Data underlying the Thesis Chapter: "Dynamic Covalent Urea-Catalysed Self-Healing of Thiol-Maleimide Networks"

DOI:10.4121/6f520cd5-cfd3-4143-bcd7-443aec887c95.v1
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DOI: 10.4121/6f520cd5-cfd3-4143-bcd7-443aec887c95

Datacite citation style

Spitzbarth, Benjamin; Sünnen, Lotte; Lohrmann, Steffen; Ardoin, Mélodie; Eelkema, Rienk (2023): Data underlying the Thesis Chapter: "Dynamic Covalent Urea-Catalysed Self-Healing of Thiol-Maleimide Networks". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/6f520cd5-cfd3-4143-bcd7-443aec887c95.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Data underlying the thesis chapter "Dynamic Covalent Urea-Catalysed Self-Healing of Thiol-Maleimide Networks". This data underlies the work which is part of the PhD Thesis "Applications of Dynamic Covalent Chemistry" by Benjamin Spitzbarth. The main text and supplementary data of this work will be published as part thereof. This work aims to demonstrate how dynamic covalent urea units can be used to catalyse the exchange of thiol-maleimide adducts and effectively lower the temperature at which a meaningful exchange occurs. More specifically, we implemented a catalytic amount of DCv urea units into a thiol-maleimide networks and show how this improves the self-healing ability of these networks at lower temperatures. We supply here the NMR data of the kinetic measurements to determine the half-live of different maleimides and maleimide adduct in addition and exchange reactions (in the form of .mnova files), as well as the rheology data characterising reference materials, externally catalysed self-healing materials, and dual synergistic materials (in the form of .xlsx files). Please refer to the readme file, explaining the experiment identifiers and conditions of each experiment.

History

  • 2023-10-30 first online, published, posted

Publisher

4TU.ResearchData

Format

NMR files as .mnova; Rheology data as .xslx

Funding

  • European Union's Horizon 2020 research and innovation program (grant code STG–677576) European Research Council

Organizations

TU Delft, Faculty of Applied Sciences, Department of Chemical Engineering

DATA

Files (57)