Payware for first-principles quantum chemical calculation. This application performs molecular orbital calculation based on Hartree-Fock approximation, density functional method, and post-HF methods such as MP, f12, multi-configuration SCF, and coupled cluster method. It also implements calculation by path-integral instanton, quantum Monte Carlo, and density-matrix renormalization group method.
The fragment molecular orbital (FMO) method can efficiently do quantum-mechanical calculations of large molecular systems by splitting the whole system into small fragments. The FMO program is distributed within quantum-chemical program suite GAMESS-US. FMO can provide various information regarding the structure and function of biopolymers, such as the interaction between a protein and a ligand.
An application for ab initio quantum chemical calculation. This application performs electronic structure calculation of molecules by the Hartree-Fock, density functional, many-body perturbation, configuration interaction theories, and so on. This application is free only for academic use in United Kingdom. Although it histrically shares core programs with GAMESS-US, different functions have been added in later development.
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.
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.
Payware for the ab-initio quantum chemical calculation. This application preforms high-speed electronic structure calculation by introducing the RI approximation, and evaluates not only ground states but also excited states by various methods such as full RPA, TDDFT, CIS(D), CC2, ADC(2). It can also be used for evaluation of spectra data of infrared(IR), visible(Vis)/ultraviolet(UV), Raman, and circular dichroism spectroscopy.
An application for first-principles calculation based on the all-electron method with localized bases. Compared with the standard all-electron method (the full-potential LAPW method), this application uses a less number of bases keeping accuracy of calculation, and realize high-speed electronic state calculation by the density functional method. This application also supports calculation for disordered structures by coherent potential approximation (CPA), relativistic effect, and the LSDA+U method.
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.
CONQUEST is a linear-scaling DFT (Density Functional Theory) code based on the density matrix minimization method. Since its computational cost, for both memory and computational costs, is only proportional to the number of atoms N of the target systems, the code can employ structure optimization or molecular dynamics on very large-scale systems, including more than hundreds of thousands of atoms. It also has high parallel efficiency and is suitable for massively parallel calculations.
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.