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.
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.
An open-source application for first-principles calculation utilizing pseudo-potentials and plane-wave basis sets. This application is capable of performing electronic structure calculations of a wide range of physical systems such as crystals and surfaces/interfaces. It supports structure relaxation, phonon-dispersion calculation, and molecular dynamics simulation, and can deal with systems with the spin-orbit interaction.
An open-source application for high-accuracy electronic-state calculation based on the variational Monte Carlo method and the diffusion Monte Carlo method. Although its computational cost is high, physical properties of atoms and small molecules in the ground states and excited states are calculated with very high accuracy. Includes an application program that generates input files from output of other packages for quantum chemical calculation, such as GAMESS, Gaussian, etc.
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.
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.
RSPACE is a first-principles code package based on a real-space finite-difference pseudo-potential method. It computes electronic states with high-speed and high precision in aperiodic systems of surfaces, solid interfaces, clusters, nanostructures, and so forth. It provides large-scale computing for semiconductor devices of nanostructure surface and interface reactions, calculation of transport properties in semi-infinite boundary conditions, and a massively parallel computing using the space partitioning method.
RSDFT is an ab-initio program with the real-space difference method and a pseudo-potential method. Using density functional theory (DFT), this calculates electronic states in a vast range of physical systems: crystals, interfaces, molecules, etc. RSDFT is suitable for highly parallel computing because it does not need the fast Fourier transformation. By using the K-computer, this program can calculate the electronic states of around 100,000 atoms. The Gordon Bell Prize for Peak-Performance was awarded to RSDFT in 2011.
Python tool for automatic extraction of chemical substance information from literature. Based on natural language processing algorithms, it can extract substance names and related physical/chemical properties such as melting points and spectra from documents written in English.
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.