Strategies to combat the fouling and surface texture issues associated with fabric-based colorimetric sensors

Abstract

Colorimetric arrays are low-cost, portable options for numerous sensing applications and are bolstered by the possibility of using high-quality smartphone imaging for signal readouts. Despite advances in the use of colorimetric sensors in the biomedical, environmental, and food safety fields, reliable fabric-based colorimetric sensors for wearable applications have not yet been fully developed. There are two major issues that attenuate the sensitivity and selectivity of fabric-based wearable colorimetric sensors in comparison to their paper-based counterparts. First, wearable colorimetric sensors are subject to fouling by body oils and other biomolecules during wear. Second, fabric surfaces are highly rough and textured, which reduces the efficacy of portable imaging and complicates signal readout. In this work, a fabric-based colorimetric sensing platform is developed based on optimized chemistry and post-image processing. A colorimetric array on natural fabrics was created via sol-gel chemistry and encapsulated using photoinitiated chemical vapor deposition. This fabrication strategy yields sensors with robust color fastness, antifouling ability, fast colorimetric response, recoverability, and mechanical stability when it is exposed to a model gaseous analyte, ammonia. Moreover, it is found that the texture problem introduced by the fabric substrate can be mitigated by image pixel manipulation after the images are captured. The accuracy for classifying different pH levels by the fabric sensor array is improved after the image sharpening technique is applied. These successful demonstrations of both qualitative and quantitative analysis of vapor and aqueous solutions sensing illustrate the practical suitability of this fabric-based sensing platform, which is appealing to advanced wearable monitoring.