/jarvis_leaderboard

Explore State-of-the-Art Materials Design Methods: https://www.nature.com/articles/s41524-024-01259-w

Primary LanguageJupyter NotebookOtherNOASSERTION

Leaderboard actions GitHub repo size name name Downloads DOI

JARVIS-Leaderboard:

This project provides benchmark-performances of various methods for materials science applications using the datasets available in JARVIS-Tools databases. Some of the methods are: Artificial Intelligence (AI), Electronic Structure (ES), Force-field (FF), Qunatum Computation (QC) and Experiments (EXP). There are a variety of properties included in the benchmark. In addition to prediction results, we attempt to capture the underlyig software, hardware and instrumental frameworks to enhance reproducibility. This project is a part of the NIST-JARVIS infrastructure.

Website: https://pages.nist.gov/jarvis_leaderboard/