Open-source tools and a database for molecular simulation. Data of molecular models (interatomic potentials and force fields), result data of molecular simulation, and test tools can be downloaded freely. API (Application Programming Interface) for exchanging information between atomistic simulation codes and interatomic models is also provided.
A general-purpose open-source application for classical molecular dynamics simulation, distributed under the GPL license. This package can perform molecular dynamics calculation of various systems such as soft matters, solids, and mesoscopic systems. It can be used as a simulator of classical dynamics of realistic atoms as well as general model particles. It supports parallel computing through spatial divisions. Its codes are designed so that their modification and extension are easy.
An open-source application for molecular simulations. This application supports various methods such as classical and ab initio molecular dynamics, path integral simulations, replica exchange simulations, metadynamics, string method, surface hopping dynamics, QM/MM simulations, and so on. A hierarchical parallelization between molecular structures (replicas) and force fields (adiabatic potentials) enables fast and efficient computation.
An open-source application for visualization of crystal structures and grid data that runs on most UNIX and UNIX-like platforms. This application can visualize calculation results from the following electronic structure packages: GAUSSIAN, CRYSTAL, Quantum Espresso (PWscf), WIEN2k, FHI98MD. Three-dimensional data such as electron densities and local potentials as well as Fermi surfaces can be visualized using this application.
An open-source application of semi-empirical/ab-initio quantum chemical calculation that comes under an academic license. It performs various quantum chemical calculations based on Hartree-Fock theory, density functional theory, and configuration interaction theory, yielding electronic states and enabling structure optimization and molecular spectrum analysis. Molecular dynamics calculation based on the QM/MM method is also possible by using this software in combination with GROMACS.
An open-source application for first-principles molecular dynamics based on a pseudopotential method using plane bases. This application can perform electronic-state calculation and molecular dynamics employing the Car-Parrinello method. It implements MPI parallelization, which enables us to perform efficient parallel computing in various environments including large-scale parallel computers. The program is written in C++, and is distributed in source form under the GPL license.
Open-source package for molecular dynamics simulation designed for biological macromolecules. This package can perform molecular dynamics simulation of biological macromolecules such as proteins, lipids, and nuclear acids as well as solutions by controlling temperature and pressure. This package can treat long-range interaction and free energy, and is designed for parallel computing.
An application for visualization of biopolymers. This application can visualize biopolymers by using its original command line and graphical user interface, more than 600 settings for visualization, and more than 20 visualization schemes. This application also supports more than 30 file formats such as PDB and multi-SDF, and can utilize sophisticated visualization methods such as the ray tracing.
A collection of shell scripts for installing open-source applications and tools for computational materials science to macOS, Linux PC, cluster workstations, and major supercomputer systems in Japan. Major applications are preinstalled to the nation-wide joint-use supercomputer system at Institute for Solid State Physics, University of Tokyo by using MateriApps Installer.
A Python package for extracting structural features from point cloud and image data using the mathematical framework of persistent homology. In the field of materials science, it is used to characterize structural differences between liquids and glasses, as well as for dimensionality reduction of microscope images. It is also useful for obtaining structural descriptors for machine learning.