You are not logged in Total: 7journals, 20,171articles Online
AccountAccount
Login / Register
Forgot Login?
 
Main menuMain menu
What's new
Journal list
Visiting ranking
Phrase ranking
Polls
About us
 
SearchSearch
 
Journal Site
Advanced Search
 

Home  >  Journal list  >  Polymer Journal  >  Vol.48  No.7 (2016)  >  pp.793-800

Polymer Journal
<<Previous article Vol.48  No.7 (2016)   pp.793 - 800 Next article>>

Multivariate analysis of 13C NMR spectra of branched copolymers prepared by initiator-fragment incorporation radical copolymerization of ethylene glycol dimethacrylate and tert-butyl methacrylate

Tomohiro Hirano1, Ryota Kamiike1, Yuchin Hsu1, Hikaru Momose1,2 and Koichi Ute1
1Department of Chemical Science and Technology, Institute of Technology and Science, Tokushima University, Tokushima, Japan
2Corporate Research Laboratories, Mitsubishi Rayon Co., Ltd, Hiroshima, Japan

In this paper, we report chemometric approach for structural analysis of branched copolymers. To evaluate chemical compositions and degree of branching (DB) values in branched copolymers, multivariate analyses, such as principal component analysis (PCA) and partial least-squares (PLS) regression, were applied to the 13C nuclear magnetic resonance (NMR) spectra of the carbonyl carbons of the copolymers prepared by initiator-fragment incorporation radical copolymerization of ethylene glycol dimethacrylate (EGDMA) and tert-butyl methacrylate (TBMA) with dimethyl 2,2′-azobisisobutyrate (MAIB). PCA successfully extracted information on monomeric units, such as EGDMA units, TBMA units and MAIB fragments, the last of which were incorporated via initiation and primary radical termination. The chemical compositions and DB values of the copolymers were predicted by PLS regression. Proper selection of a training set was found to be important for the prediction: the training set has to contain branched copolymers along with poly(EGDMA) and poly(TBMA). PLS regression using the appropriate training set allowed us to predict quantitatively the chemical compositions and DB values, without any assignments of the individual peaks.


Received: November 24, 2015 , Revised: December 27, 2015
Accepted: January 06, 2016 , Published online: March 02, 2016
© 2016 The Society of Polymer Science, Japan

NatureAbstract (Nature)


SPARC Japan

Terms of Use | Privacy Policy