Studies on Pitting Corrosion of Al-Cu-Li Alloys Part II: Breakdown Potential and Pit Initiation

• Published in: Materials Vol. 12; no. 11; p. 1786
• Main Authors: Ghanbari, Elmira, Saatchi, Alireza, Lei, Xiaowei, Macdonald, Digby D
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 02.06.2019; MDPI
• Subjects: Aerospace industry; Al-Cu-Li alloys; Al-Li alloys; Alloys; Aluminum alloys; Aluminum base alloys; Barrier layers; Breakdown; Cations; Copper; Corrosion resistance; Damage accumulation; Electrochemical analysis; Grain boundaries; Independent variables; Intermetallic compounds; Investigations; Lithium; Metal fatigue; Optimization; passivity breakdown; Pitting (corrosion); point defect model; Point defects; Vacancies; Yield stress; Al-Cu-Li alloys; passivity breakdown; Al-Li alloys; point defect model
• ISSN: 1996-1944; 1996-1944
• DOI: 10.3390/ma12111786

Prediction of the accumulated pitting corrosion damage in aluminum-lithium (Al-Li) is of great importance due to the wide application of these alloys in the aerospace industry. The Point Defect Model (PDM) is arguably one of the most well-developed techniques for evaluating the electrochemical behavior of passive metals. In this paper, the passivity breakdown and pitting corrosion performance of AA 2098-T851 was investigated using the PDM with the potentiodynamic polarization (PDP) technique in NaCl solutions at different scan rates, Cl concentrations and pH. Both the PDM predictions and experiments reveal linear relationships between the critical breakdown potential ( ) of the alloy and various independent variables, such as aCl- and pH. Optimization of the PDM of the near-normally distributed as measured in at least 20 replicate experiments under each set of conditions, allowing for the estimation of some of the critical parameters on barrier layer generation and dissolution, such as the critical areal concentration of condensed cation vacancies ( ) at the metal/barrier layer interface and the mean diffusivity of the cation vacancy in the barrier layer ( ). With these values obtained-using PDM optimization-in one set of conditions, the E distribution can be predicted for any other set of conditions (combinations of aCl-, pH and T). The PDM predictions and experimental observations in this work are in close agreement.