ERIC Number: EJ1444862
Record Type: Journal
Publication Date: 2024-Feb
Pages: 9
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0021-9584
EISSN: EISSN-1938-1328
Machine Learning for Infrared Spectral Classification of Polyvinyl butyrals with Identical Chemical Groups: An Example for Undergraduate Chemistry Classes
Raoyu Qiu; Zequn Lin; Zican Yang; Liang Gao
Journal of Chemical Education, v101 n2 p328-336 2024
Machine learning (ML) is extensively applied in chemistry, particularly in vibrational spectroscopy. However, few teaching examples effectively demonstrate the capabilities of ML in classifying polymeric materials, exhibiting subtle spectral differences that elude visual discrimination. This study presents a teaching example specifically tailored for undergraduate students to acquire the skills necessary to employ ML models in the classification of infrared spectral data from different types of polyvinyl butyrals (PVBs). The course encompasses fundamental knowledge of PVB structure and synthesis, a comprehensive spectral analysis workflow for constructing classification models, specific data processing techniques, and practical implementation of a student-synthesized PVB product in a laboratory demonstration. Assessment of students' knowledge acquisition is conducted through assignments, and student attitudes toward this course via submitted self-reflection surveys are discussed. This study underscores the efficacy of classroom examples in developing students' abilities and fostering their interest in amalgamating chemistry and artificial intelligence. The knowledge and techniques acquired in this course hold practical implications for quality control, process monitoring, and material identification in industry.
Descriptors: Artificial Intelligence, Classification, Undergraduate Study, Chemistry, Science Instruction, Spectroscopy, Undergraduate Students, Skill Development
Division of Chemical Education, Inc. and ACS Publications Division of the American Chemical Society. 1155 Sixteenth Street NW, Washington, DC 20036. Tel: 800-227-5558; Tel: 202-872-4600; e-mail: eic@jce.acs.org; Web site: http://pubs.acs.org/jchemeduc
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A