myPresto

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

Commercially-available free software for Computer-Aided Drug Development. It includes programs for compound database, protein-compound docking, structure-based drug screening, ligand-based drug screening, protein-ligand binding site prediction, molecular editor, physical property prediction, synthetic accessibility prediction, thermodynamic calculation including multi-canonical dynamics, and molecular dynamics simulations with and without acceleration using GPUs and MPI parallelization.

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n2p2

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

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.

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NAMD

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

An open-source application for molecular dynamics simulation of biomolecules, especially designed for massively parallel computing. This package enables us to perform efficient parallel calculation on parallel computers ranging from 100 to 20,000 cores. For preparation of calculation and analysis of orbits, it uses visualization software VMD. It supports file formats compatible with other applications such as AMBER and CHARMM, and can be used on various computing environments.

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NCON

  • Level of openness 2 ★★☆
  • Document quality 1 ★☆☆

A MATLAB function for the contraction process of a tensor network. It takes as input a tensor network and a contraction sequence describing how to contract the network to a single tensor or number. It returns a single tensor or number as output. This function can be obtained by downloading the preprint source.

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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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OCTA

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

OCTA is an integrated simulation system for soft materials developed by the joint project of industry and academia funded by Ministry of Economy, Trade and Industry(METI), Japan. OCTA consists of four simulation engines named COGNAC(Molecular dynamics simulation), PASTA(rheology simulation), SUSHI(mean field theory), MUFFIN(continuum theory) and a simulation platform (GOURMET).

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OpenKIM

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

Open-source tools and a database for molecular simulation. Data of molecular models (interatomic potentials and force fields), result data of molecular simulation, and test tools can be downloaded freely. API (Application Programming Interface) for exchanging information between atomistic simulation codes and interatomic models is also provided.

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OpenPhase

  • Level of openness 3 ★★★
  • Document quality 1 ★☆☆

An open-source application for the phase-field simulations. This application treats many kinds of problems in materials science such as determination of phase diagrams, crystal growing, small structures accompanied by first-order transition, and so on. Its source code is open under the GPL, and is developed putting emphasis on its flexibility in the C++ language.

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OQMD: The Open Quantum Materials Database

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

A database for thermodynamic properties and crystal structures calculated based on the density functional theory by a research group in Northwestern University. OQMD provides over one million data generated by using not only experimental crystal structures provided by ICSD but also those obtained by calculations. Users can search data in OQMD by using Python API.

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pacemaker

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

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.

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