This project is a parallel simulation engine and molecular dynamics simulator designed to model the physical movements of atoms and molecules. It functions as an interatomic potential framework for calculating forces between particles and a materials analysis tool for computing thermodynamic, structural, and transport properties of solids and fluids. The engine is distinguished by its high-performance computing capabilities, utilizing spatial-domain decomposition and message-passing interface communication to distribute workloads across processors. It supports multi-backend GPU acceleration v
DMFF (Differentiable Molecular Force Field) is a Jax-based python package that provides a full differentiable implementation of molecular force field models. This project aims to establish an extensible codebase to minimize the efforts in force field parameterization, and to ease the force and…
Muse (Mixture builder for simulation environments) is a Python package for rapidly building amorphous solids and liquid mixtures from relaxed solid-state structures on Materials Project. It uses Packmol for packing molecules into simulation cells and supports density equilibration through…
SOMD is an ab-initio molecular dynamics (AIMD) package designed for the SIESTA DFT code. The SOMD code provides some common functionalities to perform standard Born-Oppenheimer molecular dynamics (BOMD) simulations, and contains a simple wrapper to the Neuroevolution Potential (NEP) package. The…
The main features of initqp/somd are: Molecular Dynamics.
Open-source alternatives to initqp/somd include: lammps/lammps — This project is a parallel simulation engine and molecular dynamics simulator designed to model the physical movements… chiang-yuan/muse — Muse (Mixture builder for simulation environments) is a Python package for rapidly building amorphous solids and… deepmodeling/dmff — DMFF (Differentiable Molecular Force Field) is a Jax-based python package that provides a full differentiable… fitsnap/fitsnap — A Python package for machine learning potentials with LAMMPS. icams/lammps-user-pace — You could get the supported version of LAMMPS from GitHub repository. jax-md/jax-md — Quickstart | Reference docs | Paper | NeurIPS 2020.
