Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-10T08:55:01.008Z Has data issue: false hasContentIssue false

The interplay between network morphology and degradation kinetics of polymers: Theoretical and experimental analysis by means of a 2D model system

Published online by Cambridge University Press:  09 December 2019

Rainhard Machatschek
Affiliation:
Institute of Biomaterial Science, Helmholtz-Zentrum Geesthacht and Berlin-Brandenburg Center for Regenerative Therapies, Kantstraße 55, 14513 Teltow, Germany
Shivam Saretia
Affiliation:
Institute of Biomaterial Science, Helmholtz-Zentrum Geesthacht and Berlin-Brandenburg Center for Regenerative Therapies, Kantstraße 55, 14513 Teltow, Germany Institute of Chemistry, University of Potsdam, Karl-Liebknecht-Straße 24-25, 14469 Potsdam, Germany
Andreas Lendlein*
Affiliation:
Institute of Biomaterial Science, Helmholtz-Zentrum Geesthacht and Berlin-Brandenburg Center for Regenerative Therapies, Kantstraße 55, 14513 Teltow, Germany Institute of Chemistry, University of Potsdam, Karl-Liebknecht-Straße 24-25, 14469 Potsdam, Germany
*
*Correspondence to: Andreas Lendlein E-mail: andreas.lendlein@hzg.de
Get access

Abstract

Network formation by cross-linking is a common method to incorporate functions like elastic deformability, shape-memory capability or hydrogel formation into polymer materials for medical applications. Since these materials are often intended to degrade, their design would benefit from a quantitative prediction of the interdependence between network architecture and degradation behavior. Here, we introduce a quantitative description of the degradation behavior of polymer networks. A simplified model was developed under the assumption of having an ideal network, where all network strands are terminated by network nodes and each node is connected to the same number of strands. To describe the degradation of real networks, the model was modified by allowing for a varying connectivity of network nodes, which also included free chain-ends. The models were validated by comparison with Langmuir monolayer degradation data from 2D networks formed by cross-linking oligo(ε-caprolactone)diols with dialdehydes. We found that both the ideal network hypothesis and the real network model were in excellent agreement with the experimental data, with the ideal network hypothesis requiring longer network strands than the real network to result in the same degradation behavior. The models were further used to calculate the degradation curves of the corresponding, non cross-linked molecules. By comparison, it was found that the network formation increases the time required to reach 50% degradation of oligo(ε-caprolactone)diols by only 20%. This difference mainly arises from attaching free chain ends to network points.

Type
Articles
Copyright
Copyright © Materials Research Society 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Kowalski, P. S., Bhattacharya, C., Afewerki, S. and Langer, R., ACS Biomaterials Science & Engineering 4 (11), 3809-3817 (2018).CrossRefGoogle Scholar
Peterson, G. I., Dobrynin, A. V. and Becker, M. L., Advanced Healthcare Materials 6 (21), 1700694 (2017).10.1002/adhm.201700694CrossRefGoogle Scholar
Neffe, A. T., Hanh, B. D., Steuer, S. and Lendlein, A., Advanced Materials 21 (32-33), 3394-3398 (2009).CrossRefGoogle Scholar
Serrano, M. C., Carbajal, L. and Ameer, G. A., Advanced Materials 23 (19), 2211-2215 (2011).10.1002/adma.201004566CrossRefGoogle Scholar
Osada, Y. and Matsuda, A., Nature 376 (6537), 219-219 (1995).CrossRefGoogle Scholar
Lendlein, A., Balk, M., Tarazona, N. A. and Gould, O. E. C., Biomacromolecules 20 (10), 3627-3640 (2019).CrossRefGoogle Scholar
Yakacki, C. M., Shandas, R., Lanning, C., Rech, B., Eckstein, A. and Gall, K., Biomaterials 28 (14), 2255-2263 (2007).CrossRefGoogle Scholar
Darwis, D., Mitomo, H., Enjoji, T., Yoshii, F. and Makuuchi, K., Polymer Degradation and Stability 62 (2), 259-265 (1998).CrossRefGoogle Scholar
Sevim, K. and Pan, J., Acta Biomaterialia 66, 192-199 (2018).10.1016/j.actbio.2017.11.023CrossRefGoogle Scholar
Machatschek, R., Schulz, B. and Lendlein, A., Macromolecular Rapid Communications 40 (1), 1800611 (2019).CrossRefGoogle Scholar
Saretia, S., Machatschek, R., Schulz, B. and Lendlein, A., Biomedical Materials 14 (3), 034103 (2019).10.1088/1748-605X/ab0cefCrossRefGoogle Scholar
Zotzmann, J., Behl, M., Hofmann, D. and Lendlein, A., Advanced Materials 22 (31), 3424-3429 (2010).CrossRefGoogle Scholar
Schöne, A.-C., Kratz, K., Schulz, B. and Lendlein, A., Polymer Degradation and Stability 131, 114-121 (2016).10.1016/j.polymdegradstab.2016.07.010CrossRefGoogle Scholar
Ivanova, T. Z., Panaiotov, I., Boury, F., Proust, J. E. and Verger, R., Colloid and Polymer Science 275 (5), 449-457 (1997).CrossRefGoogle Scholar
Glomb, M. A. and Monnier, V. M., J. Biol. Chem. 270 (17), 10017-10026 (1995).CrossRefGoogle Scholar
Müller, V., Hinaut, A., Moradi, M., Baljozovic, M., Jung, T. A., Shahgaldian, P., Möhwald, H., Hofer, G., Kröger, M., King, B. T., Meyer, E., Glatzel, T. and Schlüter, A. D., Angew. Chem. Int. Ed. 57 (33), 10584-10588 (2018).CrossRefGoogle Scholar
Feng, X. and Schlüter, A. D., Angew. Chem. Int. Ed. 57 (42), 13748-13763 (2018).CrossRefGoogle Scholar