JARVIS (Joint Automated Repository for Various Integrated Simulations) is a repository designed to automate materials discovery and optimization using classical force-field, density functional theory, machine learning calculations and experiments. Find more details in https://arxiv.org/abs/2007.01831
Websites
NIST-JARVIS Resources
| Resource | Summary | Website |
|---|---|---|
| Homepage | Description and API | Link |
| DFT | Density functional theory data | Link |
| FF | Evaluation of classical force field | Link |
| ML | Machine learning models | Link |
| Tools | Scripts for running simulations | Link |
| Downloads | Downloadable metadata | Link |
| Notebooks | Jupyter/Google-Colab notebooks | Link |
| Heterostructure | 2D heterostructure properties | Link |
| STM | STM images for 2D materials | Link |
| WannierTB | Wannier tight binding models | Link |
| BeyondDFT | High-level ab-initio methods | Link |
| Publications | JARVIS-related publications | Link |
| Tools docs | Documentation (docs) of tools | Link |
| DB docs | Documentation on the database | Link |
| Tools pypi | Pypi repository of tools | Link |
| Workshops | JARVIS-related workshops | Link |
| ResearchG. | Social media researchgate page. | Link |
| Social media twitter page | Link | |
| Social media facebook page | Link | |
| Social media linkedin page | Link | |
| SlideShare | Collection of presentation slides | Link |
| YouTube | Social media youtube page | Link |
| Google-group | Social media google-group | Link |
Number of materials
JARVIS-FF (1471)
JARVIS-DFT (40345)
JARVIS-ML (1429605)
JARVIS-WTB (1771)
JARVIS-STM (716)
JARVIS-Hetero (226779)
Founder and developer: Dr. Kamal Choudhary
Contributors: (Drs.) Francesca Tavazza, Kevin F. Garrity, Andrew C. E. Reid, Brian DeCost, Adam J. Biacchi, 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 Agarwa, Xiaofeng Qian, Vinit Sharma, Houlong Zhuang, Sergei Kalinin, Ghanshyam Pilania, Pinar Acar, Subhasish Mandal, Kristjan Haule, David Vanderbilt, Karin Rabe.
