Correlated pitting stages of 304 stainless steel with recurrence quantification analysis of electrochemical noise

The clustered pitting corrosion process has been investigated by electrochemical noise measurement using two nominally identical Al–Mg microelectrodes in aerated 3.5 wt% NaCl solution (pH 3.5). Current transients associated with the metastable pitting were detected and the pits were examined by scanning electron microscopy (SEM) observation. The results show that two types of clustered pits can be characterized by current transients separately. Pit interaction is confirmed by one transient with multiple peaks. Considering the nonFaradic current and cathodic current of H2 evolution inside the pit, the average volume determined from an integrated charge associated with individual single peak current transient is lower than that of actual pits, while the single peak transient count is more than that from SEM observation. It thus implies that reactivation of one metastable pit occurs and the relevant millisecond transient demonstrates only a single peak associated with nanopit for each reactivation. The results from this work shed insight into the use of statistical analysis of current transients to forecast the corresponding pit morphology.

Characteristics of the random transients caused by clustered pitting corrosion for Al–Mg microelectrode

Guan

Cai

2019

Evaluation of the localized corrosion on Mg electrode surface by electrochemical noise technique

Naghizade

Hosseini

Shahidi

et al. 2020

The symmetrical and asymmetrical electrodes made of Mg were studied in 0.1-M NaCl electrolyte adjusted at pH 12. The statistical and wavelet methods were employed for analyzing the electrochemical current noise (ECN) signals. The asymmetric configuration was used for electrochemical detection of filiform corrosion on Mg electrode. The real time scale of the dominant transients of the asymmetric electrodes was detected on the basis of the maximum peak in the SDPS plots. The SDPS values of the real time scale crystals of the ECN signals resulting from asymmetrical electrodes increased with the increase in immersion time due to the onset of filiform corrosion.

Global sensitivity analysis of influence parameters in pitting corrosion behavior of 304 stainless steel using adaptive neuro‐fuzzy inference systems

Wang

Yang

et al. 2020

Pitting corrosion is simultaneously influenced by many parameters. However, conventional experimental methods do not offer information on the relative importance of each parameter to pitting corrosion. Herein, pitting corrosion of 304SS under multiple parameter influences was investigated by the global sensitivity analysis (GSA) based on adaptive neuro‐fuzzy inference system (ANFIS). It was applied for the first time in quantitatively analyzing the relative importance of each parameter to pitting corrosion. It was developed in two different systems, based on the experimental data and the published data, respectively. Both results show that ANFIS exhibits a highly accurate prediction result. The GSA based on ANFIS quantitatively analyzes the relative importance of the initiation of pitting corrosion of 304SS for each parameter, and based on the results of GSA, it can also be determined whether the parameter inhibits or promotes pitting corrosion. We believe this method could provide guidance for corrosion research.