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.
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.
An open-source application for general-purpose quantum chemical calculation, laying emphasis on excited states and time evolution. It is based on time-dependent density functional theory (TDDFT) and the QM/MM calculation. It enables efficient massive parallel computing up to one hundred thousands processes. It supports the relativistic effect and offers the basis choice between the Gaussian basis and the plane-wave basis.
xTAPP is a first-principles plane-wave pseudo-potential code. It computes band structure and electronic states with high precision for a wide range of materials including metals, oxide surfaces, solid interfaces, and so forth. It has support tools and visualization of output and input, is available as a massively parallel computer using OpenMP, MPI, and GPGPU.
An open-source application for first-principles calculation based on pseudo- potential and real-space basis. It performs electronic-state calculation such as band calculation of solids and structure optimization for a variety of physical systems. The method of time-dependent density functional theory (TDDFT) is implemented, which allows simulation of dynamical phenomena with real-time evolution of electronic states, such as chemical reaction and electronic response to time-dependent external fields. Comes with detailed tutorials and comprehensive manuals.
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.
The fragment molecular orbital (FMO) method can efficiently do quantum-mechanical calculations of large molecular systems by splitting the whole system into small fragments. The FMO program is distributed within quantum-chemical program suite GAMESS-US. FMO can provide various information regarding the structure and function of biopolymers, such as the interaction between a protein and a ligand.
A python library for materials analysis. Flexible classes for representation of materials are prepared, and data for crystal structures and various material properties can be handled efficiently. This application can performs analysis of phase diagrams, Pourbaix diagrams, diffusion analyses etc. as well as electronic structure analyses such as density of states and band structures. This software is being actively developed keeping close relation with Materials Project.
An open-source application for the first-principles calculation based on the all-electron method with localized bases. By adopting the full-potential LMTO method, high-speed electronic state calculation can be performed with a less number of bases compared with the standard all-electron method. There is no restriction on symmetries as in the LMTO-ASA method, and spin polarization and spin-orbit interaction can also be treated.
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.