This work investigates the performance accuracy of uniquely developed scanning electrochemical microscopy (SECM) devices and their errors in acceleration, which can negatively affect the accuracy of measurements. Scanning electrochemical microscopy (SECM) is a broader class of scanning probe microscopy (SPM) technique used to measure the local electrochemical behavior of liquid-solid, liquid-gas, and liquid-liquid interfaces. In this work, an image recognition technique is developed to provide the SECM operator with real-time information on the accuracy of the electrode movement. Using the MATLAB software environment and integrated image recognition algorithms, the methodology processes the digital microscope image, allowing accurate determination of the electrode position and possible errors.
The methodology’s effectiveness was evaluated by performing tests on fixed reference samples, whose precise dimensions and location allowed an accurate measurement of the errors of the SECM device. The results showed that the methodology allows an accurate estimation of the displacement errors and the creation of a map of the expected errors. This allows not only a preliminary evaluation of the accuracy of the SECM device, but also a dynamic monitoring of possible undetected errors during experiments.
The main conclusion is that this methodology can be applied to both one-off and commercialized SECM devices, improving their accuracy and smoothness. A major advantage of the methodology is its ease of use. It does not require modification of the SECM device, as it builds on existing components such as the digital microscope. The only possible modification required is the addition of a comparison scale to the sample holder, but experiments have shown that the technique works without it. In future studies, the system can be enhanced to improve the accuracy of detection of organic sample shapes.