GNoME

2.2M new crystals: Dramatically expands the known crystal inventory, with 380,000 stable materials - an order-of-magnitude leap over prior computational chemistry.

Graph networks for stability: Predicts formation energies and stability of candidate materials using graph neural networks trained on DFT-labeled data.

Active-learning loop: Combines exploration (proposing candidate structures) with exploitation (prioritizing high-stability candidates), iteratively expanding the frontier of known materials.

Autonomous lab validation: A subset of predictions was validated in Berkeley's autonomous materials lab, closing the prediction-to-synthesis loop for the first time at this scale.