Large Language Models-assisted Literature Analysis Towards Photocatalysis: A Case of Artificial Nitrogen Photofixation

doi:10.1007/s40242-026-6125-x

Chemical Research in Chinese Universities ›› 2026, Vol. 42 ›› Issue (4): 1224-1228.doi: 10.1007/s40242-026-6125-x

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Large Language Models-assisted Literature Analysis Towards Photocatalysis: A Case of Artificial Nitrogen Photofixation

CHENG Xiang^1,4, GAO Junyu^1,2, LI Jiali³, ZHAO Yunxuan^1,2, ZHANG Tierui^1,2

1. Key Laboratory of Photochemical Conversion and Optoelectronic Materials, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China;
2. Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, P. R. China;
3. Key Laboratory of Environmental Aquatic Chemistry, State Key Laboratory of Regional Environment and Sustainability, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, P. R. China;
4. College of Science, Hebei Agricultural University, Baoding 071001, P. R. China

Received:2026-05-31 Revised:2026-07-02 Online:2026-08-01 Published:2026-07-28
Contact: ZHAO Yunxuan,E-mail:yunxuan@mail.ipc.ac.cn;ZHANG Tierui,E-mail:tierui@mail.ipc.ac.cn E-mail:yunxuan@mail.ipc.ac.cn;tierui@mail.ipc.ac.cn
Supported by:
This work was supported by the National Key Projects for Fundamental Research and Development of China (No. 2023YFA1507202), the National Natural Science Foundation of China (Nos. 22421005, 52432006, 52120105002, 22472187, 22322905, W2512013, U22A20391), the International Partnership Program of Chinese Academy of Sciences (No. 174GJHZ2024054MI), the Project of the Liaoning Binhai Laboratory, China (No. LBLD-2024-06), the Energy Revolution S&T Program of Yulin Innovation Institute of Clean Energy, China (No. E511050817), the CAS Project for Young Scientists in Basic Research (No. YSBR-004), and the Natural Science Foundation of Hebei Province, China (No. B2025204002).

Abstract

Abstract: Artificial nitrogen photofixation enables green ammonia synthesis under ambient conditions, making it one of the cutting-edge technologies in the fields of energy transition and sustainable development. Rapid growth in nitrogen photofixation has yielded a massive volume of publications, posing new challenges for manual literature screening, mechanism integration, and future trend analyses. Large language models (LLMs), with their robust capabilities in semantic understanding, information extraction, and logical reasoning, can significantly facilitate literature mining in photocatalysis. Taking artificial nitrogen photofixation as a case study, this perspective constructs an LLM-assisted literature analysis system and explores the practical value of intelligent analytical technologies in view of the emerging tendency. Furthermore, we also explore the anticipated contributions and challenges of artificial intelligence in photocatalysis, particularly regarding material design, experimental optimization, and mechanism investigation, with the aim of establishing a forward-looking roadmap for a low-carbon future in photocatalysis.

Key words: Large language model, Nitrogen fixation, Photocatalysis, Ammonia

CHENG Xiang, GAO Junyu, LI Jiali, ZHAO Yunxuan, ZHANG Tierui. Large Language Models-assisted Literature Analysis Towards Photocatalysis: A Case of Artificial Nitrogen Photofixation[J]. Chemical Research in Chinese Universities, 2026, 42(4): 1224-1228.

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Large Language Models-assisted Literature Analysis Towards Photocatalysis: A Case of Artificial Nitrogen Photofixation

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