人工智能开发和优化燃料电池催化剂的初步探索  

Tentative exploration of artificial intelligence in developing and optimizing fuel cell catalysts

作　　者：华秋茹 顾一鸣[2] 郭显斌 吴楚 李刚 张义煌 王树东[2] Qiuru Hua;Yiming Gu;Xianbin Guo;Chu Wu;Gang Li;Yihuang Zhang;Shudong Wang(Weifu High-Technology Group Co.,LTD,Wuxi 214028,China;Dalian Institute of Physical Chemistry,Chinese Academy of Sciences,Dalian 116023,China)

机构地区：[1]威孚高科技集团股份有限公司,无锡214028 [2]中国科学院大连化学物理研究所,大连116023

出　　处：《中国科学：化学》2024年第11期2055-2070,共16页SCIENTIA SINICA Chimica

摘　　要：随着清洁能源技术的进步,燃料电池技术与催化剂技术的发展已成为现代科技的迫切需求.人工智能(AI)作为一种颠覆性的技术,在催化剂设计和优化方面的应用正逐步展现其潜力.本论文聚焦于AI在燃料电池催化剂研究中的应用探索,首先从人工智能的定义、起源、工具以及应用进行AI技术的理解,再探索使用AI进行新型催化剂的高效设计及性能的精准预测,进一步探索应用AI进行燃料电池催化剂的反应机理及表面反应活性位点的作用机制的解析,全方位探讨了AI如何助力燃料电池催化剂的研发.最后,通过构建数据驱动优化的AI模型,展示了AI在快速筛选高效催化剂以及揭示其结构与性能关系方面的优势,为实现高效、可控的催化剂制备提供了新的方法.本文的综述研究不仅为燃料电池催化剂的研究提供了新的思路,也为AI在催化科学中的应用提供了初步示范.With the advancement of clean energy technology,the development of fuel cell technology and catalyst technology has become a critical priority in modern technology.Artificial Intelligence(AI)is emerging as a transformative tool with its significant potential in the design and optimization of catalysts.This review explores AI’s application in fuel cell catalyst research,beginning with an overview of AI technology,including its definition,origins,tools,and applications.It then examines the use of AI for the efficient design of novel catalysts and the accurate prediction of their performance.Additionally,the paper investigates AI’s role in analyzing the reaction mechanisms of fuel cell catalysts and the interactions at reactive surface sites.The comprehensive discussion highlights AI’s contributions to the research and development of fuel cell catalysts.By constructing data-driven AI models,the paper demonstrates AI’s advantages in the rapid screening of efficient catalysts and elucidating the structure-performance relationship.This approach offers innovative methods for the preparation of efficient and controllable catalysts.The review provides new insights into fuel cell catalyst research and demonstrates AI’s preliminary applications in catalytic science.

关 键 词：人工智能 燃料电池 催化剂 模型优化 

分 类 号：TM911.4[电气工程—电力电子与电力传动] TQ426[化学工程] TP18[自动化与计算机技术—控制理论与控制工程]