Intelligent laser-induced graphene sensor for multiplex probing catechol isomers

Abstract

Herein, we unveil the intelligent detection of multiple catechol isomers in complex environments utilizing both laser-induced graphene (LIG) and artificial neural network (ANN). The large scale-up manufacturing of LIG-based sensors (LIGS) with three-electrode configuration on polyimide (PI) is achieved by direct laser-writing and screen-printing technologies. Our LIGS shows excellent electrochemical performance toward catechol isomers, i.e., hydroquinone (1,4-dihydroxybenzene, HQ), catechol (1,2-dihydroxybenzene, CT), and resorcinol (1,3-dihydroxybenzene, RC), with a low limit of detection (LOD) (CC, 0.079 µmol/L; HQ, 0.093 µmol/L; RC, 1.18 µmol/L). Moreover, the ANN model is developed for machine-intelligent to predict concentrations of catechol isomers under an interfering environment via a single LIGS. Using six unique parameters extracted from the differential pulse voltammetry (DPV) response, the machine learning-based regression provides a coefficient of correlation with 0.998 and is able to correctly predict the total and individual concentrations in complex river samples. Hence, this work provides a guide for the preparation and application of LIGS via facile and cost-efficient mass production and the development of an intelligent sensing platform based on the ANN model.