Application of generative artificial intelligence in catalysis

doi:10.1016/j.cjche.2025.05.013

中国化学工程学报 ›› 2025, Vol. 84 ›› Issue (8): 86-95.DOI: 10.1016/j.cjche.2025.05.013

Application of generative artificial intelligence in catalysis

Tiantong Zhang¹, Haolin Cheng¹, Yao Nian^1,2, Jinli Zhang^1,2, Qingbiao Li^3,4, You Han^1,2

1. School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China;
2. Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China;
3. College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China;
4. College of Ocean Food and Biologic Engineering, Jimei University, Xiamen 361021, China

收稿日期:2025-01-14 修回日期:2025-05-24 接受日期:2025-05-26 出版日期:2025-08-28 发布日期:2025-06-06
通讯作者: Qingbiao Li,E-mail:kelqb@xmu.edu.cn;You Han,E-mail:yhan@tju.edu.cn
基金资助:
This work was supported by the National Natural Science Foundation of China (T2441001) and the National Key Research & Development Program of China (2023YFB4104503).

Application of generative artificial intelligence in catalysis

Tiantong Zhang¹, Haolin Cheng¹, Yao Nian^1,2, Jinli Zhang^1,2, Qingbiao Li^3,4, You Han^1,2

1. School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China;
2. Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China;
3. College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China;
4. College of Ocean Food and Biologic Engineering, Jimei University, Xiamen 361021, China

Received:2025-01-14 Revised:2025-05-24 Accepted:2025-05-26 Online:2025-08-28 Published:2025-06-06
Contact: Qingbiao Li,E-mail:kelqb@xmu.edu.cn;You Han,E-mail:yhan@tju.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (T2441001) and the National Key Research & Development Program of China (2023YFB4104503).

摘要/Abstract

摘要： Catalysis has made great contributions to the productivity of human society. Therefore, the pursuit of new catalysts and research on catalytic processes has never stopped. Continuous and in-depth catalysis research significantly increases the complexity of dynamic systems and multivariate optimization, thus posing higher challenges to research methodologies. Recently, the significant advancement of generative artificial intelligence (AI) provides new opportunities for catalysis research. Different from traditional discriminative AI, this state-of-the-art technique generates new samples based on existing data and accumulated knowledge, which endows it with attractive potential for catalysis research — a field featuring a vast exploration space, diverse data types and complex mapping relationships. Generative AI can greatly enhance both the efficiency and innovation capacity of catalysis research, subsequently fostering new scientific paradigms. This perspective covers the basic introduction, unique advantages of this powerful tool, and presents cases of generative AI implemented in various catalysis researches, including catalyst design and optimization, characterization technique enhancement and guidance for new research paradigms. These examples highlight its exceptional efficiency and general applicability. We further discuss the practical challenges in implementation and future development perspectives, ultimately aiming to promote better applications of generative AI in catalysis.

关键词: Generative AI, Neural networks, Catalysis, Catalyst, Characterization technology, Research paradigm

Abstract: Catalysis has made great contributions to the productivity of human society. Therefore, the pursuit of new catalysts and research on catalytic processes has never stopped. Continuous and in-depth catalysis research significantly increases the complexity of dynamic systems and multivariate optimization, thus posing higher challenges to research methodologies. Recently, the significant advancement of generative artificial intelligence (AI) provides new opportunities for catalysis research. Different from traditional discriminative AI, this state-of-the-art technique generates new samples based on existing data and accumulated knowledge, which endows it with attractive potential for catalysis research — a field featuring a vast exploration space, diverse data types and complex mapping relationships. Generative AI can greatly enhance both the efficiency and innovation capacity of catalysis research, subsequently fostering new scientific paradigms. This perspective covers the basic introduction, unique advantages of this powerful tool, and presents cases of generative AI implemented in various catalysis researches, including catalyst design and optimization, characterization technique enhancement and guidance for new research paradigms. These examples highlight its exceptional efficiency and general applicability. We further discuss the practical challenges in implementation and future development perspectives, ultimately aiming to promote better applications of generative AI in catalysis.

Key words: Generative AI, Neural networks, Catalysis, Catalyst, Characterization technology, Research paradigm

Tiantong Zhang, Haolin Cheng, Yao Nian, Jinli Zhang, Qingbiao Li, You Han. Application of generative artificial intelligence in catalysis[J]. 中国化学工程学报, 2025, 84(8): 86-95.

Tiantong Zhang, Haolin Cheng, Yao Nian, Jinli Zhang, Qingbiao Li, You Han. Application of generative artificial intelligence in catalysis[J]. Chinese Journal of Chemical Engineering, 2025, 84(8): 86-95.

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Application of generative artificial intelligence in catalysis

Application of generative artificial intelligence in catalysis

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