Work

Electrospun Polyurethane Blends Exhibiting Shape Memory and Self‐Healing Properties

Year: 2025

Type: article

Abstract: ABSTRACT The ability of shape memory polymeric materials to repair physical damage and restore original functionality is of great significance in self‐healing technologies, offering a broad application. In this study, we present a novel approach: electrospun shape memory‐assisted self‐healing (SMASH) polymer blends, which build upon prior research utilizing latent crosslinkable polyurethane (x‐PU). By homogeneously blending x‐PU with linear polyurethane (l‐PU) and electrospinning the solution, we produced a family of blends with varying compositions. These blends were characterized through thermal, mechanical, and microstructural analyses, and their self‐healing capabilities were evaluated using a series of damage types. Among the compositions, the 80:20 (w/w x‐PU:l‐PU) blend demonstrated superior healing performance, achieving an average healing efficiency (η) of 92.2% for puncture damage. The introduction of structural anisotropy during electrospinning further enhanced the healing efficiency, particularly for fibers oriented perpendicular to the damage direction. These findings underscore the importance of compositional tuning and structural optimization in enhancing SMASH performance. This work highlights a scalable and versatile platform for self‐healing materials, with promising implications for extending the lifespan and functionality of polymeric systems in practical applications.

Source: Journal of Polymer Science

DOI: 10.1002/pol.20241143

Authors: Wenbin Kuang, Brian Schwartz, Patrick T. Mather

Institutions: Syracuse University, Pennsylvania State University

Language: English

Topic: Polymer composites and self-healing

Subfield: Polymers and Plastics

Field: Materials Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,380

Funder: National Science Foundation of Sri Lanka