Codes
RxnRep
RxnRep is a training method to leverage self-supervised contrastive pretraining to learn chemical reaction representations. It enables the building of graph neural networks for small chemical reaction data.
BonDNet
BonDNet is a graph neural network model for the prediction of bond dissociation energies (BDEs). It can be applied to both homolytic and heterolytic bond dissociations for molecules of any charge.
KLIFF
A KIM-based Learning-integrated Fitting Framework to train both physics-motivated and machine learning interatomic potentials.
pair dirp
LAMMPS implementation of the Dihedral-angle-corrected registry-dependent interlayer potential (DRIP) for multilayer graphene structures.
kimpy
A Python interface to the KIM API for atomistic simulations.