Literature DB >> 27116223

The lognormal and gamma distribution models for estimating molecular weight distributions of polymers using PGSE NMR.

Nathan H Williamson1, Magnus Nydén2, Magnus Röding3.   

Abstract

We present comprehensive derivations for the statistical models and methods for the use of pulsed gradient spin echo (PGSE) NMR to characterize the molecular weight distribution of polymers via the well-known scaling law relating diffusion coefficients and molecular weights. We cover the lognormal and gamma distribution models and linear combinations of these distributions. Although the focus is on methodology, we illustrate the use experimentally with three polystyrene samples, comparing the NMR results to gel permeation chromatography (GPC) measurements, test the accuracy and noise-sensitivity on simulated data, and provide code for implementation.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Gamma distribution; Lognormal distribution; Molecular weight distribution; Polydispersity; Pulsed gradient spin echo NMR; Scaling law; Self-diffusion

Year:  2016        PMID: 27116223     DOI: 10.1016/j.jmr.2016.04.007

Source DB:  PubMed          Journal:  J Magn Reson        ISSN: 1090-7807            Impact factor:   2.229


  3 in total

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Authors:  Khandokar Sadique Faisal; Andrew J Clulow; Marta Krasowska; Todd Gillam; Stanley J Miklavcic; Nathan H Williamson; Anton Blencowe
Journal:  J Colloid Interface Sci       Date:  2021-08-17       Impact factor: 8.128

2.  Clear distinction between CAC and CMC revealed by high-resolution NMR diffusometry for a series of bis-imidazolium gemini surfactants in aqueous solutions.

Authors:  Kosma Szutkowski; Żaneta Kołodziejska; Zuzanna Pietralik; Igor Zhukov; Andrzej Skrzypczak; Katarzyna Materna; Maciej Kozak
Journal:  RSC Adv       Date:  2018-11-22       Impact factor: 4.036

3.  The Power of Heterogeneity: Parameter Relationships from Distributions.

Authors:  Magnus Röding; Siobhan J Bradley; Nathan H Williamson; Melissa R Dewi; Thomas Nann; Magnus Nydén
Journal:  PLoS One       Date:  2016-05-16       Impact factor: 3.240

  3 in total

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