Electrospun Polyurethane Blends Exhibiting Shape Memory and Self‐Healing Properties

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.

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Publication Details

Journal
Journal of Polymer Science
Published
2025-03-08
DOI
https://doi.org/10.1002/pol.20241143
Citations
1
Primary Topic
Polymer composites and self-healing
Type
article
Field-Weighted Citation Impact
0.61

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article

Electrospun Polyurethane Blends Exhibiting Shape Memory and Self‐Healing Properties

Patrick T. Mather, Wenbin Kuang, Brian B. Schwartz
1 citations
Journal of Polymer Science
Polymer composites and self-healing
0.61
article

Electrospun Polyurethane Blends Exhibiting Shape Memory and Self‐Healing Properties

Patrick T. Mather, Wenbin Kuang, Brian B. Schwartz
article en
1 citations

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.

Journal of Polymer ScienceVol. 63(8)
Pennsylvania State University (US), Syracuse University (US)
National Science Foundation of Sri Lanka
Openalex Percentile: Top 39%
Polymer composites and self-healing
0.61
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Electrospun Polyurethane Blends Exhibiting Shape Memory and Self‐Healing Properties — Patrick T. Mather, Wenbin Kuang, et al. · Journal of Polymer Science (2025) | TGRS Research Map | TGRS