Multi‐Parametric Decision System for Analytical Performance Assessment of Electrochemical (Bio)Sensors

Abstract Miniaturized three‐electrode electrochemical sensors (MES) are widely used in the advancement of innovative technologies for remote sensing applications. MESs consist of conductive electrodes that are applied onto an inert solid substrate using various techniques, such as photolithography, electroplating, and screen printing. Typical MES systems comprise working (WE) and counter (CE) electrodes based on gold (Au), paired with a reference electrode (RE) based on silver (Ag). This configuration is commonly selected due to Au's high conductivity, low resistance, and compatibility with robust organothiol chemistries, especially for the WE. Moreover, Ag is often preferred for REs owing to its low toxicity, stability, and high conductivity. Nevertheless, in uncontrolled environments outside of cleanrooms, both Au and Ag surfaces are prone to atmospheric contamination, resulting in significant sensor variability and compromised analytical performance. Therefore, it is crucial to integrate a pre‐processing stage into the sensor manufacturing process to guarantee the quality and cleanliness of MES electrode surfaces for sensor functionalization and precise electrochemical measurements. Considering the potential negative effects of methods tailored for a specific electrode material on another material, this study extensively investigates 18 different treatment methods for MESs incorporating Au CEs and WEs, along with Ag REs. Employing a multi‐parametric analysis, this study aims to identify the most effective treatment for a variety of electrode materials, thereby improving analytical accuracy and reproducibility for subsequent MES (bio)sensor applications.