| Official site | https://compphysvienna.github.io/n2p2/ |
|---|---|
| Openness | ★★★ |
| Manual | https://compphysvienna.github.io/n2p2/ |
| Download | https://github.com/CompPhysVienna/n2p2 |
| License |
GPL v3 |
| Core Developers |
– Andreas Singraber – Saaketh Desai – Sam Reeve – Martin P. Bircher |
| Related Papers |
ベーラー・パリネロ型ニューラルネットワークポテンシャル： J. Behler, M. Parrinello, “Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces” [Phys. Rev. Lett. 98, 146401 (2007)] |
| Related Sites |
MateriApps: https://ma.issp.u-tokyo.ac.jp/en/app/5833 |
n2p2
n2p2 is a software package that implements the Baylor-Parinello neural network potentials. n2p2 provides a comprehensive toolkit for deriving neural network potentials from data. These potentials correlate structures and energies. With the trained potentials, n2p2 can compute energies and forces. It also supports molecular dynamics simulations via LAMMPS and CabanaMD.
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