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.
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.
Open source software for constructing the Allegro potential model based on E(3)-equivariant graph neural networks and using the potential model for molecular dynamics simulations. The code depends on NequIP and can be run in a similar manner. Allegro scales better than NequIP since it doesn’t rely on message passing and the architecture is strictly local with respect to atom-wise environments.
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.
H-wave is a Python package for performing unrestricted Hartree-Fock (UHF) calculations and random phase approximation (RPA) calculations for itinerant electron systems. H-wave supports UHF calculations both in real- and wavenumber-spaces. H-wave supports one-body and two-body interactions in the Wannier90 format as inputs for H-wave, and thus users can solve ab initio effective Hamiltonians derived from Wannier90/RESPACK calculations based on UHF and RPA methods.
TC++ is open-source software for ab initio calculations using the transcorrelated (TC) method. In TC++, users can take account of electron correlations in a Jastrow correlation factor based on the TC method. Electronic structures obtained by Quantum ESPRESSO can be used as an initial state of TC++.
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.
Python library for the Open Quantum Materials Database, a first-principles computational database. qmpy supports several analysis tools such as crystal structures and phase diagrams. Users can perform automatic calculations using VASP.
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.
Python wrapper to manage jobs for the ab initio Monte Carlo package TurboRVB. By combining with a workflow management application, TurboWorkflows, users can perform high-throughput calculations based on TurboRVB.