LLM-guided phase diagram construction through high-throughput experimentation
Constructing phase diagrams for multicomponent alloys requires extensive experimental measurements and is a time-consuming task. Here we investigate whether large language models (LLMs) can guide experimental planning for phase diagram construction. In our framework, a general-purpose LLM serves as the experimental planner, suggesting compositions for measurement at each cycle in a closed loop with high-throughput synthesis and X-ray diffraction phase identification. Using this framework, we experimentally constructed the ternary phase diagram of the Co-Al-Ge system at 900 degree C through iterative synthesis and characterization. We compared two strategies that differ in how the initial ...
| Authors | Ryo Tamura, Haruhiko Morito, Yuna Oikawa et al. |
|---|---|
| Primary category | cond-mat.mtrl-sci |
| Published | 22 April 2026 |
| Last updated at source | 22 April 2026 |
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