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<p>The field of catalysis holds paramount importance in shaping the trajectory of sustainable development, prompting intensive research efforts to leverage artificial intelligence (AI) in catalyst design. Presently, the fine-tuning of open-source large language models (LLMs) has yielded significant breakthroughs across various domains such as biology and healthcare. Drawing inspiration from these advancements, we introduce <b>CataLM</b> (<b>Cata</b>lytic <b>L</b>anguage <b>M</b>odel), a large language model tailored to the domain of electrocatalytic materials. Our findings demonstrate that <b>CataLM</b> exhibits remarkable potential for facilitating human-AI collaboration in catalyst knowledge exploration and design. To the best of our knowledge, <b>CataLM</b> stands as the pioneering LLM dedicated to the catalyst domain, offering novel avenues for catalyst discovery and development.</p>

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CataLM: empowering catalyst design through large language models

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月15日

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  • Ludi Wang,
  • Xueqing Chen,
  • Yi Du,
  • Yuanchun Zhou,
  • Yang Gao,
  • Wenjuan Cui

摘要

The field of catalysis holds paramount importance in shaping the trajectory of sustainable development, prompting intensive research efforts to leverage artificial intelligence (AI) in catalyst design. Presently, the fine-tuning of open-source large language models (LLMs) has yielded significant breakthroughs across various domains such as biology and healthcare. Drawing inspiration from these advancements, we introduce CataLM (Catalytic Language Model), a large language model tailored to the domain of electrocatalytic materials. Our findings demonstrate that CataLM exhibits remarkable potential for facilitating human-AI collaboration in catalyst knowledge exploration and design. To the best of our knowledge, CataLM stands as the pioneering LLM dedicated to the catalyst domain, offering novel avenues for catalyst discovery and development.