mat.mtrl-sci2023★ 203 cited

General-purpose machine-learned potential for 16 elemental metals and their alloys

Keke Song, Rui Zhao, Jiahui Liu +25

Machine-learned potentials (MLPs) have exhibited remarkable accuracy, yet the lack of general-purpose MLPs for a broad spectrum of elements and their alloys limits their applicabil…

cond-mat.mtrl-sci2023★ 26 cited

Combining linear-scaling quantum transport and machine-learning molecular dynamics to study thermal and electronic transports in complex materials

Zheyong Fan, Yang Xiao, Yanzhou Wang +3

We propose an efficient approach for simultaneous prediction of thermal and electronic transport properties in complex materials. Firstly, a highly efficient machine-learned neuroe…