Software framework for training a machine learning model to reproduce first-principles energies and then using the model to perform configurational sampling in disordered systems. It has been developed with an emphasis on multi-component solid-state systems such as metal and oxide alloys. At present, Quantum Espresso, VASP and OpenMX can be used as first-principles energy calculators, and aenet can be used to construct neural network potentials.
Open-source package for first-principles calculation based on pseudo-potential and plane-wave basis. This package performs various electronic-state calculation by density functional theory such as band calculation of solids, and structure optimization of surfaces/interfaces. Detailed tutorials and documents are well prepared in this package, and many physical quantities including chemical reaction and lattice vibration can be obtained easily.
Payware for quantum chemical calculation based on the density functional theory. This application supports relativistic effects needed in treatment of transition-metal complexes and heavy elements, and can also treat effect of solvents with the method of COSMO and 3D-RISM. In addition to ordinal optical spectra, it can evaluate various spectra data such as NMR, atomic vibration, electron spin resonance, and nuclear quadrupole resonance (NQR).
Advance / NanoLabo is an integrated GUI which can graphically operates various calculation solvers such as Quantum ESPRESSO, LAMMPS, Advance / PHASE. It is easy to set modeling and calculation conditions by automatically searching information in typical materials databases such as Materials Project. Results calculated by solvers are graphically displayed instantaneously.
Advance / PHASE is software for first-principles calculation based on the density functional theory by using plane-wave basis and pseudopotentials. Since the electronic state is obtained based on quantum mechanics, highly accurate results can be obtained. It can be expected not only to analyze existing materials but also to design various metals, insulators, semiconductors, magnetic materials, dielectric materials, piezoelectric materials, and various other new materials.
aenet is software for atomic interaction potentials using artificial neural networks. Users can construct neural network potentials using structures of target materials and their energies obtained from first principle calculations. The generated potentials can be used to molecular dynamics or Monte Carlo simulations.
A results database of first-principle calculation for material science. This database provides numerical data of crystal structures, band structures, thermodynamic quantities, phase diagrams, magnetic moments, and so on. This site is maintained by a research group of Duke University, and in particular, has extensive data of Heusler alloys. In addition to a user interface based on web browsers, an http-based API is also provided to enable user-defined material screening. This database can be used without charge after registration.
AkaiKKR is a first-principles all-electron code package that calculates the electronic structure of condensed matters using the Green’s function method (KKR). It is based on the density functional theory and is applicable to a wide range of physical systems. It can be used to simulate not only periodic crystalline solids, but also used to calculate electronic structures of impurity systems and, by using the coherent potential approximation (CPA), random systems such as disordered alloys, mixed crystals, and spin-disordered systems.
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.