Multiplex Analysis of Fundamental Surface Water Quality Indicators by Multichannel Electrochemical Device Combined With MFCSC Model

Abstract

Rapid and accurate detection of water quality is essential for environmental monitoring and management. Among them, permanganate index (CODMn), nitrate–nitrogen (NO3−-N), dissolvable inorganic phosphorus (DIP), and ammonia nitrogen (AN) are four important water quality indicators. A portable multichannel electrochemical device (MCED) combined with a sensor array composed of gold nanoparticles (AuNPs), silver nanodendritic structures (AgNDs), and reduced graphene oxide (rGO)-modified screen-printed electrodes (SPEs) was applied for facile, rapid on-site inspection. The sensor array exhibits good complementarity in voltammetric measurements of water quality indicators and has cross-sensitivity in multiplex measurement. A multiple fully connected shared convolution (MFCSC) model was constructed to process the voltammetric data, extracting unique features to resolve the overlap in voltammetric data of complex solutions for the quantitative determination of target analytes. Accurate predictions were successfully achieved for the four parameters, CODMn, NO3−-N, DIP, and AN in the mixture, where CODMn, NO3−-N, and AN have high coefficients of determination ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${R} ^{{2}}$ </tex-math></inline-formula> ) and low mean absolute percentage errors (MAPE%). Using the migration ability of MFCSC, combined with MCED, it is further applied for real water sample testing, which proves the good prediction of the water quality indicators of real water samples in complex matrices. The results show that the sensing system developed in this work has wide application potential and can be used to rapidly analyze surface water quality and obtain water quality information in a wide range of water bodies for monitoring.