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arXiv Machine Learning By Ivan \v{Z}ugec, Joshua Rosenthal, Ivor Lon\v{c}ari\'c, Jan-Willem van de Meent, Tin Had\v{z}i Veljkovi\'c

Orbitol: Crystal Generation on Wyckoff Orbits

Read the original on arXiv Machine Learning →

Orbitol is a crystal generation model that uses Wyckoff-orbit tokens instead of atom tokens, enabling direct control over the space group of generated structures. It produces structures two to three orders of magnitude faster than symmetry‑aware baselines and achieves higher success rates in generating stable, novel structures that retain the requested symmetry. The authors also introduce SPARC, a score combining space‑group retention with distribution agreement, and demonstrate Orbitol’s effectiveness in generating high‑quality piezoelectric candidates with superior figures of merit.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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