382 citations · 1.1k across the 19 of their papers we have counts for
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physics.chem-ph2023★ 21 cited
Developing machine-learned potentials to simultaneously capture the dynamics of excess protons and hydroxide ions in classical and path integral simulations
Austin O. Atsango, Tobias Morawietz, Ondrej Marsalek +1
The transport of excess protons and hydroxide ions in water underlies numerous important chemical and biological processes. Accurately simulating the associated transport mechanism…
physics.chem-ph2023★ 18 cited
Reducing the cost of neural network potential generation for reactive molecular systems
Krystof Brezina, Hubert Beck, Ondrej Marsalek
Although machine-learning potentials have recently had substantial impact on molecular simulations, the construction of a robust training set can still become a limiting factor, es…