Open source Python package for data mining of materials. It can extract data from more than dozens of databases, perform preprocessing and visualization of extracted data. By combining machine-learning tools such as scikit-learn, users can build machine-learning models with descriptors created from the extracted data.
Software package that implements moment tensor potentials. Potentials can be trained and used for molecular dynamics calculations using LAMMPS. Active learning combined with molecular dynamics calculations is also available.
A low-energy solver for a wide ranger of quantum lattice models (multi-orbital Hubbard model, Heisenberg model, Kondo-lattice model) by using variational Monte Carlo method. User can obtain high-accuracy wave functions for ground states of above models. Users flexibly choose the correlation factors in wavefunctions such as Gutzwiller, Jastrow, and doublon-holon binding factors and optimize more the ten thousand variational parameters. It is also possible to obtain the low-energy excited states by specifying the quantum number using the quantum number projection.
Software package that implements Behler-Parinello type neural network potential. The package provides tools for training and evaluating potentials based on given structure-energy data. It also provides an interface with LAMMPS for performing molecular dynamics calculations.
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.
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.
An application for first-principles calculation based on the order-N method. This application can perform electronic-state calculation and band calculation for various physical systems. It supports the DFT+U method, the time-dependent DFT method, molecular dynamics, etc., and can also treat van der Waals forces and phonons. By using support applications, generation of input files, transformation between different file formats, and analysis of numerical results can be performed.
A database for thermodynamic properties and crystal structures calculated based on the density functional theory by a research group in Northwestern University. OQMD provides over one million data generated by using not only experimental crystal structures provided by ICSD but also those obtained by calculations. Users can search data in OQMD by using Python API.
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.
Software tool for constructing interatomic potentials based on nonlinear atomic cluster expansion. It requires the user to either prepare a fitting dataset based on pandas and ASE, or it can automatically extract data from VASP calculation results. The obtained potentials can be used for molecular dynamics simulations using LAMMPS, and it also provides the capability to calculate extrapolation grades for on-the-fly active learning.