Advanced search
1 file | 5.72 MB Add to list

From chain growth to step growth polymerization of photoreactive poly-epsilon-caprolactone : the network topology of bioresorbable networks as tool in tissue engineering

Author
Organization
Project
Abstract
Control of the network topology by selection of an appropriate cross-linking chemistry is introduced as a new strategy to improve the elasticity and toughness of bioresorbable networks. The development of novel photocross-linkable and bioresorbable oligomers is essential for the application of light-based 3D-printing techniques in the context of tissue engineering. Although light-based 3D-printing techniques are characterized by an increased resolution and manufacturing speed as compared to extrusion-based 3D-printing, their application remains limited. Via chemical modification, poly-epsilon-caprolactone (PCL) is functionalized with photoreactive end groups such as acrylates, alkenes, and alkynes. Based on these precursors, networks with different topologies are designed via chain growth polymerization, step growth polymerization, or a combination thereof. The influence of the network topology and the concomitant cross-linking chemistry on the thermal, mechanical, and biological properties are elucidated together with their applicability in digital light processing (DLP). Photocross-linkable PCL with an elongation at break of 736.3 +/- 47% and an ultimate strength of 21.3 +/- 0.8 MPa is realized, which is approximately tenfold higher compared to the current state-of-the-art. Finally, extremely elastic DLP-printed dog bones are developed which can fully retrieve their initial length upon stress relieve at an elongation of 1000%.
Keywords
THIOL-ENE, KINETICS, PHOTOPOLYMERIZATIONS, CHEMISTRY

Downloads

  • (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 5.72 MB

Citation

Please use this url to cite or link to this publication:

MLA
Thijssen, Quinten, et al. “From Chain Growth to Step Growth Polymerization of Photoreactive Poly-Epsilon-Caprolactone : The Network Topology of Bioresorbable Networks as Tool in Tissue Engineering.” ADVANCED FUNCTIONAL MATERIALS, vol. 32, no. 20, 2022, doi:10.1002/adfm.202108869.
APA
Thijssen, Q., Parmentier, L., Augustyniak, E., Mouthuy, P.-A., & Van Vlierberghe, S. (2022). From chain growth to step growth polymerization of photoreactive poly-epsilon-caprolactone : the network topology of bioresorbable networks as tool in tissue engineering. ADVANCED FUNCTIONAL MATERIALS, 32(20). https://doi.org/10.1002/adfm.202108869
Chicago author-date
Thijssen, Quinten, Laurens Parmentier, Edyta Augustyniak, Pierre-Alexis Mouthuy, and Sandra Van Vlierberghe. 2022. “From Chain Growth to Step Growth Polymerization of Photoreactive Poly-Epsilon-Caprolactone : The Network Topology of Bioresorbable Networks as Tool in Tissue Engineering.” ADVANCED FUNCTIONAL MATERIALS 32 (20). https://doi.org/10.1002/adfm.202108869.
Chicago author-date (all authors)
Thijssen, Quinten, Laurens Parmentier, Edyta Augustyniak, Pierre-Alexis Mouthuy, and Sandra Van Vlierberghe. 2022. “From Chain Growth to Step Growth Polymerization of Photoreactive Poly-Epsilon-Caprolactone : The Network Topology of Bioresorbable Networks as Tool in Tissue Engineering.” ADVANCED FUNCTIONAL MATERIALS 32 (20). doi:10.1002/adfm.202108869.
Vancouver
1.
Thijssen Q, Parmentier L, Augustyniak E, Mouthuy P-A, Van Vlierberghe S. From chain growth to step growth polymerization of photoreactive poly-epsilon-caprolactone : the network topology of bioresorbable networks as tool in tissue engineering. ADVANCED FUNCTIONAL MATERIALS. 2022;32(20).
IEEE
[1]
Q. Thijssen, L. Parmentier, E. Augustyniak, P.-A. Mouthuy, and S. Van Vlierberghe, “From chain growth to step growth polymerization of photoreactive poly-epsilon-caprolactone : the network topology of bioresorbable networks as tool in tissue engineering,” ADVANCED FUNCTIONAL MATERIALS, vol. 32, no. 20, 2022.
@article{8747700,
  abstract     = {{Control of the network topology by selection of an appropriate cross-linking chemistry is introduced as a new strategy to improve the elasticity and toughness of bioresorbable networks. The development of novel photocross-linkable and bioresorbable oligomers is essential for the application of light-based 3D-printing techniques in the context of tissue engineering. Although light-based 3D-printing techniques are characterized by an increased resolution and manufacturing speed as compared to extrusion-based 3D-printing, their application remains limited. Via chemical modification, poly-epsilon-caprolactone (PCL) is functionalized with photoreactive end groups such as acrylates, alkenes, and alkynes. Based on these precursors, networks with different topologies are designed via chain growth polymerization, step growth polymerization, or a combination thereof. The influence of the network topology and the concomitant cross-linking chemistry on the thermal, mechanical, and biological properties are elucidated together with their applicability in digital light processing (DLP). Photocross-linkable PCL with an elongation at break of 736.3 +/- 47% and an ultimate strength of 21.3 +/- 0.8 MPa is realized, which is approximately tenfold higher compared to the current state-of-the-art. Finally, extremely elastic DLP-printed dog bones are developed which can fully retrieve their initial length upon stress relieve at an elongation of 1000%.}},
  articleno    = {{2108869}},
  author       = {{Thijssen, Quinten and Parmentier, Laurens and Augustyniak, Edyta and Mouthuy, Pierre-Alexis and Van Vlierberghe, Sandra}},
  issn         = {{1616-301X}},
  journal      = {{ADVANCED FUNCTIONAL MATERIALS}},
  keywords     = {{THIOL-ENE,KINETICS,PHOTOPOLYMERIZATIONS,CHEMISTRY}},
  language     = {{eng}},
  number       = {{20}},
  pages        = {{14}},
  title        = {{From chain growth to step growth polymerization of photoreactive poly-epsilon-caprolactone : the network topology of bioresorbable networks as tool in tissue engineering}},
  url          = {{http://doi.org/10.1002/adfm.202108869}},
  volume       = {{32}},
  year         = {{2022}},
}

Altmetric
View in Altmetric
Web of Science
Times cited: