类Chat GPT生成式人工智能——化学研究与化学教育好帮手  

ChatGPT-Like Generative AI:Good Helper in Chemistry Research and Education

作　　者：邓淞 伍晓春[1] DENG Song;WU Xiao-Chun(College of Chemistry and Materials Science,Sichuan Normal University,Chengdu 610066,China)

机构地区：[1]四川师范大学化学与材料科学学院,四川成都610066

出　　处：《化学教育（中英文）》2024年第18期14-21,共8页Chinese Journal of Chemical Education

基　　金：四川师范大学2023年度人才培养质量和教学改革项目“以研究性学习共同体推动学术型人才培养的研究”(20230014XJG);四川师范大学校级课题“课程思政领航学院”(20220030XSZ)。

摘　　要：过渡态搜索是化学中阐明反应机理和探索反应网络的关键。然而,由于势能面的复杂性,寻找精确的三维过渡态结构依赖大量的量子化学计算。对于复杂反应,得到一个基元反应过渡态结构可能需要数十小时甚至数天,效率相对较低。麻省理工的研究人员开发了一款生成式人工智能模型,能够以6 s左右的时间快速且精准地“生成”反应中的过渡态结构。此模型为高校非计算化学方向的老师探索反应机理和设计新的化学反应提供了另外一个相对便捷的工具。与此同时,随着人工智能与化学教育的深度融合,生成式人工智能有望成为化学教育领域的重要助力。Transition state search is the key to elucidating reaction mechanisms and exploring reaction networks in chemistry.However,due to the complexity of the potential energy surfaces,the search for accurate 3D transition state structures relies on a large number of quantum chemical calculations.For complex reactions,obtaining the transition state structure of a primitive reaction can take tens of hours or even days,which is relatively inefficient.MIT researchers have developed a generative AI model that is able to predict reaction transition state structures in almost 6 seconds with very high accuracy.This model provides another relatively convenient tool for non-computational chemistry faculty at universities to explore reaction mechanisms and design new chemical reactions.Meanwhile,with the deep integration of generative AI and chemistry education,generative AI is expected to become an important booster in the field of chemistry education.

关 键 词：生成式 人工智能 OA-ReactDiff模型 过渡态 ChatGPT 化学教育 

分 类 号：G642[文化科学—高等教育学] O6-4[文化科学—教育学] TP18[理学—化学]