Accurate Neural Network Potential on PyTorch
-
Updated
Oct 29, 2024 - Python
Accurate Neural Network Potential on PyTorch
Tensorflow + Molecules = TensorMol
ANI-1 neural net potential with python interface (ASE)
Tool to build force field input files for molecular simulation
A package for atom-typing as well as applying and disseminating forcefields
SO3krates and Universal Pairwise Force Field for Molecular Simulation
Differentiable molecular simulation of proteins with a coarse-grained potential
A physical property evaluation toolkit from the Open Forcefield Consortium.
Fragment molecules for quantum mechanics torsion scans
A repository for tutorials and FAQ's about LigParGen
Computational Chemistry Data Management Library for Machine Learning Force Field Development
A python code to calculate the Brownian motion of colloidal particles in a time varying force field.
Polarisable force field for ionic liquids
Genetic Algorithm Machine Learning (GAML) software package for automated force field parameterization.
A package for managing pair-potential derivation using MultiState Iterative Boltzmann Inversion (MS-IBI)
Python repository for generating molecular potential files for LAMMPS.
A template repo for disseminating force fields with foyer
Force field conversion utility: Tinker, LAMMPS and Antechamber parameters to OpenMM XML
Analytical Hessian Fitting schemes for parameterization.
scripts to interface TorchANI to Gaussian package
Add a description, image, and links to the force-field topic page so that developers can more easily learn about it.
To associate your repository with the force-field topic, visit your repo's landing page and select "manage topics."