CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation

CrystalReasoner (CrysReas) is an end‑to‑end large language model framework that generates crystal structures from natural language instructions by incorporating physical priors as thinking tokens—such as crystallographic symmetry, local coordination, and predicted properties—before producing atomic coordinates. It then uses reinforcement learning with a multi‑objective reward to enforce physical validity, chemical consistency, and thermodynamic stability, and includes task‑specific rewards for property‑conditioned generation. Empirical results show that CrysReas outperforms prior methods, triples the S.U.N. ratio, and adapts reasoning length with increasing atom counts.

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• llms
• diffusion
• reinforcement-learning
• safety