jarvis-tools: an open-source software package for data-driven atomistic materials design. https://jarvis.nist.gov/
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: https://jarvis.nist.gov . This project is a part of the Materials Genome Initiative (MGI) at NIST (https://mgi.nist.gov/).
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 .
Installation
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) 2.33 >>> >>> from jarvis.db.figshare import data >>> dft_3d = data(dataset='dft_3d') >>> print (len(dft_3d)) 36099
References
Please see Publications related to JARVIS-Tools
External links
https://figshare.com/authors/Kamal_Choudhary/4445539
https://pypi.org/project/jarvis-tools
Correspondence
Please report bugs as Github issues (https://github.com/usnistgov/jarvis/issues) or email to kamal.choudhary@nist.gov.
Funding support
NIST-MGI (https://www.nist.gov/mgi).
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