CHGNet
Universal pretrained neural network potential with charge and magnetic moment awareness, trained on 1.5M+ Materials Project inorganic structures for charge-informed molecular dynamics and phase diagram prediction (Berkeley, Nature Machine Intelligence 2023 Cover)
README
CHGNet A pretrained universal neural network potential for charge-informed atomistic modeling (see publication) Crystal Hamiltonian Graph neural Network is pretrained on the GGA/GGA+U static and relaxation trajectories from Materials Project, a comprehensive dataset consisting of more than 1.5 Million structures from 146k compounds spanning the whole periodic table. CHGNet highlights its ability to study electron interactions and charge distribution in atomistic modeling with near DFT accuracy.…
- Repository
- github.com/cedergrouphub/chgnet
Source attribution
- Awesome AI for Science — github.com/cedergrouphub/chgnet
- Awesome Python Chemistry — github.com/cedergrouphub/chgnet
- GitHub — github.com/cedergrouphub/chgnet
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