activity
20192024
most citedMicron-scale heterogeneous catalysis with Bayesian force fields from first principles and active learning

24 citations · 45 across the 6 of their papers we have counts for

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Showing 2022Show all

2 papers · 1 filter

physics.comp-ph2022

Uncertainty Driven Active Learning of Coarse Grained Free Energy Models

Blake R. Duschatko, Jonathan Vandermause, Nicola Molinari +1

Coarse graining techniques play an essential role in accelerating molecular simulations of systems with large length and time scales. Theoretically grounded bottom-up models are ap…

physics.comp-ph2022★ 24 cited

Micron-scale heterogeneous catalysis with Bayesian force fields from first principles and active learning

Anders Johansson, Yu Xie, Cameron J. Owen +4

Quantum-mechanically accurate reactive molecular dynamics (MD) at the scale of billions of atoms has been achieved for the heterogeneous catalytic system of H/Pt(111) using the…