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Water Swelling Behavior of Poly(ethylene glycol)-Based Polyurethane Networks.
Albers, Peter T M; van der Ven, Leendert G J; van Benthem, Rolf A T M; Esteves, A Catarina C; de With, Gijsbertus.
Afiliação
  • Albers PTM; Laboratory of Physical Chemistry, Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • van der Ven LGJ; Dutch Polymer Institute (DPI), P.O. Box 902, 5600 AX Eindhoven, The Netherlands.
  • van Benthem RATM; Laboratory of Physical Chemistry, Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • Esteves ACC; Laboratory of Physical Chemistry, Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • de With G; DSM Ahead BV Netherlands, P.O. Box 18, 6160 MD Geleen, The Netherlands.
Macromolecules ; 53(3): 862-874, 2020 Feb 11.
Article em En | MEDLINE | ID: mdl-32063654
ABSTRACT
Defects in a polymer network complicate an accurate calculation of structural parameters such as the molar mass between cross-links M c, typically obtained from experimental swelling data. In this paper the formation and structure of poly(ethylene glycol) (PEG)-based polyurethane networks containing PEG-mono methyl ether dangling chains are studied. The phantom network model can describe the swelling behavior of these networks only when a composition-dependent interaction parameter is used and the formation of allophanates is accounted for. A clear transition in the network formation is found at the PEG network precursor molar mass at which entanglements are formed in the melt. Correction factors based on structure calculations using the Miller-Macosko-Vallés probability approach are proposed and validated for an accurate calculation of the M c of these defect-containing networks. This provides a new approach for studies that requires an accurate estimate of the M c, only based on experimentally straightforward swelling experiments.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article