An application for quantum chemical calculation based on DFTB (Density Functional based Tight Binding). This application performs structure
optimization and molecular dynamics by the DFTB force field as well as ordinary energy calculation, and implements parallel computing by OpenMP. A tool for visualization of molecular orbitals and an extended versions supporting MPI parallel computation or electron transport calculation by the nonequilibrium Green’s function method are also
available.
An open-source application for quantum chemical calculation based on the density-matrix renormalization group (DMRG). For systems with a number of atomic orbitals, low-lying energy eigenvalues can be calculated in high accuracy of order of 1kcal/mol. This application is suitable especially to calculation of multi-orbital systems with one-dimensional topology such as chain-like or circular-like configuration of orbits.
A program package for constructing interatomic force fields which explicitly consider lattice anharmonicity. In combination with a molecular dynamics simulator LAMMPS and an external first-principles package such as VASP and Quantum ESPRESSO, ALAMODE extracts harmonic/anharmonic force constants of solids and calculates phonon dispersion, phonon DOS, Gruneisen parameter, phonon-phonon scattering probability, lattice thermal-conductivity, anharmonic phonons at finite temperature, phonon free energy and so on.
A Boltzmann transport equation solver for calculating lattice thermal conductivity based on phonon information obtained from first-principles calculations. It takes into account three-phonon interactions and enables first-principles analysis of thermal transport properties in solids, including anisotropic crystals, complex structures, and those containing defects. Tutorials and input-support tools are also provided. A tool for calculating third-order force constants (thirdorder.py) is also available on the same website.
A tool for generating wavevector paths in band calculations of solids. It identifies high-symmetry points in reciprocal space based on the symmetry of the crystal and provides a standardized “path” connecting them. It supports various crystal structure formats (such as POSCAR and CIF) and is compatible with many electronic structure calculation software (e.g., VASP, Quantum ESPRESSO, ABINIT). A web-based interface is also available.
A set of python modules for modeling atomic structures, running simulations, and visualizing results. These modules provide interfaces for various application of first-principles calculation, classical molecular dynamics, and quantum chemical calculation through GUI, command line, or python scripts. The source code is available under the LGPL.
A highly efficient framework for crystal structure exploration and property prediction dedicated to material science calculations. This application can automate the setup, execution, and analysis of the results of calculations based primarily on the density functional theory. It provides data on more than millions of crystal structures and can be used for high throughput calculations for material exploration. It also interfaces with various DFT codes (VASP, Quantum ESPRESSO, etc.).
An open-source application for the first-principles calculation by the all-electron calculation method based on plane wave bases. In addition to standard methods (LDA, GGA, etc.), the LDA+U method, treatment of spin-orbit interaction (noncolinear magnetism), and calculation of phonons are supported. Hybrid parallel computing by OpenMP and MPI is also supported.
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.
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.