Polymers capable of thermally controlled reversible bonding reactions are promising candidates for stimuli responsive materials, as required for self-healing or drug delivery materials. In order to investigate how the dynamic reactions can be controlled, effective analytical tools are demanded that are capable of analyzing not only the polymers but can also monitor the respective bonding reactions. Herein, we employ size exclusion chromatography in a newly developed temperature dependent mode (TD SEC) for the in situ characterization of polymers that undergo retro Diels-Alder (rDA) reaction at temperatures higher than 60 °C. Monitoring the evolution of the molar mass distribution of the polymers during the rDA reaction and evaluating the data quantitatively gives detailed information about the extent of the reaction and allows elucidating structural parameters that can be used for controlling the polymers debonding behavior.
In contrast to spectroscopic techniques, TD SEC analyzes only the size of the polymers, hence the polymers do not need to fulfill any particular requirements (e.g. presence of detectable functional groups) but only need to be soluble in the TD SEC, which makes the method universally applicable. Side effects that might bias the results are minimized by using a high temperature chromatograph that allows performing the analysis in a broad temperature range (60 – 200 °C) and in different solvents. Thus, the analysis can be performed under the exact conditions that are required for the bonding reactions and an in situ image is provided.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa.de:bsz:14-qucosa-207589 |
Date | 01 August 2016 |
Creators | Brandt, Josef |
Contributors | Technische Universtität Dresden, Fakultät Mathematik und Naturwissenschaften, Prof. Dr. Brigitte Voit, PD Dr. Albena Lederer, Prof. Dr. Brigitte Voit, Prof. Dr. Peter Schoenmakers |
Publisher | Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | doc-type:doctoralThesis |
Format | application/pdf |
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