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Polydispersity Ratio and Its Application for the Characterization of Poloxamers

  • Gergő Róth
    Gergő Róth
    Department of Applied Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
    Doctoral School of Chemistry, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
    More by Gergő Róth
  • Tibor Nagy
    Tibor Nagy
    Department of Applied Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
    More by Tibor Nagy
  • Ákos Kuki
    Ákos Kuki
    Department of Applied Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
    More by Ákos Kuki
  • Mahir Hashimov
    Mahir Hashimov
    Department of Applied Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
    Doctoral School of Chemistry, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
  • Zsófia Vonza
    Zsófia Vonza
    Department of Applied Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
  • István Timári
    István Timári
    Department of Organic Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
  • Miklós Zsuga
    Miklós Zsuga
    Department of Applied Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
  • , and 
  • Sándor Kéki*
    Sándor Kéki
    Department of Applied Chemistry, Faculty of Science and Technology, University of Debrecen, Egyetem tér 1, H-4032 Debrecen, Hungary
    *Email: [email protected]. Fax: +36 52 518662.
Cite this: Macromolecules 2021, 54, 21, 9984–9991
Publication Date (Web):October 7, 2021
https://doi.org/10.1021/acs.macromol.1c01552
Copyright © 2021 American Chemical Society

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    Abstract

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    The data processing and visualization methods are of paramount importance in the mass spectrometry of copolymers. To determine the copolymer composition, in this article, a robust algorithm is proposed for the compositional assignment and for the estimation of the relative abundance of each species present in copolymer mass spectra. Our homemade software enables the accurate calculation of the compositional drift, i.e., the variation of copolymer composition with the polymer chain lengths. Furthermore, we introduce a novel copolymer quantity, namely, the polydispersity (also called as dispersity) ratio (PDR) of the comonomers, and establish a characteristic relationship between the shape of the composition drift curves and the PDR values. This relation allows, for instance, a quick visual recognition of the presence of diblocks in a triblock copolymer by means of mass spectrometry. Our approach is demonstrated by the analysis of various poloxamers, i.e., polyethylene oxide (PEO)–polypropylene oxide (PPO) block copolymers up to the average molecular weight of approximately 4000 g/mol. The determined number-average molecular weights and the ethylene oxide contents were also confirmed by nuclear magnetic resonance spectroscopy. Dynamic light scattering experiments revealed that small variations in the copolymer composition significantly affect the properties of the copolymer.

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.macromol.1c01552.

    • Mass spectra, NMR spectra, and DLS measurements (PDF)

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    Cited By

    This article is cited by 3 publications.

    1. Tibor Nagy, Gergő Róth, Máté Benedek, Ákos Kuki, István Timári, Miklós Zsuga, Sándor Kéki. Enhanced Copolymer Characterization for Polyethers Using Gel Permeation Chromatography Combined with Artificial Neural Networks. Analytical Chemistry 2023, 95 (28) , 10504-10511. https://doi.org/10.1021/acs.analchem.2c02913
    2. Tibor Nagy, Akos Kuki, Gergo Roth, Zuura Kaldybek Kyzy, Alifya Balqis Zatalini, David Nyul, Miklos Zsuga, Sandor Keki. Characterization of polyacrylamide diblock copolymers by mass spectrometry combined with Mass-remainder analysis (MARA). Polymer Testing 2023, 117 , 107834. https://doi.org/10.1016/j.polymertesting.2022.107834
    3. Ákos Kuki, Gergő Róth, Anna Nagy, Miklós Zsuga, Sándor Kéki, Tibor Nagy. A Short-Cut Data Mining Method for the Mass Spectrometric Characterization of Block Copolymers. Processes 2022, 10 (1) , 42. https://doi.org/10.3390/pr10010042

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