人工智能在科学研究中的融合创新应用——以双碳目标背景下的二氧化碳电催化还原为例

doi:10.12461/PKU.DXHX202412099

Abstract

Abstract: Against the backdrop of rapid advancements in artificial intelligence (AI) technology worldwide, universities face significant challenges in addressing contemporary issues by integrating traditional scientific research with AI. This integration aims to broaden the perspectives of engineering graduate students, stimulate innovative thinking, enhance the efficiency of innovative outputs, and cultivate versatile talents for national and societal needs. This paper, using electrocatalytic carbon dioxide reduction (CO2RR) within the framework of carbon neutrality as a case study, underscores the importance of merging scientific research with AI to augment research output and accuracy. It highlights how AI computing facilitates the screening and prediction of high-performance catalysts, deepens the understanding of complex reaction mechanisms, optimizes electrolytes, and aids in experimental design. Furthermore, it promotes interdisciplinary collaboration and serves as a reference for engineering graduate students embarking on experimental research in universities.

Key words: Artificial intelligence, Carbon dioxide electrocatalytic reduction, Carbon neutrality, Catalyst screening, Electrolyte optimization, Reaction mechanism research, Experimental plan design

Haoran Zhang, Yaxin Jin, Peng Kang, Sheng Zhang. The Convergence and Innovative Application of Artificial Intelligence in Scientific Research: A Case Study of Electrocatalytic Carbon Dioxide Reduction in the Context of the Dual-Carbon Strategy[J].University Chemistry, 2025, 40(9): 148-155.

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The Convergence and Innovative Application of Artificial Intelligence in Scientific Research: A Case Study of Electrocatalytic Carbon Dioxide Reduction in the Context of the Dual-Carbon Strategy

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