JARVIS-Leaderboard

This project benchmarks the performance of materials-science methods using datasets from the JARVIS-Tools databases. It covers AI-driven materials design, property prediction, electronic-structure methods, force fields, quantum computing, and experimental data.

Benchmark Categories

| Category | Contributions |
| ------------------------------ | ------------: |
| Artificial Intelligence (AI) | 1,034 |
| Electronic Structure (ES) | 741 |
| Force Fields / Potentials (FF) | 282 |
| Experiments (EXP) | 25 |
| Quantum Computing (QC) | 6 |