Application of AI-Visual-Assisted Digital Technology in Titration Analysis Experiments:Determination of Hardness,Calcium and Magnesium Components in Tap Water
XIAO Yu-Tong, CHEN Peng-Shuo, QIN Zi-Yun, CHEN Yi-Rui, NAN Cai-Yun, LIU Hong-Yun**
Key Laboratory of Radiopharmaceuticals,Ministry of Education,College of Chemistry,Beijing Normal University,Beijing 100875,China
Abstract This work is grounded in the intelligent reform of the quantitative chemical analysis experimental teaching system,focusing on the practical application of artificial intelligence(AI) in complexometric titration experiments.Taking the determination of total hardness and calcium-magnesium components in tap water as the research object,an intelligent analysis system based on convolutional neural network(CNN) was constructed to address the teaching pain points of subjective errors and time-consuming detection caused by manual end-point interpretation in traditional complexometric titration.The technical scheme employed a self-built microfluidic device for automatic titration,captured the color characteristics of the solution in real time through a high-frame-rate camera,and established a dynamic color recognition model combined with a CNN architecture to achieve accurate determination of the titration end-point.This experiment could be integrated into the analytical chemistry experimental teaching platform,which would effectively cultivate students' core capabilities,such as intelligent instrument operation,data analysis,and interdisciplinary innovation,providing a paradigm for the digital transformation of chemical experiments.
XIAO Yu-Tong, CHEN Peng-Shuo, QIN Zi-Yun, CHEN Yi-Rui, NAN Cai-Yun, LIU Hong-Yun. Application of AI-Visual-Assisted Digital Technology in Titration Analysis Experiments:Determination of Hardness,Calcium and Magnesium Components in Tap Water[J]. Chinese Journal of Chemical Education, 2026, 47(12): 32-39.
