Scaling exponent and dispersity of polymers in solution by diffusion NMR

Nathan H. Williamson*, Magnus Röding, Stanley J. Miklavcic, Magnus Nydén

*Corresponding author for this work

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Molecular mass distribution measurements by pulsed gradient spin echo nuclear magnetic resonance (PGSE NMR) spectroscopy currently require prior knowledge of scaling parameters to convert from polymer self-diffusion coefficient to molecular mass. Reversing the problem, we utilize the scaling relation as prior knowledge to uncover the scaling exponent from within the PGSE data. Thus, the scaling exponent—a measure of polymer conformation and solvent quality—and the dispersity (Mw/Mn) are obtainable from one simple PGSE experiment. The method utilizes constraints and parametric distribution models in a two-step fitting routine involving first the mass-weighted signal and second the number-weighted signal. The method is developed using lognormal and gamma distribution models and tested on experimental PGSE attenuation of the terminal methylene signal and on the sum of all methylene signals of polyethylene glycol in D2O. Scaling exponent and dispersity estimates agree with known values in the majority of instances, leading to the potential application of the method to polymers for which characterization is not possible with alternative techniques.

Original languageEnglish
Pages (from-to)393-397
Number of pages5
JournalJournal of Colloid and Interface Science
Volume493
DOIs
Publication statusPublished - 1 May 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Elsevier Inc.

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

Keywords

  • Pulsed gradient spin echo
  • Pulsed field gradient
  • Nuclear Magnetic Resonance spectroscopy
  • Molecular weight distribution
  • Polymers
  • DOSY
  • Polydispersity Index
  • Lognormal distribution
  • Molar mass
  • Self-diffusion
  • Flory exponent
  • Gamma distribution
  • End-group analysis
  • Scaling law

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