2, Harvard University, Cambridge, Massachusetts, United States
3, Georgia Institute of Technology, Atlanta, Georgia, United States
The fast development of wearable sensors has been promoted by the broad needs for real-time monitoring the metabolism, bodily functions non-invasively and the air quality in the environment by aging populations, soldiers, working professionals, etc. Interests in many wearables electronic sensors, which started with high expectations, however have seen a decrease over time, due to the needs of frequent charging of batteries in practical usage. Wearable colorimetric sensors, using optical read-out signals under ambient light without any electronic components, become highly advantageous. However, creating conventional dye- or chemical-based colorimetric sensors with high sensitivity and selectivity usually requires complicated synthesis process. Here we report an adaptive colorimetric sensing platform based on a bulk structure of covalently bonded hydrogel thin film-substrate system. The dynamic coloration arises from the interference of reflected light on air-hydrogel and hydrogel-substrate interfaces, and can be flexibly tuned in a broad spectral range. External stimuli from the analytes can rapidly change the thickness of the hydrogel film, resulting in an instant color change. We have built theoretical models that capture the key chemo-mechano-optical process occurring in the dynamic materials, mainly the mechanics of the chemical-induced hydrogel volume phase change and the interference-based coloration governed by 2ndcosθ = mλ, showing good agreement with experimental results. The soft and high stretchable robust synthetic hydrogel materials can form a highly compliant contact to human epidermis and has good self-recovery capability, as an ideal candidate for soft matrices of wearable devices. Also, this colorimetric sensing platform allows for in situ quantitative analysis by naked eye or camera via analysis app, as a wireless wearable sensing component for the next-generation textile. Moreover, we have shown this customizabile adaptive platform can detect a large variety of analytes including cations for hydration and other physiologic metabolic state monitoring, Cu2+ for Wilson's disease prescreening, glucose for diabetes monitoring, and sulfur dioxide and nitrogen dioxide for air quality detecting. This sensing platform showed a high performance on the sensitivity and response time. The limit of detection for Cu2+ could reach as low as 10.0 pM with only 1-2 second. Such high performance is attributed by this unique chemo-mechano-optical signal transduction mechanism, which effectively amplifies the nm-scale hydrogel thickness change to a greater and more detectable optical spectrum change. This will lead to a broad platform of a new class of wearable sensors with superior performance at low cost.