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Article

Modeling and Analysis of Corrosion of Aluminium Alloy 6060 Using Electrochemical Impedance Spectroscopy (EIS)

by
Aikaterini Baxevani
1,
Eleni Lamprou
1,
Azarias Mavropoulos
1,*,
Fani Stergioudi
1,
Nikolaos Michailidis
1 and
Ioannis Tsoulfaidis
2
1
Physical Metallurgy Laboratory, School of Mechanical Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece
2
Alumil S.A., Kilkis Intustrial Area, GR-61100 Kilkis, Greece
*
Author to whom correspondence should be addressed.
Alloys 2025, 4(3), 17; https://doi.org/10.3390/alloys4030017
Submission received: 15 July 2025 / Revised: 5 August 2025 / Accepted: 26 August 2025 / Published: 29 August 2025
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Abstract

Aluminum is widely used in many industries like automotive, aerospace and construction because of its low weight, good mechanical strength and resistance to corrosion. This resistance comes mainly from a passive oxide layer that forms on its surface. However, when aluminum is exposed to harsh environments, especially those containing chloride ions in marine environments, this layer can break down and lead to localized corrosion, such as pitting. This study examined aluminum profiles at different processing stages, including homogenization and aging, anodizing and pre-anodizing followed by painting. Corrosion behavior of samples was studied using two electrochemical methods. Potentiodynamic polarization was used to measure corrosion rate and current density, while Electrochemical Impedance Spectroscopy (EIS) helped to understand the behavior of protective layers and corrosion progression. Tests were carried out in a 3.5% NaCl solution at room temperature. EIS results were analyzed using equivalent circuit models to better understand electrochemical processes. Overall, this study shows how surface treatment affects corrosion resistance and highlights advantages of EIS in studying corrosion behavior in a more reliable and repeatable way.

1. Introduction

Aluminum and its alloys are widely used across industries such as aerospace, automotive, and construction, due to their favorable properties, including low density, high mechanical strength, excellent thermal and electrical conductivity and ease of manufacturing and recycling [1]. In architectural applications and sectors like automotive, aerospace and construction aluminum profiles combine attractive aesthetics, mechanical robustness and corrosion resistance [2]. However, they can be susceptible to certain types of localized corrosion, including filiform, pitting, crevice and intergranular corrosion. To address this issue, various accelerated laboratory corrosion tests have been conducted; however, they do not provide a solution to predicting the corrosion tendency combined with the selected surface treatment system [3]. The increasing use of recycled aluminum in architectural constructions is best practice because it significantly reduces energy costs, carbon emissions, and it retains its original properties, such as strength and corrosion resistance, and is infinitely recyclable without degradation. On the other hand, it can create potential problems in the corrosion resistance of the parent material. A poorly executed homogenization process in secondary aluminum billet production can significantly compromise corrosion resistance, leading to performance issues in downstream applications.
More specifically, the role of intermetallic compounds, the uneven grain structure and the chemical segregation that are created during casting and continue to exist during the thermomechanical processes that follow, are under investigation as they may constitute preferential ascending routes leading to localized corrosion and a reduction in the corrosion resistance of structures [4].
The production of aluminum profiles is a process that requires precision and expertise at every stage, from the selection of the appropriate alloy to the final surface treatment. Quality of the final product depends on the correct implementation of each step and understanding the scientific principles governing production is crucial to optimizing the process and achieving high-quality profiles.
Choice of aluminum alloy is the first and fundamental step. Each alloy has unique properties that make it suitable for specific applications. The 6000 (Al-Mg-Si) series, for example, offers excellent corrosion resistance and extrudability, making it ideal for automotive and architectural construction applications [2]. Other alloys, such as the 7000 (Al-Zn) series, offer high strength, suitable for aerospace applications [5,6,7,8,9,10]. The choice of alloy directly affects the mechanical properties, corrosion resistance and processability of the final product.
A major benefit of aluminum is its inherent corrosion resistance, which is due to the spontaneous formation of a thin and stable oxide layer that protects the surface from further degradation. Anodizing is a widely used electrochemical process that creates a protective, decorative, and durable oxide layer on the surface of the aluminum profiles. During anodizing, the aluminum part serves as the anode in an electrolytic cell, forming a controlled, nanoscale porous oxide film. Properties of the film can be adjusted by critical parameters control such as voltage, current density, electrolyte concentration, temperature, and anodizing time [11,12]. Among various anodizing techniques, sulfuric acid anodizing is preferred for decorative finishes and moderate corrosion protection. The 6xxx series alloys, particularly 6060, are well-suited to this process due to their favorable anodizing response, good formability and balanced mechanical properties [13].
Despite surface treatments, aluminum in aggressive conditions, especially in seawater, can still lose its protective oxide layer, causing localized corrosion such as pitting. This can quickly damage the structural integrity [14,15,16,17,18]. To better understand aluminum corrosion mechanisms and improve durability, numerous experimental methods have been developed. Traditional techniques such as weight loss measurement provide simple estimates of material degradation but are time-consuming and offer limited insight into corrosion mechanisms. Hydrogen evolution methods quantify corrosion rates based on gas generation but can be influenced by external factors such as temperature and pressure, limiting reliability [19,20,21]. Corrosion tests like acetic acid salt spray (AASS, ISO 9227) [22] and Filiform corrosion test (FFC, ISO 4623-2) [23] are commonly used for assessing the corrosion resistance of decorative coatings but often fail to replicate complex real-world conditions, resulting in variable and sometimes non-representative results [24,25,26,27,28]. Electrochemical Noise Analysis can monitor spontaneous fluctuations related to corrosion but presents challenges in data interpretation and usually requires supplementary methods [29,30,31,32,33].
To overcome these problems, Electrochemical Impedance Spectroscopy (EIS) is used as a strong, non-damaging tool that can carefully and repeatedly monitor corrosion in real time. EIS enables the detection of minor defects before they become visible under electron microscopy and allows continuous monitoring of the same samples. By measuring impedance over a range of frequencies, EIS provides detailed information about charge transfer, film stability, diffusion and double-layer behavior [34,35,36,37,38]. Also, modeling corrosion with equivalent electrical circuits from EIS data helps explain corrosion processes, evaluate coating performance, and monitor changes over time without damaging the sample. This study investigates the corrosion behavior of EN AW 6060 aluminum alloy samples subjected to various surface treatments. Electrochemical corrosion techniques, including potentiodynamic polarization and EIS were employed, while scanning electron microscopy (SEM) was used to analyze the morphology of the treated surfaces. This work uses these electrochemical methods to provide rapid, non-destructive and repeatable evaluation of corrosion behavior and coating performance. Unlike many other studies that examine these techniques separately, this work combines potentiodynamic polarization, EIS with equivalent circuit modeling and SEM analyses to provide a more comprehensive evaluation of corrosion behavior. Additionally, in contrast to studies based on prolonged natural exposure, this work systematically investigates all key industrial processing stages including homogenization, aging, anodizing, pre-anodizing and painting under controlled laboratory conditions [39,40,41,42,43,44]. Such an approach facilitates a comprehensive understanding of the material’s corrosion resistance throughout the entire manufacturing process. The methodology relies on accessible tools, making it feasible for industrial quality control laboratories that may lack access to advanced or costly equipment required for techniques, which are used in other studies [45]. Furthermore, this practical methodology supports faster decision-making and improved corrosion management in real-world manufacturing environments.

2. Materials and Methods

2.1. Materials and Coating Production

In this study, four EN AW 6060 aluminum alloy profiles samples were examined. One untreated sample was used as a reference after it was homogenized and aged (initial), while the other three were subjected to different surface treatments, such as clear anodizing, black anodizing and one pre-anodized plus painted sample, to assess their corrosion resistance and aesthetic properties. For clear and the black anodized sample, the process used was sulfuric acid anodizing according to Qualanod [46] and DIN 17611 [47] specifications. The production steps are alkaline degreasing, alkaline etching, desmutting, anodizing, electro coloring and cold sealing. Careful control of these parameters ensures a uniform and durable oxide layer suitable for a variety of applications. This process resulted in an approximate thickness of 17 μm oxide layer, composed of hexagonal columnar cells with nanometric pores [48,49,50].
The third sample was anodic pretreated and coated with architectural polyester powder. Pre-anodizing is a process that forms a protective oxide layer of 5–8 μm on the profiles before painting. This treatment improves corrosion resistance of the aluminum profiles. This combined surface treatment sample was produced according to Qualicoat specifications. Overall, these three treatments, like clear anodizing, black anodizing, and pre-anodizing combined with painting, provide a complete way to compare different surface modification methods on EN AW 6060 aluminum alloys.

2.2. Experimental Procedure

Corrosion characterization of aluminum samples was conducted using potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). Potentiodynamic polarization was used to determine the corrosion potential (Ecorr), corrosion current density (Icorr) and corrosion rate for each sample, using a sweep rate of 2 mV/s. Exposed sample area was carefully defined as 1 cm2 to ensure accurate measurement of current densities. EIS measurements were performed to investigate the electrochemical behavior over a frequency range, typically from 100 kHz to 100 mHz. Impedance data were analyzed using electrical circuit models to understand how different layers, like oxide films and coatings, contribute to corrosion protection and to quantify parameters such as pore resistance, coating capacitance and diffusion effects.
All electrochemical tests were carried out in 3.5 wt.% NaCl aqueous solution at room temperature (25 °C) using a Gamry potentiostat/galvanostat system. A standard three-electrode setup was used, with the aluminum sample as the working electrode, a platinum rod as the counter electrode and a saturated calomel electrode (SCE) as the reference. The microstructure of the aluminum matrix as well as the coatings formed through different surface treatments was analyzed using a Phenom ProX desktop SEM (Thermo Fisher Scientific). Before SEM analysis, the samples were cut using a low-speed diamond saw to avoid damage. The specimens were then mounted in epoxy resin, followed by grinding with SiC papers of progressively finer grit sizes. Polishing was performed using alumina suspension to achieve a smooth, reflective surface. To reveal the microstructural features, the samples were chemically etched using Keller’s reagent. Figure 1a shows the aluminum alloy samples, Figure 1b the electrochemical cell and Figure 1c the experimental setup for electrochemical measurements.

3. Results and Discussion

3.1. Surface Morphology

Figure 2a presents SEM (SED) micrographs of the aluminum matrix, clearly revealing grain boundaries and possible inclusions. These microstructural features reflect the complex internal structure of the alloy. The prominent lines denote the interfaces between individual grains, while dispersed particles may correspond to secondary phases or impurities. In 6xxx series aluminum alloys, magnesium and silicon are the primary alloying elements, with iron, manganese and chromium typically present as trace elements or impurities. During solidification and subsequent processing, these elements form intermetallic compounds that play a critical role in determining the alloy’s mechanical performance and corrosion behavior. In Figure 2a, Mg2Si precipitates are apparent within the aluminum matrix. These precipitates are crucial for strengthening the alloy through a process called precipitation hardening [51].
Figure 2b,c depicts SEM (BSD) images of the anodized layers, which exhibit a fibrous morphology that develops along the growth direction of the layer. The fibers within the oxide are aligned parallel to one another, forming gaps between them. The porosity of these oxide layers plays a crucial role in defining their function. The type, size and shape of the pores depend on factors such as the substrate’s structure, the etching conditions of the aluminum alloy surface, the electrolyte type and the parameters of the anodizing process [52]. The black anodized layer is thicker (~18 μm) than the clear one (~17 μm), likely due to different anodizing parameters. The anodized layer is well-adhered to the substrate, with no evidence of interfacial defects or delamination. Figure 2d shows an SEM (BSD) image of the sample that was pre-anodized and painted, showing a well-formed multilayer structure. However, in the magnified surface image of the anodized samples, some voids and discontinuities are observed within the anodic oxide layer. These features are indicative of poor sealing, which can reduce the long-term effectiveness of anodizing by allowing chloride ions to penetrate through the porous structure. Despite this limitation, the presence of the additional painting layer significantly minimizes this risk. The painting acts as a supplementary barrier, filling surface defects and sealing the underlying oxide layer, thereby enhancing the overall corrosion resistance of the system.
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Figure 2. (a) Microstructure of the matrix of Al alloy sample, cross-section of (b) clear anodized, (c) black anodized and (d) pre-anodized and painted Al samples.
Figure 2. (a) Microstructure of the matrix of Al alloy sample, cross-section of (b) clear anodized, (c) black anodized and (d) pre-anodized and painted Al samples.
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3.2. Electrochemical Characterization

Figure 3 shows the potentiodynamic polarization curves of the aluminum samples to study the influence of different surface treatments on corrosion behavior in 3.5% NaCl solution at 25 °C. The anodized samples show significantly lower current density values compared to the initial (uncoated) samples, in which a clear tendency for pitting corrosion is observed. The pre-anodized and painted sample exhibits the lowest corrosion current density among all tested samples. This confirms the synergistic protective effect of combining anodization and electrostatic coating, creating a dual barrier against corrosion. A tendency for pitting corrosion, indicated by the pitting potential (Epit), was also observed in both clear and black anodized samples. This means that although anodizing improves general corrosion resistance, it does not fully protect against localized corrosion. Small defects or pores in the oxide layer may allow pitting to start under certain conditions. Additionally, metastable pits, reflected as small current fluctuations, typically occur at voltages approaching the pitting potential (Epit) [53]. The corrosion resistance of aluminum and its alloys in water-based environments mainly comes from the rapid formation of a protective oxide layer on their surface. However, aggressive ions such as chlorides can locally damage this layer, leading to a severe form of localized corrosion called pitting. Chloride ions typically gather at weak spots in the oxide film, penetrate it, and eventually initiate pit formation. Pitting corrosion often occurs when cathodic intermetallic particles fully dissolve due to a local increase in pH. This rise in pH degrades the oxide film around the particles, weakens the connection between the particles and the aluminum, and makes the surrounding area more prone to further corrosion [54].
In all cases studied, the anodic polarization curves show an initial region (Region I) where the aluminum surface undergoes active corrosion, with the current increasing rapidly as the potential rises. As the potential continues to increase, this behavior transitions into a second region (Region II), where the current becomes more stable and less dependent on voltage. This region suggests the formation of a thin or unstable surface layer that slightly slows down the corrosion process but does not provide full protection. For this reason, Region II is often described as pseudo-passive.
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Figure 3. Potentiodynamic polarization curves of Al alloy samples with different surface treatments in sodium chloride solution. The potential is measured against the Saturated Calomel Electrode (SCE), and corrosion rates are expressed in millimeters per year (mmpy).
Figure 3. Potentiodynamic polarization curves of Al alloy samples with different surface treatments in sodium chloride solution. The potential is measured against the Saturated Calomel Electrode (SCE), and corrosion rates are expressed in millimeters per year (mmpy).
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Classic Tafel analysis involves extrapolating the linear regions of a logarithmic current-versus-potential plot back to their point of intersection. The experimental data are fitted by adjusting the parameters Ecorr, Icorr, βa, and βc. This curve-fitting approach is advantageous because it does not require a fully developed linear segment on the plot. In cases of non-uniform dissolution, it may be necessary to measure corrosion products directly in order to determine the equivalent weight (EW). The conversion of weight loss data to corrosion rate (CR) is performed using Equation (1):
(CR = Icorr × K × EW)/(d × A)
where Icorr = corrosion current (A), K = 3272 mm (A-cm-year), EW = equivalent weight (g/equivalent), d = density (g/cm3), A = sample area (cm2) [55].
Table 1 shows the corrosion potential (Ecorr), corrosion current density (icorr), the anodic (βa) and cathodic (βc) Tafel slopes for aluminum samples with different surface treatments in sodium chloride solution. The corrosion current densities (Icorr) and corrosion rates decrease with the application of various surface treatments compared to the initial sample. The initial sample exhibits the highest Icorr value and a corresponding corrosion rate of 0.03 mmpy. The clear and black anodized samples show about 30 times lower corrosion current density and corrosion rate compared to the untreated sample, indicating much better corrosion resistance. The combination of pre-anodizing and painting provides the most effective corrosion protection, achieving an extremely low Icorr of 9.72 × 10−10 A/cm2 and a corrosion rate of 0.00003 mmpy, which is approximately 1000 times lower than that of the original sample.
Electrochemical impedance spectroscopy (EIS) was used to investigate the corrosion behavior of aluminum samples with different surface treatments, in a sodium chloride (NaCl) solution. Figure 4a displays the Nyquist, Figure 4b Bode magnitude and Figure 4c Bode phase angle plots for initial (uncoated), anodized and pre-anodized plus painted samples.
In the Nyquist plot (Figure 4a), the diameter of the semicircle is directly related to the polarization resistance, which serves as an indicator of corrosion protection efficiency. The sample treated with both pre-anodizing and painting exhibits the largest semicircle diameter, indicating significantly higher impedance values and higher corrosion resistance. The initial samples show much smaller semicircles, showing that the material is more likely to corrode. The remaining samples, including those that were only anodized, show intermediate semicircle diameters, reflecting moderate levels of corrosion resistance. The Bode magnitude plot (Figure 4b) supports these observations. The anodized samples show medium impedance, suggesting they provide some level of protection. The untreated samples had low impedance, indicating very limited or no effective surface protection. Also, a decrease in the low-frequency impedance typically reflects degradation or breakdown of the protective passive film, indicating loss of corrosion protection, which is consistent with the potentiodynamic polarization curves of the initial sample [34,36,37]. In the Bode phase angle plot (Figure 4c), the pre-anodized and painted sample demonstrates a broad plateau with a phase angle near −90°, which is characteristic of capacitive behavior and indicates a stable dielectric interface [54]. The phase angle plots for the aluminum samples indicate the presence of at least two time constants. This suggests a complex protective system involving multiple electrochemical processes. The initial samples show a rapid phase drop and low phase angles, indicating limited corrosion protection [56,57]. Overall, the EIS results clearly illustrate the beneficial effect of combined preanodizing and painting. This multilayer system provides enhanced corrosion protection. The clear and black anodized samples showed different levels of corrosion protection, likely due to differences in pigment type, thickness or porosity that affect their electrochemical properties. In the diagrams (Figure 4), the straight line represents the fitting curve, while the data points correspond to the experimental measurements.
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Figure 4. (a) Nyquist, (b) Bode impedance magnitude and (c) Bode phase angle plots of Al alloy samples with different surface treatments after immersion in 3.5 wt% sodium chloride solution.
Figure 4. (a) Nyquist, (b) Bode impedance magnitude and (c) Bode phase angle plots of Al alloy samples with different surface treatments after immersion in 3.5 wt% sodium chloride solution.
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3.3. Proposed Equivalent Electrical Circuit Models

To thoroughly analyze the electrochemical behavior of EN AW 6060 aluminum alloy samples subjected to different surface treatments, three distinct equivalent electrical circuits were constructed, as shown in Figure 5, Figure 6 and Figure 7. Each circuit represents the distinct structural and electrochemical properties of the surface layers produced by each treatment, enabling a detailed analysis of the impedance spectroscopy results.
For the homogenized and aged sample, the simplest equivalent electrical circuit model was employed. This model includes the solution resistance (Rs), which represent the resistance of the electrolyte solution between the working and reference electrodes, a constant phase element (CPE1) models the non-ideal capacitive behavior of the electrochemical double layer formed at the metal–electrolyte interface, describing surface heterogeneities and roughness. The charge transfer resistance (Rct) quantifies the resistance to electron movement during corrosion reactions occurring on the aluminum surface. This basic circuit effectively models the corrosion process in bare aluminum samples, where no protective layers affect the electrochemical reactions [58].
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Figure 5. Equivalent circuit representing the corrosion of uncoated Al alloy samples.
Figure 5. Equivalent circuit representing the corrosion of uncoated Al alloy samples.
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In contrast, the anodized samples exhibit a more complex structure due to the presence of a porous oxide film. Therefore, a two-layer model was used to represent both the anodic film and the aluminum substrate. The first layer models the anodic oxide film, including Rs, a constant phase element (CPE1) and a resistance (R1) that characterizes the oxide layer’s dielectric and resistive properties. The oxide layer acts as a shield, stopping ions from passing through and improving corrosion resistance. Below the oxide film, the aluminum substrate is modeled by a second constant phase element (CPE2) in parallel with a charge transfer resistance (Rct), reflecting the electrochemical activity at the metal interface beneath the oxide. Additionally, a Warburg diffusion element (W) is included for diffusion-controlled processes.
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Figure 6. Equivalent circuit representing the corrosion of anodized Al alloy samples.
Figure 6. Equivalent circuit representing the corrosion of anodized Al alloy samples.
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For the pre-anodized samples that were further powder painted, a more detailed equivalent circuit was necessary for the representation of the multi-layered protective system. This circuit includes all the components found in the model used for anodized-only samples, Rs, CPE1, R1 for the anodic oxide layer and CPE2, Rct, W for the substrate, while including an additional parallel branch consisting of CPE3 and R2. This additional branch represents the electrostatic powder coating, which forms a continuous, insulating barrier on top of the anodic film. The coating’s capacitive and resistive characteristics are modeled by the constant phase element (CPE3) and resistance (R2), respectively. This hierarchical modeling approach provides a deep understanding of how corrosion protection works in each surface treatment. By separating the effects of the electrolyte, anodic oxide layer, substrate and powder coating, the equivalent circuits allow for precise measurement of coating durability, oxide layer quality and corrosion resistance of the sample.
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Figure 7. Equivalent circuit representing the corrosion of pre-anodized and painted Al alloy samples.
Figure 7. Equivalent circuit representing the corrosion of pre-anodized and painted Al alloy samples.
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In addition to the specific equivalent circuits designed for each sample type, a more generalized equivalent circuit model was developed to include uncoated, anodized and pre-anodized and painted samples within a single, flexible model. This model adapts to different surface conditions by adjusting key parameters, particularly the variables u and n, which define the behavior of the constant phase elements and resistances for each case. The circuit includes the solution resistance (Rs), representing the electrolyte’s resistance, along with parameters R1 and CPE1, which correspond to the powder coated layer when present. The anodized layer is described by CPE2 and R2, capturing its capacitive and resistive properties, respectively. At the metal/electrolyte interface, the charge transfer resistance (Rct), a third constant phase element (CPE3) model the non-ideal double-layer capacitance and a Warburg impedance element (Zw) is incorporated when necessary. This flexible equivalent circuit allows reliable fitting and interpretation of electrochemical impedance data for various surface treatments, offering valuable understanding of how each layer contributes and interacts within the overall corrosion protection system. The values of the equivalent circuit elements shown in Figure 4 are listed in Table 2. The model fits the experimental data well, meaning it can effectively describe the corrosion behavior of all aluminum samples in NaCl solution (with a standard error less than 10%) [59].
The uncoated sample exhibited an α value of 0.87 and low charge transfer resistance (13 kΩ), indicating poor corrosion protection. Anodized samples showed medium corrosion protection. The clear one exhibited a nearly ideal dielectric response (α~1), suggesting a uniform oxide and Rct of 1.48 MΩ, while the black anodized sample showed higher resistance of the anodized layer but lower charge transfer resistance (0.74 MΩ) and α values, indicating reduced oxide integrity, possibly due to increased porosity or dye-related degradation. The high values of resistance indicate that the sealing process was highly effective. Sealing the outer oxide layers effectively fills and blocks the pores in the porous anodic film. This process creates a denser and less permeable oxide layer, which significantly reduces the penetration of corrosive species such as chloride ions, enhancing corrosion resistance [60]. The pre-anodized and painted samples have the highest resistance (R1 = 7.5 MΩ), which corresponds to the powder coating, an intermediate anodized-layer resistance (R2 = 2 kΩ) and improved α values (0.93–0.95). These features show a strong combination of barrier effects, meaning better corrosion protection than anodizing alone. Low values of R2 indicate poor sealing quality of the porous layer, as also confirmed by the SEM images. This can be attributed to the presence of an additional powder coating applied on top, meaning that the porous layer is not the only protective barrier. Overall, while the uncoated sample exhibited the lowest resistance, pre-anodized and painted samples show the most efficient protective behavior [61,62,63].
The thickness of the different layers can be estimated using Equation (2):
C = εεοA/d
where εο = 8.85 × 10−14 F/cm the dielectric constant of vacuum, ε = 10 the relative dielectric constant of aluminum oxide, A the active surface and d the thickness of the layer. This equation is most accurate when a is close to unity [57]. The calculated average values of clear anodized samples are d1 = 14.8 μm and d2 = 4.4 μm while d1 = 22 μm and d2 = 3 μm for the black anodized samples, with a total thickness of 19 μm and 25 μm, respectively, values that are very close to those measured from the SEM images. For the pre-anodized and painted sample, the thicknesses of the anodized layers are d2 = 4.9 μm and d3 = 6.3 μm, with a total thickness of 11 μm, which coincides with and confirms the thickness measured from the SEM images.
Table 2. Parameters of the equivalent circuit elements (Figure 4, Figure 5, Figure 6, Figure 7 and Figure 8) representing the corrosion behavior of uncoated, anodized, pre-anodized and painted samples, after immersion in 3.5 wt% sodium chloride solution.
Table 2. Parameters of the equivalent circuit elements (Figure 4, Figure 5, Figure 6, Figure 7 and Figure 8) representing the corrosion behavior of uncoated, anodized, pre-anodized and painted samples, after immersion in 3.5 wt% sodium chloride solution.
Al SamplesRs
(Ω)		CPE1
(S × sa)		α1CPE2
(S × sa)		α2CPE3
(S × sa)		α3R1
(MΩ)		R2
Rct
W
(S × s1/2)
Initial6.639.95 × 10−60.87------13 kΩ-
Clear
anodized		26.36 × 10−1012 × 10−90.95---0.7 ΜΩ1.48 ΜΩ1.2 × 10−6
Black
Anodized		14 × 10−100.922.9 × 10−90.9---4.21 MΩ0.74 ΜΩ68 × 10−5
Pre-anodized and painted0.11.74 × 10−90.951.8 × 10−90.931.4 × 10−90.97.5 2
kΩ		0.47 MΩ1.3 × 10−5
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Figure 8. General equivalent circuit proposed for the corrosion behavior of uncoated, anodized and pre-anodized plus painted samples, after immersion in 3.5 wt% sodium chloride solution (where n = 0 and u = 0 for uncoated, n = 0 and u = 1 for anodized, n = 1 and u = 1 for pre-anodized plus painted, Al alloy samples).
Figure 8. General equivalent circuit proposed for the corrosion behavior of uncoated, anodized and pre-anodized plus painted samples, after immersion in 3.5 wt% sodium chloride solution (where n = 0 and u = 0 for uncoated, n = 0 and u = 1 for anodized, n = 1 and u = 1 for pre-anodized plus painted, Al alloy samples).
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4. Conclusions

This study focused on a systematic evaluation of the electrochemical behavior of aluminum samples with various surface treatments (untreated, anodized, pre-anodized and painted). Through electrochemical impedance spectroscopy (EIS) and equivalent circuit analysis, several findings were obtained:
  • Surface treatments significantly improve corrosion resistance. Anodized samples demonstrate an approximately 30 times lower corrosion rate, while the pre-anodized and painted samples offer the highest protection, with a corrosion rate nearly 1000 times lower than that of the untreated aluminum.
  • The clear anodized sample showed an almost ideal dielectric behavior (α~1) and a charge transfer resistance of 1.48 MΩ, indicating a uniform oxide. The clear anodized sample had higher anodic resistance but lower Rct (0.74 MΩ), suggesting reduced oxide quality, likely due to porosity or dye effects.
  • The pre-anodized and painted samples demonstrate a complex multilayer electrochemical behavior that explains its superior protective performance. The outer layer exhibits very high resistance (7.5 MΩ) and excellent dielectric properties (α = 0.95), indicating an effective barrier against corrosion.
  • The high values of resistance for the anodized samples indicate that the sealing process was highly effective.
  • The thickness of the anodized layers correlates well with the SEM results.

Author Contributions

Conceptualization, A.M. and F.S.; methodology, F.S., A.M. and N.M.; software, A.B. and E.L.; vali-dation, A.B. and E.L.; formal analysis, F.S., A.B. and I.T.; investigation, E.L., A.M. ans A.B.; resources, N.M. and I.T.; data curation, A.M.; writing—original draft preparation, A.B., F.S. and A.M.; writ-ing—review and editing, N.M., F.S. and I.T.; visualization, A.B.; supervision, F.S. and N.M.; project administration, N.M.; funding acquisition, I.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

Author Ioannis Tsoulfaidis was employed by the company Alumil S.A. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Alloys 04 00017 g001
Figure 1. (a) Images of the aluminum samples, (b) electrochemical cell, and (c) experimental setup for electrochemical measurements.
Figure 1. (a) Images of the aluminum samples, (b) electrochemical cell, and (c) experimental setup for electrochemical measurements.
Alloys 04 00017 g001
Table 1. Corrosion potentials (Ecorr), corrosion currents (icorr), anodic (βa) and cathodic (βc) Tafel slopes for Al alloy samples with different surface treatments in sodium chloride solution.
Table 1. Corrosion potentials (Ecorr), corrosion currents (icorr), anodic (βa) and cathodic (βc) Tafel slopes for Al alloy samples with different surface treatments in sodium chloride solution.
SampleEcorr [mV]Icorr
[A/cm2]		βaβcCorrosion Rate [mmpy]
Initial−0.7569 × 10−70.022−0.520.03
Clear anodized−0.7022.72 × 10−80.78−0.520.0009
Black anodized−0.7224 × 10−81.19−0.860.0014
Pre-anodized and painted−0.7299.72 × 10−100.91−0.460.00003
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Baxevani, A.; Lamprou, E.; Mavropoulos, A.; Stergioudi, F.; Michailidis, N.; Tsoulfaidis, I. Modeling and Analysis of Corrosion of Aluminium Alloy 6060 Using Electrochemical Impedance Spectroscopy (EIS). Alloys 2025, 4, 17. https://doi.org/10.3390/alloys4030017

AMA Style

Baxevani A, Lamprou E, Mavropoulos A, Stergioudi F, Michailidis N, Tsoulfaidis I. Modeling and Analysis of Corrosion of Aluminium Alloy 6060 Using Electrochemical Impedance Spectroscopy (EIS). Alloys. 2025; 4(3):17. https://doi.org/10.3390/alloys4030017

Chicago/Turabian Style

Baxevani, Aikaterini, Eleni Lamprou, Azarias Mavropoulos, Fani Stergioudi, Nikolaos Michailidis, and Ioannis Tsoulfaidis. 2025. "Modeling and Analysis of Corrosion of Aluminium Alloy 6060 Using Electrochemical Impedance Spectroscopy (EIS)" Alloys 4, no. 3: 17. https://doi.org/10.3390/alloys4030017

APA Style

Baxevani, A., Lamprou, E., Mavropoulos, A., Stergioudi, F., Michailidis, N., & Tsoulfaidis, I. (2025). Modeling and Analysis of Corrosion of Aluminium Alloy 6060 Using Electrochemical Impedance Spectroscopy (EIS). Alloys, 4(3), 17. https://doi.org/10.3390/alloys4030017

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