Evaluation of the formation and protectiveness of a lithium-based conversion layer using electrochemical noise

Journal article (2022)

Authors

Z. Li Team Arjan Mol - Mechanical, Maritime and Materials Engineering
A.M. Homborg Netherlands Defence Academy, Team Arjan Mol - Mechanical, Maritime and Materials Engineering
Y. Gonzalez Garcia Team Yaiza Gonzalez Garcia - Mechanical, Maritime and Materials Engineering
A. Kosari Team Yaiza Gonzalez Garcia - Mechanical, Maritime and Materials Engineering
Peter Visser Akzo Nobel
J.M.C. Mol Team Arjan Mol - Mechanical, Maritime and Materials Engineering
Research Group
Team Arjan Mol (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 Z. Li, A.M. Homborg, Y. Gonzalez Garcia, A. Kosari, Peter Visser, J.M.C. Mol
DOI: https://doi.org/10.1016/j.electacta.2022.140733
More Info
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Published Date

2022

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Materials Science and Engineering

Research Group

Team Arjan Mol

Abstract

The formation process of a lithium-based conversion layer on AA2024-T3 and its corrosion protective behavior are studied using electrochemical noise (EN). Wavelet transform, as well as noise resistance analysis, have been employed to interpret the EN data. The EN data confirmed five different stages during the conversion layer growth, accompanied by anodic dissolution, increasing corrosion protection of the conversion layer, and adsorption, growth and desorption of hydrogen bubbles simultaneously. The detachment of hydrogen bubbles, localized and uniform corrosion generate different features in the EN signals with energy maxima in high, intermediate and low frequency bands, respectively. In addition, EN results show that the lithium-based conversion layer still provides efficient protection after re-immersion in a corrosive environment, even though localized damage occurs. Moreover, the EN data corresponds well with the morphological layer formation and breakdown observed with microscopy techniques. The results demonstrate that EN is a powerful tool to provide continuous time- and frequency-resolved information about inhibition efficiency.