The latest implementation of this model has been merged into PyTorch Geometric. Please use the PyG version in the future.

• PR: #5866
• Doc: link

Atomistic Force Fields based on GNNFF

GNNFF [1] is a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant, but rotationally-covariant to the coordinate of the atoms. This package is an atomistic force fields that constructed based on GNNFF.

References

• [1] C. W. Park, M. Kornbluth, J. Vandermause, C. Wolverton, B. Kozinsky, J. P. Mailoa, Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture. npj Computational Materials. 7, 1–9 (2021). link