Application of Shape Memory and Self-Healable Polymers/Composites in the Biomedical Field: A Review

Abstract

Shape memory-assisted self-healing polymers have drawn attention over the past few years owing to their interdisciplinary and wide range of applications. Self-healing and shape memory are two approaches used to improve the applicability of polymers in the biomedical field. Combining both these approaches in a polymer composite opens new possibilities for its use in biomedical applications, such as the "close then heal" concept, which uses the shape memory capabilities of polymers to bring injured sections together to promote autonomous healing. This review focuses on using shape memory-assisted self-healing approaches along with their respective affecting factors for biomedical applications such as tissue engineering, drug delivery, biomaterial-inks, and 4D printed scaffolds, soft actuators, wearable electronics, etc. In addition, quantification of self-healing and shape memory efficiency is also discussed. The challenges and prospects of these polymers for biomedical applications have been summarized.

Figure 1

Various interactions involved in self-healing of a polymeric matrix.

Figure 2

(a) Schematic representation of PBISI-based SMP’s mechanism during shape recovery. 3D diagrams of stress-controlled programming cycles for the (b) PBSI SMP and (c) PBISI-2 SMP. An asterisk denotes the initial point of the cycling process. (d) Graph showing percent shape fixity and shape recovery of PBISI-based SMPs. (e) Shape recovery time of PBISI-2 SMP scaffold with temperature (adapted from ref (45)).

Figure 3

(a) Dyed red and blue PGS-U films enable visualization of interfaces that close when pressed for 5 min at 55 °C. (b) Optical images of superficially damaged and healed PGS-U samples at 55 °C with time. Scale bar: 200 μm (adapted from ref (55)). (c) Healing efficiency of EMNa/EMA-30 at different cycle times. (d) Healing efficiency of EMNa/EMA-30 at different cycle times. (e) Stress–strain curves for both original and healed EMNa/EMA-30 (adapted from ref (58)).

Figure 4

Schematic showing switchable control of the stiffness characteristics of the functionalized CMC polymer scaffold. (a) Light-induced trans/cis isomerization of bis-AAP for cross-linking and partial separation of the polymer chains. (b) A hybrid CMC hydrogel that has been cooperatively cross-linked by β-CD/trans-AAP and nucleic acid. (c) Hydrogel matrix with dual-triggered (UV and CE) stiffness characteristics made up of β-CD/trans-AAP and K⁺ ion stabilized G-quadruplexes (adapted from ref (73)).

Figure 5

Diagrammatic representation of the gelatin-based colloidal inks used in extrusion-based 3D printing, their architecture at various length scales, and significant characteristics of printed scaffold facilitated by UV cross-linking (adapted from ref (86)).

Figure 6

(a) Schematic depicting the synthesis of PAAc hydrogels containing C16A units via stereolithography. (b) A printed robotic hand in temporary and permanent shapes. (c) and the shape-recovery process in water at 43 °C. (d) SEM pictures demonstrating the beginning of the healing process (adapted from ref (93)).

Figure 7

(A) Schematic presentation of fabrication of electroconductive hydrogel. (B) Shape fixity ratio (R_f) curve of G-shape hydrogel for various times of soaking in alkaline solution. (C) The G-hydrogel shape recovery ratios (R_r) curve an alkaline solution for various soaking times. (D) The healing efficiency of G-hydrogel curves for different healing times under NIR light (adapted from ref (98)).

Figure 8

Material design: (a) the self-healable thermoreversible cross-linked polymer composites with dynamic cross-linking network design; (b) compositional schematic of the multifunctional composites; and shape memory assisted self-healing performance demonstration in the self-healing process of (c) conductive device and (d) bionic skin fluorescence device (adapted from ref (111)).