Abstract

Solid contact ion-selective electrodes (SCISEs) offer many benefits over traditional liquid contact ion-selective electrodes. Their small size made them the default choice in many clinical analysis tools. Reproducibility of their production is crucial in achieving calibration-free sensors. Electrochemical impedance spectroscopy (EIS) is a versatile technique that can provide valuable information on many physico-chemical parameters of examined SCISEs and it can give results under 1 min. Discerning different phenomena that govern the EIS spectrum require the theoretical understanding of the processes (e.g., diffusion, heterogeneous kinetics etc.) that determine the time-dependent response of SCISEs. EIS simulations of SCISEs with Nernst-Planck-Poisson finite element method are applied to describe the experimental response of SCISEs. The numerical simulations are used to train a black-box supervised learning algorithm—a deep feedforward neural network—and a white-box symbolic regression algorithm to learn the underlying model of EIS spectra of SCISEs. The neural networks are used to significantly speed up the solution of the inverse problem of obtaining physico-chemical parameters from experimental data.

Highlights

  • To cite this article: Miklós Márton Kovács and Lajos Höfler 2022 J

  • Electrochemical impedance spectroscopy measurements with PPy films, ionophore free and ionophore containing electrodes were performed to obtain information about the charge transfer, diffusion and double layer charging processes in the electrodes

  • The low frequency quasi-linear waves were not significantly different between PPy film electrodes and SCISEs, indicating that the process generating the low frequency impedance is due to the electron diffusion and ion-to-electron transduction in the PPy film

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Summary

Introduction

To cite this article: Miklós Márton Kovács and Lajos Höfler 2022 J. Ion-selective electrodes (ISEs) can be found in many analytical applications, ranging from clinical diagnostics and process control to environmental analysis.[1,2,3,4] The development of solid contact ionselective electrodes (SCISEs)—where an ion-selective membrane (ISM) is directly attached to a solid substrate—was driven by the need for a mass-producible, small size ion sensor, which permit reproducible measurements in small sample sizes.[5,6,7] Conducting polymers are often introduced as a layer between the electrode substrate and the ISM. We have addressed the problem of directly assessing the underlying physico-chemical parameters by using a combined approach of

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