Analytical strategy for the molecular weight determination of random copolymers of poly(methyl methacrylate) and poly(methacrylic acid) View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-06

AUTHORS

Rémi Giordanengo, Stéphane Viel, Manuel Hidalgo, Béatrice Allard-Breton, André Thévand, Laurence Charles

ABSTRACT

Molecular weight characterization of random amphiphilic copolymers currently represents an analytical challenge. In particular, molecules composed of methacrylic acid (MAA) and methyl methacrylate (MMA) as the repeat units raise issues in commonly used techniques. The present study shows that when random copolymers cannot be properly ionized by MALDI, and hence detected and measured in MS, one possible analytical strategy is to transform them into homopolymers, which are more amenable to this ionization technique. Then, by combining the molecular weight of the so-obtained homopolymers, as measured by MS, with the relative molar proportion of the MMA and MMA units, as given by (1)H NMR spectrum, one can straightforwardly estimate the molecular weight of the initial copolymer. A methylation reaction was performed to transform MAA-MMA copolymer samples into PMMA homopolymers, using trimethylsilyldiazomethane as a derivatization agent. Weight average molecular weight (M(w)) parameters of the MAA-MMA copolymers could then be derived from M(w) values obtained for the methylated MAA-MMA molecules by MALDI, which were also validated by pulsed gradient spin echo (PGSE) NMR. An alkene function in one of the studied copolymer end-groups was also shown to react with the methylation agent, giving rise to MMA-like polymeric by-products characterized by tandem mass spectrometry and which could be avoided by adjusting the amount of the trimethylsilyldiazomethane in the reaction medium. More... »

PAGES

1075-1085

Identifiers

URI

http://scigraph.springernature.com/pub.10.1016/j.jasms.2010.02.007

DOI

http://dx.doi.org/10.1016/j.jasms.2010.02.007

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1039178488

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20202862


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