DeePMD-kit

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

Python/C++ based software package that employs deep learning techniques for construction of interatomic potentials. It implements the Deep Potential, which defines atomic environment descriptors with respect to a local reference frame. The output of many first-principles and molecular dynamics applications can be used as training data, and the trained potentials can be used for molecular dynamics calculations using LAMMPS and path integral molecular dynamics calculations using i-PI.

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FHI-aims

  • Level of openness 0 ☆☆☆
  • Document quality 2 ★★☆

An application for first-principles calculation based on all-electron calculation using atomic bases. This application can perform accurate electronic-state calculation for various physical systems. It supports a number of functional sets including hybrid functionals, and can support relativistic effects, many-body perturbation methods, and the GW method. It can treat over 100 elements, and keeps high efficiency in parallel calculation from a desktop machine to a high-performance parallel computer up to 10,000 CPUs.

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JDFTx

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

An application for first-principles calculation by the joint-DFT method based on a plane-wave basis. By implementation of the joint-DFT method, this application realizes a good convergence for electronic state calculation of molecules in liquid, particular for charged systems. This application is written by C++11, and supports GPU calculation by CUDA. This application also supports diffusive Monte Carlo simulation in cooperation with CASINO.

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GULP

  • Level of openness 0 ☆☆☆
  • Document quality 2 ★★☆

An application program for lattice dynamics calculation of molecules, surfaces, and solids in various boundary conditions. It lays emphasis on analytic calculation of lattice dynamics while it can perform molecular dynamics simulation as well. It supports various force fields to treat ionic materials, organic materials, and metals. It also implements analytic derivatives of the second and third order for many force fields.

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DC

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

An electronic state solver distributed with GAMESS, the quantum chemical (QM) calculation software. Combining energy density analysis and Divide-and-Conquer (DC) method, accurate QM calculation with electronic correlation is solved in a short time. Highly accurate QM calculations for many-atom/nano-scale material can be solved when run on a high performance super computer.

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QUIP

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

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.

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Firefly

  • Level of openness 2 ★★☆
  • Document quality 2 ★★☆

An application for ab initio quantum chemical calculation. This application performs electronic structure calculation of molecules by the Hartree-Fock, density functional, the many-body perturbation, configuration interaction theories, and so on. While this application is a derivative of GAMESS-US for specific use of Intel compatible CPU, it does not include recently developed calculation methods such as the CC and FMO methods.

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Molden

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

An open-source application for pre- and post-processing for quantum chemistry calculation. This application can handle outputs from Gaussian, GAMESS, and MOPAC as well as the result of other applications via the Molden format. It supports many graphical interfaces such as Postscript, XWindows, VRML, and OpenGL, and performs visualization of molecular orbitals and electron density. It also produces animation videos of molecular vibration.

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NequIP

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

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.

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GaussView

  • Level of openness 0 ☆☆☆
  • Document quality 2 ★★☆

An official Gaussian-series payware for molecular visualization. Must be used with Gaussian, the well-known software of quantum chemistry calculation. This application provides many functions such as molecular modeling, parameter setting, job management and visualization of calculation results. It also performs input file generation for Gaussian, and supports read/write of files with other formats such as Sybyl, Molden, PDB and CIF.

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