Automated discovery of a robust interatomic potential for aluminum
oleh: Justin S. Smith, Benjamin Nebgen, Nithin Mathew, Jie Chen, Nicholas Lubbers, Leonid Burakovsky, Sergei Tretiak, Hai Ah Nam, Timothy Germann, Saryu Fensin, Kipton Barros
| Format: | Article |
|---|---|
| Diterbitkan: | Nature Portfolio 2021-02-01 |
Deskripsi
The accuracy of a machine-learned potential is limited by the quality and diversity of the training dataset. Here the authors propose an active learning approach to automatically construct general purpose machine-learning potentials here demonstrated for the aluminum case.