Tough, Self-Healing, Recyclable Bottlebrush Polyurethane Elastomer with a Skin-like Strain-Adaptive-Strengthening Property

Bottlebrush polymers consisting of linear polymer backbone and polymeric side-chains are of significant interest for an extensive variety of potential applications that include drug delivery, omniphobic surface, and amphiphilic emulsion surfactants. These polymers are challenging to prepare in large quantities for practical use. Therefore, it is necessary to provide a facile synthetic route for bottlebrush polymers with commercially available products. Here, we describe a simple approach to converting widely used linear poly(tetramethylene ether glycol) (PTMG) polyurethanes into a bottlebrush elastomer with extraordinary self-healing and recycling properties. Random and block distributed glyceryl monostearate (GM) brushes result in distinguishing mechanical and surface properties of the bottlebrush elastomer. The exchangeable character of aromatic disulfides facilitates the self-healing processes by temperature-, stress-, or solvent-induced arrangements, enabling a deformed sample to recover its original appearance and mechanical properties after applications of the self-healing and recycling process. The material manifested a self-healing recovering efficiency of 86% of tensile strength, above 90% of elongation at break, and a complete recovery of tensile strength after the reforming process. Other dynamic thermomechanical and surface properties, such as rheological analysis, DMA, DSC, and contact angles were investigated and compared with those of conventional PTMG polyurethanes. Furthermore, inspired by biological tissues and real human skin, a stain-adaptive-strengthening effect in tensile measurements was observed with highly correlated polynomial fittings with R2 = 0.9996. This simple and easy approach to preparing bottlebrush polyurethane elastomer with skin-like, self-healing, and recycling properties offers unique opportunities in the field of advanced materials, such as surgical skin dressing, intelligent sensors, human–machine interaction, and soft robotics.