croncagl/ML-potential-training---CP2K-LAMMPS-MACE

A workflow for training MACE machine learning potentials using CP2K and LAMMPS

/ 100

Experimental

No Package No Dependents

Maintenance 13 / 25

Adoption 0 / 25

Maturity 9 / 25

Community 0 / 25

Stars

—

Forks

—

Language

Python

License

MIT

Category

Last pushed

Mar 18, 2026

Commits (30d)

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/croncagl/ML-potential-training---CP2K-LAMMPS-MACE"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Higher-rated alternatives

deepmodeling/deepmd-kit

A deep learning package for many-body potential energy representation and molecular dynamics

chemprop/chemprop

Message Passing Neural Networks for Molecule Property Prediction

mir-group/nequip

NequIP is a code for building E(3)-equivariant interatomic potentials

CederGroupHub/chgnet

Pretrained universal neural network potential for charge-informed atomistic modeling...

microsoft/mattersim

MatterSim: A deep learning atomistic model across elements, temperatures and pressures.