Novel recalibration methodologies for ion‐selective electrode arrays in the multi‐ion interference scenario

Abstract

Because of the deterioration of sensitivity and selectivity of ion‐selective electrode (ISE) arrays after a long period of storage or measurement, the recalibration of ISE arrays is a major challenge, which significantly affects the practical application of ISE arrays. Although approaches using artificial neural networks (ANN) to solve the problem have been widely studied, it is impractical for end‐users to frequently remeasure dozens of samples to rebuild an ANN model for measuring of ISE array. In this study, a system of equations was developed to simulate the ISE array response for the scenario of multiple interfering ions. By fitting the coefficients for the system of equations using optimization algorithms, such as genetic algorithms (GA), the ISE array can be recalibrated with only a couple of selected samples. As a case study, a solid‐state ISE array for the detection of 4 exchangeable cations was applied. The deterioration of sensitivity and selectivity of the ISE array over time was investigated. The simplified methodology for calibrating this ISE array was applied and demonstrated in this study.