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.
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.
ALPS is a numerical simulation library for strongly correlated systems such as magnetic materials or correlated electrons. It contains typicalsolvers for strongly correlated systems: Monte Carlo methods, exact diagonalization, the density matrix renormalization group, etc. It can be used to calculate heat capacities, susceptibilities, magnetization processes in interacting spin systems, the density of states in strongly correlated electrons, etc. A highly efficient scheduler for parallel computing is another improvement.
An open-source impurity solver based on the quantum Monte Carlo method. Thermal equilibrium states of interacting impurity systems, such as the impurity Anderson model, can be evaluated by the continuous-time hybridization-expansion quantum Monte Carlo method. It can be used as a solver of effective impurity models derived from the dynamical mean-field theory (DMFT) and can deal with multi-orbital models. This package supports parallel computation by MPI and is developed based on the ALPSCore library.
AMULET is a collection of tools for a first principles calculation of physical properties of strongly correlated materials. It is based on density functional theory (DFT) combined with dynamical mean-field theory (DMFT). Users can calculate physical properties of chemically disordered compounds and alloys within CPA+DMFT formalism.
Payware for evaluation of electron transport based on nonequilibrium Green’s function. This application is descended from the SIESTA application, and can calculate electronic transport properties of bulk materials and molecules inserted between leads by performing electronic state calculation under a finite bias. One can choose either density functional method or semiempirical method, and can control external factors such as gate voltages. It also implements structure optimization and analysis of chemical reaction paths.
A tool for performing Bader analysis of assigning electron density of molecules and solids to individual atoms. Binaries for Linux and Mac OS X, as well as source code is provided under the GPL. The code is written in fortran90, and can handle charge density data in VASP CHGCAR and Gaussian Cube formats.
An open-source application for first-principles calculation based on pseudopotential and wavelet basis. Electronic state calculation of massive systems is performed with high accuracy and high efficiency by using adaptive mesh. Parallel computing by MPI, OpenMP, and GPU is also supported.
Fitting data to a scaling law of critical phenomena, we automatically estimate critical point and indices. Since Bayesian method is flexible, we can use all data in a critical region.