Nano-structured dynamic Schiff base cues as robust self-healing polymers for biomedical and tissue engineering applications: a review

Malik, US, Niazi, MBK, Jahan, Z, Zafar, MI, Vo, D-VN and Sher, F ORCID logoORCID: https://orcid.org/0000-0003-2890-5912, 2022. Nano-structured dynamic Schiff base cues as robust self-healing polymers for biomedical and tissue engineering applications: a review. Environmental Chemistry Letters, 20 (1), pp. 495-517. ISSN 1610-3653

[thumbnail of 1567558_Sher.pdf]
Preview
Text
1567558_Sher.pdf - Post-print

Download (1MB) | Preview

Abstract

Polymer materials are vulnerable to damages, failures, and degradations, making them economically unreliable. Self-healing polymers, on the other hand, are multifunctional materials with superior properties of autonomic recovery from physical damages. These materials are suitable for biomedical and tissue engineering in terms of cost and durability. Schiff base linkages-based polymer materials are one of the robust techniques owing to their simple self-healing mechanism. These are dynamic reversible covalent bonds, easy to fabricate at mild conditions, and can self-reintegrate after network disruption at physiological conditions making them distinguished. Here we review self-healing polymer materials based on Schiff base bonds. We discuss the Schiff base bond formation between polymeric networks, which explains the self-healing phenomenon. These bonds have induced 100% recovery in optimal cases.

Item Type: Journal article
Publication Title: Environmental Chemistry Letters
Creators: Malik, U.S., Niazi, M.B.K., Jahan, Z., Zafar, M.I., Vo, D.-V.N. and Sher, F.
Publisher: Springer Science and Business Media LLC
Date: February 2022
Volume: 20
Number: 1
ISSN: 1610-3653
Identifiers:
Number
Type
10.1007/s10311-021-01337-1
DOI
1567578
Other
Divisions: Schools > School of Science and Technology
Record created by: Linda Sullivan
Date Added: 25 Jul 2022 13:47
Last Modified: 31 Oct 2022 03:00
URI: https://irep.ntu.ac.uk/id/eprint/46701

Actions (login required)

Edit View Edit View

Statistics

Views

Views per month over past year

Downloads

Downloads per month over past year