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.
Bibliographical noteFunding Information:
This study was supported in part by a National Research Foundation of Korea (NRF) grant funded by the Korean government ( MSIT ) ( 2015R1A5A1037668 ), the ITRC program supported by IITP ( IITP-2020-2020-0-01461 ), Creative Materials Discovery Program through the National Research Foundation ( 2019M3D1A1078941 ), Technology Innovation Program ( 10077599 ) funded by the Ministry of Trade, Industry & Energy, the KRIBB Research Initiative Program [ KGM9952011 ], and a National Research Foundation of Korea (NRF) grant funded by the Korean government ( MSIT ) ( NRF-2020R1C1C1010044 ) ( NRF-2019R1A6A1A11051471 ).
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All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)
- Process Chemistry and Technology