Characteristics of the random transients caused by clustered pitting corrosion for Al–Mg microelectrode
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 scan...
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Veröffentlicht in: | Materials and corrosion 2020-01, Vol.71 (1), p.86-92 |
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Sprache: | eng |
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Zusammenfassung: | 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.
The clustered pitting corrosion process has been investigated by electrochemical noise measurement using two nominally identical A–Mg microelectrodes in aerated 3.5 wt% NaCl solution (pH 3.5). Two types of clustered pits can be characterized by current transients separately. The results from this work shed insight into the use of statistical analysis of current transients to forecast the corresponding pit morphology. |
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ISSN: | 0947-5117 1521-4176 |
DOI: | 10.1002/maco.201911048 |