NIST-JARVIS

The JARVIS (Joint Automated Repository for Various Integrated Simulations) is an infrastructure designed to automate materials discovery and optimization using classical force-field, density functional theory, machine learning, quantum computation calculations and experiments. Access to the database and web apps requires user credentials. User-registration is free, click on the Login/Sign up button. Find more details about JARVIS in: Nature Portfolio, AIP and other publications. For upcomnig events, checkout the JARVIS-Events page.

Resources


Statistics

JARVIS-DFT materials (77096)

JARVIS-FF materials (2538)

JARVIS-ML (1429605)

OptB88vdW bandgaps and formation energies (77096)

TBmBJ bandgaps (18293)

Elastic Tensors (25513)

Topological SOC spillage (11383)

Infrared intensities (4801)

Dielectric function (15860)

2D exfoliation energy (812)

Carrier effective mass (17642)

Piezoelectric tensors (4801)

Seebeck coeff. (23210)

Electric field gradient (11865)

Solar-SLME (8614)

JARVIS-WannierTB (1771)

JARVIS-STM (1432)

JARVIS-Hetero (226778)




Founder and developer: Dr. Kamal Choudhary

Contributors: (Drs.) Francesca Tavazza, Kevin F. Garrity, Andrew C. E. Reid, Brian DeCost, Adam J. Biacchi, Ramya Gurunathan, Daniel Wines, Taner Yildirim, Angela R. Hight Walker, Zachary Trautt, Jason Hattrick-Simpers, A. Gilad Kusne, Andrea Centrone, Albert Davydov, Jie Jiang, Ruth Pachter, Gowoon Cheon, Evan Reed, Ankit Agarwal, Xiaofeng Qian, Vinit Sharma, Houlong Zhuang, Sergei Kalinin, Ghanshyam Pilania, Pinar Acar, Subhasish Mandal, Kristjan Haule, David Vanderbilt, Igor Mazin, Karin Rabe, Mark Kasule.