Interpretation of stochastic electrochemical data

• DOI: 10.1016/j.coelec.2024.101505
• Publication Date: 2024-04-22T09:37:00Z
• Authors: Sina S. Jamali; Yanfang Wu; Axel M. Homborg; Serge G. Lemay; J. Justin Gooding
• Keywords: Stochastic modelling

Stochastic electrochemical measurement has come of age as a powerful analytical tool in corrosion science, electrophysiology, and single-entity electrochemistry. It relies on the fundamental trait that most processes are stochastic discrete nature. single entity probes charge transfer from few or even one electroactive species. In corrosion, measurements capture either average amplitude/frequency many events taking place spontaneously probe transients, signifying localized dissolution. The principles vary single-entity, yet main quantifiable values commonly frequency amplitude events. This perspective delves into methodologies for analysis deconvolution signals Ranging visual assessment transients to time/frequency analyses data state-of-the-art machine learning, these mainly aim at identifying patterns, singular events, rates signals.