A combined generative model, ML potential, and graph neural network pipeline expands the Alexandria database by 1.3 million DFT-validated compounds with 99% success near the convex hull and releases training data for universal force fields.
We then selected the 88 thousands structures compounds predicted to have the smallest distance to the hull for further DFT relaxation
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AI-Driven Expansion and Application of the Alexandria Database
A combined generative model, ML potential, and graph neural network pipeline expands the Alexandria database by 1.3 million DFT-validated compounds with 99% success near the convex hull and releases training data for universal force fields.