催化GPT：用于催化剂的人工智能驱动的定向高效设计框架。
Catal-GPT: AI-driven directed efficient design framework for catalysts.
作者信息
Zheng Peng, Han Zhennan, Su Bao-Lian, Xu Guangwen
机构信息
Key Laboratory on Resources Chemicals and Materials of Ministry of Education, Shenyang University of Chemical Technology, China.
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, China.
出版信息
Natl Sci Rev. 2025 Jul 25;12(9):nwaf299. doi: 10.1093/nsr/nwaf299. eCollection 2025 Sep.
Abstract
This perspective article proposes and further preliminarily verifies an artificial intelligence assistant (Catal-GPT) that interacts with researchers to optimize catalyst formulations, thereby improving the efficiency of catalyst design.
摘要
这篇观点文章提出并进一步初步验证了一种人工智能助手（Catal-GPT），它与研究人员互动以优化催化剂配方，从而提高催化剂设计的效率。
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