Publication | Open Access
A Soft, Adhesive Self‐Healing Naked‐Eye Strain/Stress Visualization Patch
20
Citations
39
References
2023
Year
EngineeringBiomimetic MaterialsSmart PolymerResponsive PolymersBiofabricationBioresponsive MaterialsBiomedical EngineeringSelf-healing SurfaceSoft MatterStrain/stress DistributionSelf-repairFlexible SensorHydrogelsSelf-healing MaterialMechanicsBiomechanicsBiomedical DevicesBiophysicsInnovative Responsive HydrogelCamouflage MechanismOptical SensorsBiopolymer GelBiomedical DiagnosticsMaterials CharacterizationWound HealingMedicineBiomaterialsMechanics Of Materials
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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