A Soft, Adhesive Self-Healing Naked-Eye Strain/Stress Visualization Patch
© 2023 Wiley-VCH GmbH.
| Publié dans: | Advanced materials (Deerfield Beach, Fla.). - 1998. - 36(2024), 9 vom: 01. März, Seite e2307582 |
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| Auteur principal: | |
| Autres auteurs: | , , , , , , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2024
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| Accès à la collection: | Advanced materials (Deerfield Beach, Fla.) |
| Sujets: | Journal Article bio-inspired hydrogel mechano-iridophore naked-eye self-healing material soft mechanical sensor strain/stress visualization patch |
| Résumé: | © 2023 Wiley-VCH GmbH. Learning about the strain/stress distribution in a material is essential to achieve its mechanical stability and proper functionality. Conventional techniques such as universal testing machines only apply to static samples with standardized geometry in laboratory environment. Soft mechanical sensors based on stretchable conductors, carbon-filled composites, or conductive gels possess better adaptability, but still face challenges from complicated fabrication process, dependence on extra readout device, and limited strain/stress mapping ability. Inspired by the camouflage mechanism of cuttlefish and chameleons, here an innovative responsive hydrogel containing light-scattering "mechano-iridophores" is developed. Force induced reversible phase separation manipulates the dynamic generation of mechano-iridophores, serving as optical indicators of local deformation. Patch-shaped mechanical sensors made from the responsive hydrogel feature fast response time (<0.4 s), high spatial resolution (≈100 µm), and wide dynamic ranges (e.g., 10-150% strain). The intrinsic adhesiveness and self-healing material capability of sensing patches also ensure their excellent applicability and robustness. This combination of chemical and optical properties allows strain/stress distributions in target samples to be directly identified by naked eyes or smartphone apps, which is not yet achieved. The great advantages above are ideal for developing the next-generation mechanical sensors toward material studies, damage diagnosis, risk prediction, and smart devices |
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| Description: | Date Revised 02.03.2024 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1521-4095 |
| DOI: | 10.1002/adma.202307582 |