An application for the Rietveld analysis used in X-ray and neutron diffraction experiments. This application determines lattice constants and atomic coordinates from X-ray and neutron diffraction data on powder samples by pattern fitting based on the maximum entropy method (MEM). It can also analyze materials with random atomic configuration effectively. It supports Windows and Mac OS, and is still being developed actively.
Payware for the ab-initio quantum chemical calculation. This application preforms high-speed electronic structure calculation by introducing the RI approximation, and evaluates not only ground states but also excited states by various methods such as full RPA, TDDFT, CIS(D), CC2, ADC(2). It can also be used for evaluation of spectra data of infrared(IR), visible(Vis)/ultraviolet(UV), Raman, and circular dichroism spectroscopy.
A Python library for simulating strongly correlated quantum systems using tensor networks. The goal is to make the algorithms readable and easy to use for beginners, and also powerful and fast for experts. Simple sample code and toy code to illustrate TEBD and DMRG are also provided.
An open-source application for atomic structure analysis from powder diffraction data. This application can calculate atomic coordinates, valence sums, and chemical bonds from diffraction data of crystals, nanostructures, and amorphous materials. It is written in Python, and realizes multi-functional fitting and flexible data analysis.
An application for first-principles calculation based on the all-electron method with localized bases. Compared with the standard all-electron method (the full-potential LAPW method), this application uses a less number of bases keeping accuracy of calculation, and realize high-speed electronic state calculation by the density functional method. This application also supports calculation for disordered structures by coherent potential approximation (CPA), relativistic effect, and the LSDA+U method.
An open-source application for first-principles molecular dynamics simulation based on pseudo-potential and plane-wave basis set. This application enables accurate molecular dynamics by density functional theory and Car-Parrinello method. It also supports structure optimization, Born-Oppenheimer molecular dynamics, path-integral molecular dynamics, calculation of response functions, the QM/MM method, and excited-state calculation.
An official Gaussian-series payware for molecular visualization. Must be used with Gaussian, the well-known software of quantum chemistry calculation. This application provides many functions such as molecular modeling, parameter setting, job management and visualization of calculation results. It also performs input file generation for Gaussian, and supports read/write of files with other formats such as Sybyl, Molden, PDB and CIF.
Python-based simulations of chemistry framework (PySCF) is a general-purpose electronic structure platform written in Python. Users can perform mean-field and post-mean-field methods with standard Gaussian basis functions. This package also provides several interfaces to other software such as BLOCK and Libxc.
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.