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Structural Characterization of Multicomponent Copolyesters by Mass Spectrometry
The structural characterization and composition of five random copolyesters, originating from 1,4-butanediol and mixtures of succinic, adipic, sebacic, and terephthalic acids, were obtained by analysis of their fast atom bombardment (FAB) and their matrix-assisted laser desorption ionization (MALDI)...
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Published in: | Macromolecules 1998-12, Vol.31 (25), p.8666-8676 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The structural characterization and composition of five random copolyesters, originating from 1,4-butanediol and mixtures of succinic, adipic, sebacic, and terephthalic acids, were obtained by analysis of their fast atom bombardment (FAB) and their matrix-assisted laser desorption ionization (MALDI) mass spectra. Multicomponent condensation copolymers may sometimes prove difficult to characterize by conventional techniques, whereas mass spectrometry is able to handle them. Once the choice between Bernoullian or Markoffian models has been made, the determination of copolymer composition, number-average sequence length, and related quantities can be achieved by applying well-defined analytical equations. The theoretical mass spectra of multicomponent copolymers are remarkably simple, and the number of peaks appearing in each copolymer mass spectrum is easily predictable. Different kinds of spectral fitting algorithms may help in the actual computations, and it has been shown that the apparent complexity of mass spectra of copolymers is due to the presence of mass series bearing different end groups. By selecting a single mass series, one obtains an experimental spectrum immediately comparable to the theoretical one. Detailed examples, together with a discussion on the reliability of results, are given to apply the computation procedures and to gain proper understanding of the concepts involved. |
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ISSN: | 0024-9297 1520-5835 |
DOI: | 10.1021/ma980821c |