WANG Yi,LIN Qin-bao,XIE Yan-ling,ZHANG Ming-yue.Identification of Recycled PET Using GC-MS Combined with Chemometric Methods[J].Journal of Instrumental Analysis,2025,44(04):637-644.
WANG Yi,LIN Qin-bao,XIE Yan-ling,ZHANG Ming-yue.Identification of Recycled PET Using GC-MS Combined with Chemometric Methods[J].Journal of Instrumental Analysis,2025,44(04):637-644. DOI: 10.12452/j.fxcsxb.240709203.
Identification of Recycled PET Using GC-MS Combined with Chemometric Methods
This study aimed to analyze the volatile substances in both virgin and recycled polyethylene terephthalate(PET) using gas chromatography-mass spectrometry(GC-MS). Based on various chemometric methods,this study also compared the differences between virgin and recycled PET. The ultimate goal was to establish a model that could identify and distinguish between virgin and recycled PET by analyzing characteristic substances and their concentrations. This research collected 26 samples of recycled PET particles and 48 samples of virgin PET particles provided by different plastic chemical companies. Dichloromethane was used as the extraction solvent. The samples were extracted at a temperature of 50 ℃ under ultrasonic conditions with a fixed power of 1000 W for 1 hour. The extracted solutions were analyzed using GC-MS,and a total of 21 volatile organic compounds were detected. The detected compounds were primarily phenolic and fatty substances,with complex sources that were difficult to trace. Subsequently,various chemometric methods were applied to analyze and identify both virgin and recycled PET. These methods included principal component analysis(PCA),orthogonal projections to latent structures discriminant analysis(OPLS-DA),linear discriminant analysis(LDA),artificial neural networks(ANN) and decision trees(DT). The accuracy of these different models in distinguishing between virgin and recycled PET was compared to determine which method was most effective. The results indicated that the combination of GC-MS with ANN and DT models achieved a classification accuracy of over 96% for recycled PET. This demonstrates that these models are effective in distinguishing between virgin and recycled PET. Therefore,the models can provide technical references for the application and regulation of recycled PET in the market,and will benefit both the industry and environmental sustainability.
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