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jarvis-tools: an open-source software package for data-driven atomistic materials design.

Project description

JARVIS-Tools: an open-source software package for data-driven atomistic materials design

NIST-JARVIS (Joint Automated Repository for Various Integrated Simulations) is an integrated framework for computational science using density functional theory, classical force-field/molecular dynamics and machine-learning. The jarvis-tools package consists of scripts used in generating and analyzing the dataset. The NIST-JARVIS official website is: . This project is a part of the Materials Genome Initiative (MGI) at NIST (

For more details, checkout our latest article: JARVIS: An Integrated Infrastructure for Data-driven Materials Design

Some important features

  • Software workflow tasks: VASP, Quantum Espresso, BoltzTrap, Wannier90, LAMMPS, Scikit-learn, TensorFlow, LightGBM.
  • HPC clusters: PBS and SLURM.
  • Examples: Notebooks and test scripts to explain the package.
  • Available datasets: Summary of several datasets .


Please see Installation instructions

Example Jupyter notebooks

Please find several Google Colab Notebooks

Example function

>>> from jarvis.core.atoms import Atoms
>>> box = [[2.715, 2.715, 0], [0, 2.715, 2.715], [2.715, 0, 2.715]]
>>> coords = [[0, 0, 0], [0.25, 0.25, 0.25]]
>>> elements = ["Si", "Si"]
>>> Si = Atoms(lattice_mat=box, coords=coords, elements=elements)
>>> density = round(Si.density,2)
>>> print (density)
>>> from jarvis.db.figshare import data
>>> dft_3d = data(dataset='dft_3d')
>>> print (len(dft_3d))


Please see Publications related to JARVIS-Tools


Please report bugs as Github issues ( or email to

Funding support


Project details

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