Interpretation of stochastic electrochemical data

anzsrc-for: 40 Engineering Physical chemistry 34 Chemical Sciences 3401 Analytical Chemistry anzsrc-for: 3406 Physical chemistry Nanotechnology Bioengineering anzsrc-for: 3401 Analytical Chemistry anzsrc-for: 4018 Nanotechnology Analytical chemistry anzsrc-for: 34 Chemical Sciences 40 Engineering 620
DOI: 10.1016/j.coelec.2024.101505 Publication Date: 2024-04-22T09:37:00Z
ABSTRACT
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 electrochemical processes are stochastic and discrete in nature. Stochastic measurement of a single entity probes the charge transfer from a few or even one electroactive species. In corrosion, the stochastic measurements capture either the average amplitude/frequency of many events taking place spontaneously or probe discrete transients, signifying localized dissolution. The measurement principles vary in corrosion, single-entity, and electrophysiology, yet the main quantifiable values are commonly the frequency and amplitude of events. This perspective delves into the methodologies for the analysis and deconvolution of stochastic signals in electrochemistry. Ranging from visual assessment of transients to time/frequency analyses of the data and state-of-the-art machine learning, these methodologies mainly aim at identifying patterns, singular events, and rates of electrochemical processes from stochastic signals.
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