Determination of Chemical Composition and Monomer Sequence Distributions of Methacrylate Copolymers by Multivariate Analysis of NMR Spectra

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  • HIRANO Tomohiro
    Department of Applied Chemistry, Tokushima University
  • MOMOSE Hikaru
    Department of Applied Chemistry, Tokushima University Materials Characterization Laboratory, Mitsubishi Chemical Corporation
  • KAMIIKE Ryota
    Department of Applied Chemistry, Tokushima University R&D center, Nippon A&L Inc.
  • UTE Koichi
    Department of Applied Chemistry, Tokushima University

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Other Title
  • NMRスペクトルの多変量解析によるメタクリレート系共重合体の組成・連鎖分布解析
  • NMR スペクトル ノ タヘンリョウ カイセキ ニ ヨル メタクリレートケイ キョウ ジュウゴウタイ ノ ソセイ ・ レンサ ブンプ カイセキ

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Abstract

<p>Multivariate analysis was applied to nuclear magnetic resonance (NMR) spectra of methacrylate copolymers. Principal component analysis (PCA) of 13C NMR spectra of linear copolymers of methyl methacrylate (MMA) and tert-butyl methacrylate (TBMA) successfully extracted information on chemical compositions and monomer sequences. Quantitative analysis of the chemical composition and monomer sequence was achieved by partial least-squares (PLS) regression using NMR spectra of the corresponding homopolymers and their blends as a training dataset. PCA was also useful for the extraction of information on chemical composition in branched copolymers prepared by initiator-fragment incorporation radical copolymerization of TBMA and ethylene glycol dimethacrylate with dimethyl 2,2’-azobis(isobutyrate). The chemical compositions and degree of branching were predicted by PLS regression using NMR spectra of the corresponding homopolymers, their blends and branched copolymers as a training dataset. In addition, PCA was found to be a good measure to evaluate the monomer sequence distribution in linear copolymers of MMA and benzyl methacrylate (BnMA) prepared by various polymer reactions. Furthermore, PCA of 1H NMR spectra of linear copolymers of MMA and BnMA was applied to extract information on chemical compositions and monomer sequences. Monomer reactivity ratios were reasonably estimated from a single sample using the diad sequence distributions predicted by PLS regression.</p>

Journal

  • BUNSEKI KAGAKU

    BUNSEKI KAGAKU 71 (9), 471-482, 2022-09-05

    The Japan Society for Analytical Chemistry

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