Citation:
Wenwen Ma, Lian Kong, Jinyang Chu, Li Ma, Ziqing Ma, Heyu Cheng, Xinyuan Li, Zhan Yu, Zhen Zhao. Digitalization-Driven Olefin Production: Digital Design of Catalysts for CO2-Assisted Oxidation Dehydrogenation of Ethane to Ethylene[J]. University Chemistry,
;2026, 41(1): 363-372.
doi:
10.12461/PKU.DXHX202506055
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To align with the educational objectives of Energy Chemical Engineering and enhance undergraduates’ research interest while cultivating their scientific thinking and methodology, we have incorporated faculty research achievements into specialized experimental teaching. By employing digital tools to support the experimental learning process, we have developed a comprehensive and innovative undergraduate laboratory course. This digitally-enhanced experiment employs CO2-assisted oxidative dehydrogenation of ethane to ethylene as a probe reaction, encompassing the complete workflow of catalyst preparation, characterization, performance evaluation, and data analysis. This approach significantly deepens students’ understanding of catalytic processes in energy conversion. The integration of digital teaching methods during experimental preparation and data processing not only promotes autonomous learning but also enables efficient data classification and organization. Furthermore, utilizing our experimental database, decision tree models with optimized depth can identify critical input variables and provide targeted guidance for catalyst design. The experiment skillfully combines core elements from inorganic chemistry, physical chemistry, and instrumental analysis, creating an innovative and well-rounded experimental platform. This methodology not only develops students’ fundamental laboratory skills but also stimulates their enthusiasm for chemical experimentation while comprehensively enhancing their operational, analytical, innovative, and collaborative competencies.
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