Introducing Raman Spectroscopy through Analysis of Microplastic Pollutants: A Polymer Characterization Practical for Chemical Engineering Undergraduates

Raman spectroscopy, a powerful vibrational spectroscopic technique widely used in chemistry, materials science, and environmental analysis, provides critical molecular insights through spectral fingerprints. However, undergraduate students often lack proficiency in optimizing experimental parameters, interpreting vibrational modes, and applying chemometric tools to real-world samples. To address this gap, we designed a problem-based learning (PBL) laboratory course for chemical engineering students in a Polymeric Materials curriculum. Participants analyzed microplastics─an emerging environmental contaminant─using Raman spectroscopy to identify polymer types, assign functional groups, and correlate spectral features with material properties. Students employed principal component analysis (PCA) to classify polymer spectra and visualize results through score plots, integrating hands-on instrumentation with computational data analysis. This inquiry-driven experiment achieved educational outcomes including enhanced technical skills in Raman parameter optimization and spectral interpretation, proficiency in chemometrics for material classification, and heightened critical thinking through authentic environmental problem-solving. This practical framework bridges fundamental spectroscopy, materials science, and data analytics, preparing undergraduates for interdisciplinary research.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Education
Published
2025-09-22
DOI
https://doi.org/10.1021/acs.jchemed.5c00725
Primary Topic
Nanotechnology research and applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Introducing Raman Spectroscopy through Analysis of Microplastic Pollutants: A Polymer Characterization Practical for Chemical Engineering Undergraduates

Qing He, Huilin Hu, Zhu‐Feng Geng, Fengmin Jin et al.
Journal of Chemical Education
Nanotechnology research and applications
article

Introducing Raman Spectroscopy through Analysis of Microplastic Pollutants: A Polymer Characterization Practical for Chemical Engineering Undergraduates

Qing He, Huilin Hu, Zhu‐Feng Geng, Fengmin Jin, Xiaobin Fan, Shaolan Zou, Na Liu, Wen Zhang, Nana Tian, Shixin Liu, Yinping Li, Hui Fang
article en

Abstract

Raman spectroscopy, a powerful vibrational spectroscopic technique widely used in chemistry, materials science, and environmental analysis, provides critical molecular insights through spectral fingerprints. However, undergraduate students often lack proficiency in optimizing experimental parameters, interpreting vibrational modes, and applying chemometric tools to real-world samples. To address this gap, we designed a problem-based learning (PBL) laboratory course for chemical engineering students in a Polymeric Materials curriculum. Participants analyzed microplastics─an emerging environmental contaminant─using Raman spectroscopy to identify polymer types, assign functional groups, and correlate spectral features with material properties. Students employed principal component analysis (PCA) to classify polymer spectra and visualize results through score plots, integrating hands-on instrumentation with computational data analysis. This inquiry-driven experiment achieved educational outcomes including enhanced technical skills in Raman parameter optimization and spectral interpretation, proficiency in chemometrics for material classification, and heightened critical thinking through authentic environmental problem-solving. This practical framework bridges fundamental spectroscopy, materials science, and data analytics, preparing undergraduates for interdisciplinary research.

Journal of Chemical EducationVol. 102(10)
Xinjiang Normal University (CN), Tianjin University of Technology (CN), Tianjin University (CN), Beijing Normal University (CN), Analysis and Testing Centre (CN), Electronics Testing Center (TW)
Openalex Percentile: Top 75%
Nanotechnology research and applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.