AI One-Click-Processing-Assisted Ratiometric RTP Paper-Based Sensor Array for the Rapid Discrimination and Detection of Mixtures of Oxolinic Acid and Flumequine
Henggang Wang, Beibei Zhang, Yaole Qin, Yue Shi, Yulu Wang, Shikao Shi, Zhenguang Wang
Abstract
The rapid and precise detection and discrimination of structurally analogous analytes remain highly desirable yet challenging. In this work, a ratiometric room-temperature phosphorescence (RTP) sensor array integrated with phosphorescence amplification and artificial intelligence (AI)-driven data processing was developed for the rapid discrimination and quantification of the mixture of oxolinic acid (OLA) and flumequine (FMQ). The sensor array leverages paper substrates to amplify the blue RTP signals of the OLA and FMQ and the green RTP signals of 1,5-naphthalenedisulfonic acid through a confinement and thermal annealing mechanism. By coupling these amplified signals with automated AI processing and pattern recognition, quantification, and discrimination, the mixture of OLA and FMQ was realized, as low as 1.96 μM, within 10 min. In addition, the entire process could be executed by using a smartphone-based camera, eliminating the need for specialized instrumentation. The sensor array also demonstrated exceptional performance in practical samples, including environmental and food matrices, and paved the way for innovative sensor design.