2024
DOI: 10.26434/chemrxiv-2024-9bmfj-v3
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Large Language Models for Inorganic Synthesis Predictions

Seongmin Kim,
Yousung Jung,
Joshua Schrier

Abstract: We evaluate the effectiveness of pre-trained and fine-tuned large language models (LLMs) for predicting the synthesizability of inorganic compounds and the selection of precursors needed to perform inorganic synthesis. The predictions of fine-tuned LLMs are comparable to—and sometimes better than—recent bespoke machine learning models for these tasks, but require only minimal user expertise, cost, and time to develop. Therefore, this strategy can serve both as an effective and strong baseline for future machin… Show more

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