Comprehensive Experimental Design of Photocatalytic Treatment of Antibiotic Wastewater Process Optimization Based on Machine Learning
ZHAO Ying1, SHANG Qiao-Yan1,2**
1. College of Chemistry,Chemical Engineering and Materials Science,Shandong Normal University,Jinan 250014,China; 2. College of Marine and Environmental Sciences,Tianjin University of Science and Technology, Tianjin 300457,China
Abstract Industrial intelligence and automation have become an inevitable trend with the rapid development of artificial intelligence and data science.According to Emerging Engineering Education(3E)requirements for training chemical professionals,combined with the national major strategy of “green development”,a comprehensive experiment for optimizing photocatalytic treatment of antibiotic wastewater by machine learning was designed to solve problems(such as obscure theoretical knowledge and complicated calculation formulas)in Chemical Reaction Engineering course.Based on the integration of theory and experiment,it aims to help students deeply understand the chemical reaction mechanism and optimize the reaction process conditions assisted by artificial intelligence.The experimental principle,educational objective and evaluation method are described.The implementation process of the comprehensive experiment is clarified.The results of model training,process parameter optimization and verification experiment are discussed.Through this comprehensive experiment,students learned engineering knowledge such as chemical industry,environment and computer,mastered the method of solving complex chemical engineering problems with a new generation of information technology,and build interaction and integration scientific research and environmental awareness.
ZHAO Ying, SHANG Qiao-Yan. Comprehensive Experimental Design of Photocatalytic Treatment of Antibiotic Wastewater Process Optimization Based on Machine Learning[J]. Chinese Journal of Chemical Education, 2025, 46(16): 47-53.
