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Rapid and Accurate Data Processing in Nano-Impact Electrochemistry for Silver Nanoparticle Oxidation

Robert Stan

Nano-Impact Electrochemistry (NIE) has gained extensive interest in recent years as a novel electroanalytical technique for the investigation and characterisation of single nanoparticles in solution. The proper analysis of the vast volume of experimental data is critical to improve the method's dependability. Unfortunately, the most generally utilised data analysis methods, which are mostly dependent on manual processing, are frequently time-consuming and subjective. In this paper, we offer a spike detection technique for automatically processing data from NIE experiments involving direct oxidation of silver nanoparticles (AgNPs), including baseline extraction, spike identification, and spike area integration. The obtained size distribution of AgNPs agrees extremely well with that from Transmission Electron Microscopy (TEM), indicating that the current approach is promising for automated NIE data processing with great efficiency and accuracy.