Image-based framework quantifies strain through hue shifts in colloidal photonic crystals, enhancing sensing capabilities.
Mechanochromic materials, particularly colloidal photonic crystals (CPCs) embedded in soft stretchable films, hold significant potential in applications requiring precise and real‐time strain monitoring. These materials exhibit strain‐induced color changes arising from alterations in lattice periodicity, yet conventional quantification methods like spectroscopy are often costly, complex, and challenging to scale. Here, an image‐based quantification framework is presented that evaluates mechanochromic behavior with high precision by tracking hue shifts in optical images. CPC films are prepared from core‐shell nanoparticles with acrylate shells of different glass transition temperatures, allowing systematic control of elastic modulus and composition‐dependent chromatic responses. RGB image data are converted into the hue‐saturation‐value (HSV) color space, where the hue component serves as a robust optical readout of lattice compression, directly reflecting nanoscale spacing changes. The hue‐strain relationship is reproducible, material‐dependent, and consistent under multi‐axial loading, thereby linking strain‐induced color shifts to intrinsic material properties. Statistical filtering together with consistency across different brightness levels further ensures stability under variable imaging conditions. This framework establishes hue as a precise and scalable metric for mechanochromic quantification, broadening opportunities for cost‐effective strain sensing in wearable devices, soft robotics, and structural diagnostics.
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Lee et al. (2025) studied this question.
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