133 citations · 196 across the 12 of their papers we have counts for
4 papers · 1 filter
Nuclear Quantum Effects in Liquid Water Are Negligible for Structure but Significant for Dynamics
Nore Stolte, János Daru, Harald Forbert +2
Isotopic substitution, which can be realized both in experiment and computer simulations, is a direct approach to assess the role of nuclear quantum effects on the structure and dy…
Random sampling versus active learning algorithms for machine learning potentials of quantum liquid water
Nore Stolte, János Daru, Harald Forbert +2
Training accurate machine learning potentials requires electronic structure data comprehensively covering the configurational space of the system of interest. As the construction o…
A High-Dimensional Neural Network Potential for CoO
Amir Omranpour, Jörg Behler
The CoO spinel is an important material in oxidation catalysis. Its properties under catalytic conditions, i.e., at finite temperatures, can be studied by molecular dynamic…
From electrons to phase diagrams with classical and machine learning potentials: automated workflows for materials science with pyiron
Sarath Menon, Yury Lysogorskiy, Alexander L. M. Knoll +10
We present a comprehensive and user-friendly framework built upon the pyiron integrated development environment (IDE), enabling researchers to perform the entire Machine Learning P…