3 papers
physics.comp-ph2020
Metadynamics sampling in atomic environment space for collecting training data for machine learning potentials
Dongsun Yoo, Jisu Jung, Wonseok Jeong +1
The universal mathematical form of machine-learning potentials (MLPs) shifts the core of development of interatomic potentials to collecting proper training data. Ideally, the trai…
physics.comp-ph2020
Training machine-learning potentials for crystal structure prediction using disordered structures
Changho Hong, Jeong Min Choi, Wonseok Jeong +6
Prediction of the stable crystal structure for multinary (ternary or higher) compounds with unexplored compositions demands fast and accurate evaluation of free energies in explori…
physics.comp-ph2019
Atomic energy mapping of neural network potential
Dongsun Yoo, Kyuhyun Lee, Wonseok Jeong +2
We show that the intelligence of the machine-learning potential arises from its ability to infer the reference atomic-energy function from a given set of total energies. By utilizi…