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Localized crack-enabled mechanical switching through micro-nano interfacial control of fracture pathways

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Soft Sci 2026;6:[Accepted].
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Abstract

Cracks have been widely employed as functional elements in stretchable sensors exhibiting continuous resistance modulation under mechanical strain. Although the opening of an individual crack inherently induces a nonlinear, sharp increase in resistance, most strategies rely on dense multi-crack networks, in which statistical reconfiguration of percolation pathways averages the nonlinear behavior of individual cracks. Here, we present a strategy that transforms a multi-crack percolation system into a deterministic architecture with a small number of confined cracks, thereby enabling deterministic mechanical switching characterized by discrete on/off switching at a critical strain. To do this, a U-shaped notch microchannel and nanostructures are introduced on the top surface of soft substrates, which can prevent random crack initiation and suppress competing interfacial delamination of thin conducting films during repeated mechanical deformation of the substrate by taking advantage of mechanical interlocking-enhanced adhesion. This multiscale interface engineering selectively programs the dominant fracture pathway toward notch-confined crack opening and closing. The resulting device exhibits reproducible off-state and on-state switching during tensile loading and release, while maintaining stable baseline resistance over 210 cycles and showing low hysteresis. These results demonstrate that statistically governed dense crack-based devices can be redefined as deformation-driven mechanical switching, providing a fracture-pathway design principle for functional expansion of deformable electronics.

Keywords

Localized cracks, mechanical switching, micro-nano interfaces, fracture pathways

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Kim K, Park SJ, Oh S, Moon MW, Cho H. Localized crack-enabled mechanical switching through micro-nano interfacial control of fracture pathways. Soft Sci 2026;6:[Accept]. http://dx.doi.org/10.20517/ss.2026.45

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© The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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Soft Science
ISSN 2769-5441 (Online)

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