BoltzTraP2

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

An application for calculating transport coefficients based on the Boltzman equation. Within the relaxation time approximation, transport coefficients such as the Hall coefficient and the Seebeck coefficient can be evaluated from the output of the first principles calculation applications (Wien2k, ABINIT, SIESTA, quantum ESPRESSO, VASP). If users can measure relaxation time experimentally, electric conductivity can also be evaluated.

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Phonopy

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

Software to calculate physical quantities related to phonon in solids from result calculated using first principles calculation software. Results calculated from first principles calculation software such as VASP and Wien2k are used as an input.

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PySCF

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

Python-based simulations of chemistry framework (PySCF) is a general-purpose electronic structure platform written in Python. Users can perform mean-field and post-mean-field methods with standard Gaussian basis functions. This package also provides several interfaces to other software such as BLOCK and Libxc.

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DAMASK

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

DAMASK is a unified multi-physics crystal plasticity simulation package. The solution of continuum mechanical boundary value problems requires a constitutive response that connects deformation and stress at each material point. This problem is solved in DAMASK on the basis of crystal plasticity using a variety of constitutive models and homogenization approaches. However, treating mechanics in isolation is no longer sufficient to study emergent advanced high-strength materials. In these materials, deformation happens interrelated with displacive phase transformation, significant heating, and potential damage evolution. Therefore, DAMASK is capable of handling multi-physics problems. Following a modular approach, additional field equations are solved in a fully coupled way using a staggered approach.

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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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DSQSS

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

DSQSS is an application program for solving quantum many body problems in a discrete set (typically a lattice). It carries out quantum Monte Carlo simulations that sample from the Feynman path integral using the worm update. It can handle any lattice geometry and interaction.

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NAP

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

A group of applications that perform molecular dynamics, hybrid quantum/classical mechanical simulation, search of chemical reaction path by the nudged elastic band method, and potential parameter fitting. The molecular dynamics code includes interatomic potentials for several metals and semiconductors, and is capable of parallel computation based of spatial decomposition.

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SpM

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

A sparse-modeling tool for computing the spectral function from the imaginary-time Green function. It removes statistical errors in quantum Monte Carlo data, and performs a stable analytical continuation. The obtained spectral function fulfills the non-negativity and the sum rule. The computation is fast and free from tuning parameters.

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VisBAR

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆
A set of Python scripts for post-simulation data analysis of large-scale electronic state calculations. Currently the open script is ‘VisBAR Wave Batch’ that visualizes many wavefunctions, as isosurfaces, simultaneously. The script generates picture files in PNG and other formats from grid data files in the Gaussian cube format. Many data files can be treated in parallelism by MPI.
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XenonPy

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

XenonPy is a high-throughput material exploration framework based on machine learning technologies. This library can generate various chem/phys descriptors for machine learning to explore materials in virtual environment. Descriptors in matminer can be also used. Model training is done by PyTorch. Visualization tool for descriptor and transfer learning framework are also provided.

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