An open-source multi-purpose application for many-particle simulation. This application prepares various kinds of statistical methods and potentials, and can perform simulation of rigid-body mechanics, Langevin dynamics, dissipative-particle dynamics, nonequilibrium molecular dynamics, and so on. It prepares python scripts for production of initial conditions, job submission, and analysis of results.
An open-source application for molecular dynamics simulation of biomolecules, especially designed for massively parallel computing. This package enables us to perform efficient parallel calculation on parallel computers ranging from 100 to 20,000 cores. For preparation of calculation and analysis of orbits, it uses visualization software VMD. It supports file formats compatible with other applications such as AMBER and CHARMM, and can be used on various computing environments.
Debian Live Linux System that contains OS, editors, materials science application software, visualization tools, etc. An environment needed to perform materials science simulations is provided as a one package. By booting up on VirtualBox virtual machine, one can start simulations, such as the first-principles calculation, molecular dynamics, quantum chemical calculation, lattice model calculation, etc, immediately.
Software package that implements moment tensor potentials. Potentials can be trained and used for molecular dynamics calculations using LAMMPS. Active learning combined with molecular dynamics calculations is also available.
FORTRAN-based software package developed by the Behler Group for implementing Behler-Parinello neural network potentials. Potentials can be constructed, evaluated, and used for molecular dynamics simulations using LAMMPS. The newest generation of neural network potentials that take into account long-range electrostatic interactions are implemented.
Software package to implement Behler-Parinello neural network potentials. Potentials can be trained from structure-energy/ interatomic forces/stress data, and molecular dynamics calculations using LAMMPS can also be performed using learned potentials. A prediction uncertainty measure can also be calculated simultaneously.
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.
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.
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.
Python/C++ based software package that employs deep learning techniques for construction of interatomic potentials. It implements the Deep Potential, which defines atomic environment descriptors with respect to a local reference frame. The output of many first-principles and molecular dynamics applications can be used as training data, and the trained potentials can be used for molecular dynamics calculations using LAMMPS and path integral molecular dynamics calculations using i-PI.