Jump to main content
Jump to site search

Issue 37, 2017
Previous Article Next Article

Molecular weight prediction in polystyrene blends. Unprecedented use of a genetic algorithm in pulse field gradient spin echo (PGSE) NMR

Author affiliations

Abstract

A genetic algorithm that uses boxcar functions (diffGA) has been applied for the first time in PGSE NMR. It reconstructs accurate diffusion coefficients for all the components of the mixture, and therefore predicts correct weight-average molecular weights for all of them. The results reported herein complement those obtained with established methods such as ITAMeD, CONTIN and TRAIn algorithms, and provide a detailed solution picture. Its robustness and limits have been stretched in order to ascertain the minimum separation within diffusion coefficients or relative proportion between components. In addition, the new genetic algorithm has been also applied to a mixture of small molecules, providing excellent results at very low computational times.

Graphical abstract: Molecular weight prediction in polystyrene blends. Unprecedented use of a genetic algorithm in pulse field gradient spin echo (PGSE) NMR

Back to tab navigation

Supplementary files

Publication details

The article was received on 04 Aug 2017, accepted on 31 Aug 2017 and first published on 18 Sep 2017


Article type: Paper
DOI: 10.1039/C7SM01569K
Citation: Soft Matter, 2017,13, 6620-6626
  •   Request permissions

    Molecular weight prediction in polystyrene blends. Unprecedented use of a genetic algorithm in pulse field gradient spin echo (PGSE) NMR

    F. M. Arrabal-Campos, J. D. Álvarez, A. García-Sancho and I. Fernández, Soft Matter, 2017, 13, 6620
    DOI: 10.1039/C7SM01569K

Search articles by author

Spotlight

Advertisements