徳島大学 教育・研究者情報データベース(EDB)

1. 徳島大学.大学院社会産業理工学研究部.理工学域.応用化学系.物質合成化学分野(2017年4月1日〜)

1. (英) Kamiike Ryota

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2. 平野 朋広([徳島大学.大学院社会産業理工学研究部.理工学域.応用化学系.物質合成化学分野]/[徳島大学.理工学部.理工学科.応用化学システムコース.物質合成化学講座])

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3. 右手 浩一

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(英) Multivariate statistical analysis of ¹H NMR data for binary and ternary blends of copolymers to determine the chemical composition and blending fractions of the components

(英) Statistical 1H nuclear magnetic resonance (NMR) analysis was conducted for ternary blends of copolymers. Two out of three monomers, acrylonitrile, styrene, and α-methylstyrene, were radically polymerized to synthesize three kinds of copolymers that were mixed to prepare binary and ternary blends of the copolymers. The 1H NMR spectral matrix of the copolymers and their blends (explanatory variables) was combined with the blending parameter matrix (objective variables). Cross-validation with the least absolute shrinkage and selection operator regression confirmed that excellent regression models were constructed with the dataset composed of data for eight copolymers and forty-five binary blends to predict the blending parameters, such as the chemical composition and mole fraction of the component copolymers, in the binary blends. Accordingly, the models were applied to predict the blending parameters in the ternary blends, resulting in successful predictions with high accuracy. Other regularized regression models, such as Ridge regression and Elastic Net, were also examined.

(日) アクリロニトリル，スチレンおよびα-メチルスチレンのうちの2つのモノマーからなる2元共重合体を合成し，その3元ブレンドの1H NMRスペクトルの多変量解析により，ブレンドパラメータを推定した．