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 application for ab initio quantum chemical calculation. This application can calculate molecular structures, chemical reactivity, frequency analysis, electron spectrum, and NMR spectrum with high accuracy. It implements the density functional theory, the Hartree-Fock(HF) method as well as recently developed methods such as the post-HF correlation method. It also has GUI for molecular modeling and a tool for preparation of input files.
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 obtaining optimized many-body wavefunctions expressed by matrix product states (MPS). By using a second-generation density matrix renormalization group (DMRG) algorithm, many-body wave functions can be efficiently optimized. The quantum-chemical operators are represented by matrix product operators (MPOs), which provides flexibility to accommodate various symmetries and relativistic effects.
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.
A program package for electronic state calculations based on two-component relativistic quantum chemical theories. Several schemes and algorithms, which are specialized in calculations of molecules containing heavy elements, have been implemented. Single-point energies for ground and excited states, geometry optimizations, and molecular properties are available. Furthermore, the package can perform accurate calculations for molecules including many heavy atoms such as metal clusters with practical computational cost.
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.
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.
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.
Open source software for massively parallel quantum chemistry calculations. Energies and geometries of nano-sized molecules can be calculated without fragmentation. The program supports Hartree-Fock, density functional theory, and second-order Møller-Plesset perturbation theory calculations. The input format, execution method, and program structure are simple, and frequently used routines can be easily extracted.