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In-Line Monitoring the Degradation of Polypropylene under Multiple Extrusions Based on Raman Spectroscopy.
Guo, Xuemei; Lin, Zenan; Wang, Yingjun; He, Zhangping; Wang, Mengmeng; Jin, Gang.
Afiliação
  • Guo X; National Engineering Research Center of Novel Equipment for Polymer Processing, South China University of Technology, Guangzhou 510641, China. guoxm2710@163.com.
  • Lin Z; Key Laboratory of Polymer Processing Engineering of Ministry of Education, South China University of Technology, Guangzhou 510641, China. guoxm2710@163.com.
  • Wang Y; Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing, South China University of Technology, Guangzhou 510641, China. guoxm2710@163.com.
  • He Z; National Engineering Research Center of Novel Equipment for Polymer Processing, South China University of Technology, Guangzhou 510641, China. lzn557968@163.com.
  • Wang M; Key Laboratory of Polymer Processing Engineering of Ministry of Education, South China University of Technology, Guangzhou 510641, China. lzn557968@163.com.
  • Jin G; Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing, South China University of Technology, Guangzhou 510641, China. lzn557968@163.com.
Polymers (Basel) ; 11(10)2019 Oct 16.
Article em En | MEDLINE | ID: mdl-31623208
ABSTRACT
Polymer degradation is a common problem in the extrusion process. In this work, Raman spectroscopy, a robust, rapid, and non-destructive tool for in-line monitoring, was utilized to in-line monitor the degradation of polypropylene (PP) under multiple extrusions. Raw spectra were pretreated by chemometrics methods to extract variations of spectra and eliminate noise. The variation of Raman intensity with the increasing number of extrusions was caused by the scission of PP chains and oxidative degradation, and the variation trend of Raman intensity indicated that long chains were more likely to be damaged by the extrusion. For the quantitative analysis of degradation, the partial least square was used to build a model to predict the degree of PP degradation measured by gel permeation chromatography (GPC). For the calibration set, the coefficient of determination (R2) and the root mean square error of cross-validation (RMSECV) were 0.9859 and 1.2676%, and for the prediction set, R2 and the root mean square error of prediction (RMSEP) were 0.9752 and 1.7228%, which demonstrated the accuracy of the proposed model. The in-line Raman spectroscopy combined with the chemometrics methods was proved to be an accurate and highly effective tool, which can monitor the degradation of polymer in real time.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Polymers (Basel) Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Polymers (Basel) Ano de publicação: 2019 Tipo de documento: Article