Open source software for building and using machine learning potentials based on E(3)-equivariant graph neural networks, which can be trained on output files of simulation codes that can be read by ASE. Molecular dynamics calculations with LAMMPS can be performed using the trained potentials.
An application for structure prediction based on the genetic algorithm. This application can predict the structure and composition of stable phase of crystals, molecules, atomic clusters, and so on by using first-principles calculation and molecular dynamics. This application implements interfaces with various programs such as VASP, LAMMPS, MOPAC, GULP, JDFTx, etc, and runs efficiently on parallel computing architectures.
Open source software for constructing the Allegro potential model based on E(3)-equivariant graph neural networks and using the potential model for molecular dynamics simulations. The code depends on NequIP and can be run in a similar manner. Allegro scales better than NequIP since it doesn’t rely on message passing and the architecture is strictly local with respect to atom-wise environments.
A group of applications that perform molecular dynamics, hybrid quantum/classical mechanical simulation, search of chemical reaction path by the nudged elastic band method, and potential parameter fitting. The molecular dynamics code includes interatomic potentials for several metals and semiconductors, and is capable of parallel computation based of spatial decomposition.
Software tool for constructing interatomic potentials based on nonlinear atomic cluster expansion. It requires the user to either prepare a fitting dataset based on pandas and ASE, or it can automatically extract data from VASP calculation results. The obtained potentials can be used for molecular dynamics simulations using LAMMPS, and it also provides the capability to calculate extrapolation grades for on-the-fly active learning.
An open-source application for molecular dynamics simulation of biomolecules. This application is optimized for massive parallel computing environments such as the K-computer, and can perform high-speed molecular dynamical simulation of proteins and biomolecules. This application supports both all atoms calculation and coarse-grained model calculation, and can treat extended ensemble such as a replica exchange method. This code is released under GPL license.
i-PI is a universal force engine interface written in Python, designed to be used together with an ab-initio (or force-field based) evaluation of the interactions between the atoms. This application includes a large number of sophisticated methods such as replica exchange molecular dynamics (REMD) and path integral molecular dynamics (PIMD). Inter-atomic forces can be computed by using external codes such as CP2K, Quantum ESPRESSO and LAMMPS.
aenet is software for atomic interaction potentials using artificial neural networks. Users can construct neural network potentials using structures of target materials and their energies obtained from first principle calculations. The generated potentials can be used to molecular dynamics or Monte Carlo simulations.
An open-source application for visualization of many-particle systems. With simple operation by graphical user interface (GUI) or by command line, this application can visualize particle positions obtained from molecular dynamics simulation as well as three-dimensional scalar quantities such as potential energies. It supports various display options on kinds and shapes of particles, and can also visualize bond formation between particles.
Software package that implements Behler-Parinello type neural network potential. The package provides tools for training and evaluating potentials based on given structure-energy data. It also provides an interface with LAMMPS for performing molecular dynamics calculations.