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.
MODYLAS is a highly parallelized general-purpose molecular dynamics (MD) simulation program appropriate for very large physical, chemical, and biological systems. It is equipped most standard MD techniques including free energy calculations based on thermodynamic integration method. Long-range forces are evaluated rigorously by the fast multipole method (FMM) without using the fast Fourier transform (FFT) in order to realize excellent scalability. The program enables investigations of large-scale real systems such as viruses, liposomes, assemblies of proteins and micelles, and polymers. It works on ordinary linux machines, too.
ERmod is software for calculating the free energy in soft, molecular aggregate. This program rapidly and accurately calculates the free energy of binding of a molecule in the aggregate through combination of the molecular dynamics simulation and the energy-representation theory of solvation. The solubility of a molecule can be determined with ERmod in arbitrary solvent including supercritical fluid and ionic liquid. Assessment is also possible for the binding strength and site of a molecule in micelle, lipid membrane or protein.
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.
An application for adding a function of the replica exchange method to the existing applications for molecular dynamics simulation such as MODYLAS, AMBER, and CHARMM. Without changing original programs of molecular dynamics, the replica exchange method can be implemented easily. This application also shows high performance in massive parallel computing by the K-computer.
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.
A collection of software tools for molecular dynamics calculations. Various interatomic potentials and tight binding models are implemented, and numerous external applications can be invoked. It also supports training and evaluation of GAP (Gaussian Approximation Potential), which is a form of machine learning potential.
OCTA is an integrated simulation system for soft materials developed by the joint project of industry and academia funded by Ministry of Economy, Trade and Industry(METI), Japan. OCTA consists of four simulation engines named COGNAC(Molecular dynamics simulation), PASTA(rheology simulation), SUSHI(mean field theory), MUFFIN(continuum theory) and a simulation platform (GOURMET).
An open-source multi-purpose application for modeling and visualizing molecules (biomolecules, in particular). This application has been developed for multi-scale molecular simulation, and also provides a simple GUI for AMBER and Gaussian. It also implements exchange of protein residues and the Pathways model for the electron transfer in proteins. It calls rasmol for visualization of atoms and molecules.
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.