Crystal-structure design by agentic AI in a language of motifs
Data-driven materials discovery interpolates more reliably than it extrapolates and seldom reaches new structure types. We present MatEvolve, an agentic-AI framework designing crystals, proposing each candidate with a stated rationale and testing it. The agent reasons in an interpretable \emph{language of motifs}, writing each crystal as a \emph{motif profile} that describes the recurring geometric patterns---the \emph{motifs}---composing it. The motif profile serves not merely as a description of a material but as the medium for material design: the agent edits the profile and constructs a crystal from the modified one, and the most promising candidates are validated by first-principles ...
| Authors | Dinh-Khiet Le, Minh-Quyet Ha, Hong-Phuc Vu-Dinh et al. |
|---|---|
| Primary category | cond-mat.mtrl-sci |
| Published | 16 August 2026 |
| Last updated at source | 16 August 2026 |
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