Application of Machine Learning in Teaching Infrared Spectroscopy
PAN Qing1,2, HE Jia-Ni1,2, ZHONG Rong-Zhen1,2, LIN Wen-Yu1,2, FAN Jian-Ping1,2, CAI Kai-Cong1,2**
1. Fujian Normal University,College of Chemistry and Materials Science,Fujian Provincial Key Laboratory of Advanced Materials Oriented Chemical Engineering,Fuzhou 350117,China; 2. Xiamen University, Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry,Xiamen 361005,China
Abstract Machine learning technique was introduced into“Computer and Applied Chemistry”course for students to train neural network models based on the conformers’ data of alanine dipeptide,aimed to predict amide-Ⅰ vibrational feature of dipeptides backbone.Students’ understanding of the applications of artificial intelligence was promoted through class practice,and they gained insights into the correlation between molecular structure and vibrational feature,thus would be helpful for cultivating interdisciplinary and innovative talents.
PAN Qing, HE Jia-Ni, ZHONG Rong-Zhen, LIN Wen-Yu, FAN Jian-Ping, CAI Kai-Cong. Application of Machine Learning in Teaching Infrared Spectroscopy[J]. Chinese Journal of Chemical Education, 2025, 46(12): 110-115.
