Intelligent laser-induced graphene sensor for multiplex probing catechol isomers  

作　　者：Tian Cao Xuyin Ding Qiwen Peng Min Zhang Guoyue Shi 

机构地区：[1]School of Chemistry and Molecular Engineering,Shanghai Key Laboratory for Urban Ecological Processes and Eco-Restoration,East China Normal University,Shanghai 200241,China

出　　处：《Chinese Chemical Letters》2024年第7期227-234,共8页中国化学快报（英文版）

基　　金：supported by the National Natural Science Foundation of China(Nos.22274053 and 22274051);the Shanghai Municipal Science and Technology Major Project(“Beyond Limits Manufacture”)。

摘　　要：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,0.079μmol/L;HQ,0.093μmol/L;RC,1.18μmol/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.

关 键 词：Laser-induced graphene Phenolic pollutants Electrochemical detection Artificial neural network 

分 类 号：O657.1[理学—分析化学] X830[理学—化学]