
AbstractThe theory of step‐growth polymerizations including the cascade theory is discussed in the light of new results focussing on the role of cyclization reactions. The identification of cyclic oligomers and polymers in reaction products of step‐growth polymerizations has been eased considerably by means of MALDI‐TOF mass spectrometry. Experimental examples concern syntheses of polyesters, polycarbonates, polyamides, polyimides, poly(ether sulfone)s, poly(ether ketone)s and polyurethanes. It was found in all cases that the percentage and molecular weight of the cycles increases when the reaction conditions favor high molecular weights. In the absence of side reactions all reaction products will be cycles when conversion approaches 100%. Cyclization may even take place in the nematic phase but even‐numbered cycles are favored over odd‐numbered ones due to electronic interactions between mesogens aligned in parallel. In contrast to Flory's cascade theory, cyclization also plays a decisive role in polycondensations of abn‐type monomers, and at 100% conversion all hyperbranched polymers have a cyclic core. Furthermore, it is demonstrated that in a2+b3 polycondensations intensive cyclization in the early stages of the process has the consequence that either no gelation occurs or the resulting networks consist of cyclic and bicyclic oligomers as building blocks. Finally, a comparison between cyclization of synthetic polymers and biopolymers is discussed. Schematic representation of a network structure mainly consisting of cyclic oligomers and multicyclic building blocks as derived from “a2” + “b3” polycondensation.magnified imageSchematic representation of a network structure mainly consisting of cyclic oligomers and multicyclic building blocks as derived from “a2” + “b3” polycondensation.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 233 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
