Fluorescent sensor array for high-precision pH classification with machine learning-supported mobile devices

Abstract

There is growing research interest from many scientific, healthcare, and industrial applications toward the development of high-precision optical pH sensors that cover a broad pH range. Despite enthusiastic endeavors, however, it remains challenging to develop cost-effective, high-precision, and broadband working paper-strip-type optical pH measurement systems, particularly for on-site or in-the-field pH sensing applications. We develop a fluorescent array based on a KIz system for accurate pH level classification. Based on the indolizine fluorescent core skeleton, a library of 30 different pH-responsive fluorescent probes is rationally designed and efficiently synthesized. Spotting the compounds in a checkered pattern (5 × 6) allows for the development of a disposable compound array on wax-printed cellulose paper. Compounds sharing a single chemical core skeleton result in the interrogation of all the components of a system with a single excitation light, resulting in a simple system design for pH classification. Furthermore, we design a 3D-printed enclosure to capture the fluorescence pattern changes of the array by using an intelligent, smartphone-based, handheld pH detection system. Specifically, by exploiting a random forest-based machine learning algorithm on a smartphone, we can effectively analyze the fluorescence pattern changes. Our results suggest that our proposed system can classify pH levels in fine-grain (0.2 pH) units.