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

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. •Synthesizing of 30 different fluorescent probes containing pH responding units based on the indolizine core skeleton.•Resulting compounds respond to pH with different photophysical property changes.•Exposure of the fluorescent compounds array with different pH generated distinct fluorescent pattern changes.•Machine learning algorithm allows for fluorescent-image based high-precision pH classification in broad pH ranges.