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Researchers developed an LLM-based closed-loop platform that generates and refines synthesis recipes for new materials using data from 4,407 published experiments. In tests on a previously unreported solid electrolyte, experimental feedback enabled the model to adjust synthesis temperatures from 600°C to 400°C and produce a single-phase material within only a few iterations, reducing trial and error in materials discovery.

https://advanced.onlinelibrary.wiley.com/doi/10.1002/adma.74502
The Advanced Portfolio Closed‐Loop Solid‐State Synthesis Planning for Materials Discovery With Large Language Models Leveraging literature data, we build a large-language-model-driven workflow that extracts synthesis steps from 4407 papers, retrieves similar precedents, and generates candidate solid-state synthesis...
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