Analysis of Plasma Electrolytic Oxidation Process Parameters for Optimizing Adhesion in Aluminum–Composite Hybrid Structures

Abstract

The Plasma Electrolytic Oxidation (PEO) process was investigated to enhance the adhesion of AA2024-O aluminum alloy with a polyetherimide (PEI) matrix composite, using oxy-fuel welding (OFW). A Central Composite Design (CCD) statistical model was used to optimize three independent parameters in PEO: immersion time (s), duty cycle (%), and electrolyte concentration (Na₂B₄O₇·10H₂O), aiming to achieve a maximum value of shear strength of the hybrid joint (in MPa). The hybrid joint without PEO treatment presented a resistance of 2.2 MPa while the best condition presented a resistance of 9.5 MPa, resulting in a value 4× higher than the untreated material, due to the characteristics of the coating, which presented a more hydrophilic surface, allowing better mechanical interlocking with the polymer matrix and resulting in mixed-mode failure (adhesive, cohesive, and light fiber). In addition to improving adhesion, the PEO treatment provided better corrosion resistance to the alloy, forming an inert aluminum oxide (Al₂O₃) coating, with an improvement of approximately 99.84% compared to the untreated alloy. The statistical design covers about 77.15% of the total variability of the PEO + welding process, with independent factors influencing around 48.4% of the variability.

1. Introduction

Hybrid structures are increasing in the automotive, aerospace, and naval industries, especially when these vehicles are electric or hybrid, making energy efficiency crucial for cost savings. When it is necessary to join components of different materials, adhesive bonding is the primary method employed [1]. It ensures good mechanical strength, mitigates stress concentrations, and offers better corrosion resistance properties [2].

When these materials are metallic alloys, they need to undergo surface treatments to enhance their corrosion resistance and increase their surface area, developing mechanical anchorage sites. In the case of aluminum alloys, the primary treatment used is anodization, which creates a thin alumina (Al₂O₃) oxide layer on the order of micrometers. This improves corrosion resistance in environments rich in Cl⁻ ions and provides a certain degree of affinity with some adhesives [2,3].

The anodization process has several disadvantages, such as the use of extremely acidic electrolytes, high sensitivity to the chemical composition and surface condition of the substrate, and significant environmental and health risks [4]. Should the by-products from the anodizing procedure be indiscriminately released into the sewage infrastructure, it has the potential to instigate eutrophication, a phenomenon that ought to be meticulously circumvented. It is imperative to implement post-treatment protocols for the resultant effluents to avert this issue, which consequently incurs supplementary expenditures associated with transportation and treatment, and amplifies bureaucratic processes due to regulatory compliance [5,6,7].

To mitigate the environmental repercussions associated with the acidic anodization process, an electrochemical methodology predicated on anodization but utilizing elevated voltage levels (ranging from 100 to 700 V) was conceived in the 1970s. This advancement facilitated the implementation of more ecologically sustainable solutions, including those derived from silicates, aluminates, and borates, among various others. Referred to as Plasma Electrolytic Oxidation (PEO) or Micro-Arc Oxidation (MAO), this methodology is esteemed for its advantageous properties, which encompass elevated productivity, the utilization of benign and environmentally responsible alkaline electrolytes, enhanced hardness attributed to localized temperature surges that may attain levels of up to 25,000 K, and improved corrosion resistance resultant from the formation of a compact layer adjacent to the substrate. Furthermore, it affords an exceptional adhesion of the coating to the substrate [2,8].

Although PEO is a highly innovative and effective process, it consumes a significant amount of energy. To initiate the ionization process of gasses, present in the microbubbles near the substrate, voltages start at 100 V–120 V and reach final potentials around 400 V–450 V. This makes the process economically unfeasible for some companies compared to conventional methods with cheaper post-treatment [9,10,11,12,13,14].

In the literature, studies focus on optimizing the physical and chemical characteristics of oxide coatings. Bajat et al. [15] investigated the time optimization of the PEO process to stabilize corrosion in aluminum alloys. Coto et al. [16] optimized the PEO process on CP Grade 1 titanium sheets to improve photocatalytic properties. However, it is observed that there are few studies in the literature that aim to optimize surface properties using electrolytic plasma in light alloys, such as aluminum for applications in hybrid structures.

Recognizing the need to optimize adhesion between dissimilar materials, this study employs a Central Composite Design (CCD) factorial design to optimize three PEO process parameters: immersion time (X1), duty cycle (X2), and the electrolyte concentration of sodium tetraborate Na₂B₄O₇·10H₂O (X3). This process is then applied to the AA2024-O aluminum alloy to improve adhesion to the PEI/fiberglass composite material, using oxyacetylene welding (OFW), thus creating a type of adhesive bond without the need for external adhesive, using only the thermoplastic composite’s matrix.

2. Materials and Methods

2.1. PEI/Glass Fiber Laminate

The laminate used in this study was obtained from Toray Advanced Composites (Nijverdal, The Netherlands). Its polymer matrix is TC1000, reinforced with glass fiber (50% by volume). Widely used in the manufacturing of aerospace structures, such as seat shells, duct channels, rail interiors, and face sheets for structural sandwich panels, PEI/fiberglass laminate is characterized by its relatively high glass transition temperature (Tg) of approximately 217 °C (polymer matrix—according to ASTM D3418 [17] and D3878 [18]), degradation temperature of around 460 °C, and good mechanical strength (516 MPa).

2.2. Aluminum Alloy 2024

In this study, the AA2024-O alloy (Al-Cu) was used, with a chemical composition according to the supplier presented in

Table 1. Chemical composition of the AA2024 alloy, according to the supplier.

Si	Fe	Cu	Mn	Cr	Zn	Ti	Al
<0.5%	<0.5%	3.8–4.9%	0.3–0.9%	<0.1%	<0.25%	<0.15%	Balance

.

It has broad applicability in the aerospace industry, particularly in the production of structures such as fuselages, where the requirement for damage resistance is higher [19].

In this study, samples were prepared with dimensions of 100 × 25 × 2.5 mm, following ASTM D1002:19 standards [20], as shown in Figure 1. After cutting the samples, the aluminum was sanded with sandpaper to homogenize the surface up to 100# mesh, cleaned with a neutral detergent solution in an ultrasonic bath (900 s), then rinsed with isopropyl alcohol (99%), dried with a hot air blower, and stored on soft paper until treatment. A small area of 25 × 25 mm on the aluminum was designated for PEO treatment.

2.3. Experimental Design

For this study, a Central Composite Design (CCD) with k factors (where k = 3 factors) was employed, including immersion time (s), duty cycle (%), and electrolyte concentration (g/L). Such an experimental design involves a factorial layout among the variables, incorporating central points “0” and axial points “α” (

Table 2. PEO variables.

Real Variables	Coded	Levels
		−α	−1	0	+1	+α
Time (s)	X1	197	300	450	600	702
Duty Cycle (%)	X2	15	20	45	70	87
Concentration (g/L)	X3	0.6	3.0	6.5	10.0	12.0

), which aid in predicting the response surface behavior.

From the data presented in Table 2, 17 experimental patterns were generated, which are a set of parameters (time, duty cycle, and concentration) and each pattern was repeated 5 times, meeting the ASTM D1002:19 standard. For statistical analysis, the Minitab 17.1.0 software was used. Analysis of variance (ANOVA) was conducted in this study to ensure process reliability and to assess the significance of each parameter on the response variable “y” (lap shear strength, MPa), calculated from Equation (1). The coefficient of determination (R²) was also assessed to quantify the total variability and determine the proportion explained by the model.

$$\tau ={\displaystyle \frac{F_{máx}}{A}}$$

(1)

where τ: joint shear strength (in MPa); F_máx: maximum force recorded before joint fracture (in N); and A: welded area of the structure (in mm²).

2.4. PEO Treatment

The electrolyte used in this study was based on sodium tetraborate (Na₂B₄O₇·10H₂O), with varying concentrations as shown in Table 1, supplemented with 1.5 g/L of potassium hydroxide (KOH) to increase the conductivity of the solution. This solution was chosen due to its promising adhesion results at the metal/oxide interface, as well as its ability to avoid the formation of excessively thick oxide layers, as in the Na₂SiO₃ solution [21]. Silicon-rich electrolytes, on the other hand, tend to produce coatings that are brittle under shear stresses [1,2,21,22]. The treatments were performed with different and constant current densities of 7.74 mA/cm², as shown in Figure 2 (showing one of the treatments).

The system used for the treatment consists of a pulsed DC power supply T²S TECHNOLOGY, model PS-2, which provides a range of 0 to 900 V with duty cycle control (15 to 100%), a 25-ohm rheostat used to regulate the electric current in the system, a 250 mL stainless steel (304) beaker as cathode, and a mechanical stirrer with a stainless steel (304) shaft.

2.5. Joining Dissimilar Materials

The method of joining materials used in this study was oxy-fuel welding (OFW). The gas pressures were set at 0.05 MPa for acetylene and 0.1 MPa for oxygen, with a flame exposure time of 2 min (on aluminum), as shown in Figure 3. To measure the temperature at the metal/compound interface, a type K thermocouple, FLUKE, model 117 True RMS, was used.

When evaluating the temperature, it was observed that it was around 270 ± 10 °C, which is above the glass transition temperature (Tg) of the polymer matrix in the composite. It was not possible to control the temperature much, as new studies applying oxy-fuel welding are necessary for its optimization [23,24,25].

2.6. Characterizations

To evaluate the lap shear strength (LSS), a Shimadzu AG-X universal testing machine (Kyoto City, Japan) with a 50 kN load cell was used, operating at a speed of 1.5 mm/min, in accordance with ASTM D1002:19 [20]. Five samples were tested for each experiment (18 experimental conditions, with 17 corresponding to treated samples and 1 used as a control), totaling 90 samples analyzed. After statistical analysis and determining the highest lap shear strength value, the coating that yielded this result was evaluated using scanning electron microscopy (SEM) with a ZEISS microscope, model EVO LS15 (Jena, Germany). The thickness of the oxide coatings was measured using an INSTRUTHERM non-metallic film thickness gauge, model ME 250 (Sao Paulo, Brazil), employing the eddy current concept. Each sample underwent 10 measurements, with an accuracy of 0.1 µm. The contact angle of the untreated and treated samples was measured using a Ramé-Hart goniometer (ADVANCED 300 F-1, Succasunna, NJ, USA), applying 10 drops to each surface randomly.

To evaluate the corrosion resistance of the alloy and after PEO treatment, the samples were subjected to linear polarization electrochemical techniques using the AUTOLAB potentiostat/galvanostat model PGSTAT302N from Metrohm Autolab© (Utrecht, The Netherlands). The tests were conducted in a horizontal electrochemical cell with a 3.5% NaCl solution and equipped with three electrodes: treated AA2024 alloy (working electrode), platinum (counter electrode), and Ag/AgCl (saturated KCl—reference electrode). One replicate was performed for each sample, with each sample being immersed in the solution for approximately 86,400 s (at open circuit potential). The linear polarization test was performed at a scan rate of 0.33 mV/s, with an analysis range of +700 to −100 mV relative to the open circuit potential (OCP) value.

3. Results and Discussions

3.1. Lap Shear Strength (LSS)

The values obtained after the lap shear strength test are presented in

Table 3. Coded and actual parameters used and response variable (lap shear strength).

Std.	Coded Variable			Real Variable			LSS (MPa)
	X1	X2	X3	Time (s)	Duty (%)	Conc. (g/L)
00	N/A	N/A	N/A	N/A	N/A	N/A	2.2 ± 1.5
01	−1	−1	−1	300	20	3	7.6 ± 3.0
02	+1	−1	−1	600	20	3	7.3 ± 1.6
03	−1	+1	−1	300	70	3	9.5 ± 0.5
04	+1	+1	−1	600	70	3	6.9 ± 1.7
05	−1	−1	+1	300	20	10	7.2 ± 1.7
06	+1	−1	+1	600	20	10	5.9 ± 2.6
07	−1	+1	+1	300	70	10	6.6 ± 1.1
08	+1	+1	+1	600	70	10	5.8 ± 2.2
09	−α	0	0	197	45	6.5	7.1 ± 2.1
10	+α	0	0	702	45	6.5	6.9 ± 1.9
11	0	−α	0	450	15	6.5	7.5 ± 3.3
12	0	+α	0	450	87	6.5	7.8 ± 0.8
13	0	0	−α	450	45	0.6	7.6 ± 1.2
14	0	0	+α	450	45	12	5.7 ± 2.7
15	0	0	0	450	45	6.5	7.1 ± 3.3
16	0	0	0	450	45	6.5	6.6 ± 1.7
17	0	0	0	450	45	6.5	5.7 ± 1.0

. The experiments conducted with the aluminum samples treated by PEO (01 to 17) show average lap shear strength values ranging from 5.7 to 9.5 MPa. Considering the lap shear values, it is observed that the PEO treatment resulted in increases of 2.5 to 4.3× compared to the set without surface treatment. This is due to the costing’s morphological characteristics, such as micro-pores, protrusions, and other microstructures that appear in the oxide coating, providing a larger surface area for the sample and allowing greater interaction with the thermoplastic matrix [1,2,21,26,27,28].

The obtained lap shear values are promising compared to other studies conducted on both metallic and polymeric materials.

Table 4. Shear strength values of joints in dissimilar materials.

Methodology	MPa	Ref.
AA2024 (treated by PEO) + PEI/welding by OFW (this study)	9.5	-
AA6060-T6 + AA6060-T6/adhesive bonding	35.9	[1]
AA2024-T3 (treated by PEO) + PEI/welding by OFW	5.2	[21]
AA2024-T3 (anodized) + PEI/welding by laser YB	16	[29]
AA6082-T6 + PEI glass fiber/friction injection joining	1.1	[30]
PEI Glass fiber + PEI glass fiber/adhesive bonding	15	[31]
AA5052 (treated by PEO) + Polypropylene/friction stir spot welding	1.4	[32]
CF-PPS + CF-PPS/friction stir spot welding	2.4	[33]
Polyamide 6 + Polyamide 6/adhesive bonding	7.5	[34]
AA1100 (treated by PEO) + PEI/welding by OFW	10.7	[35]

presents some comparisons of lap shear values and the materials used.

With the development of a statistical model, the significance of parameters (independent variables) was evaluated using analysis of variance (ANOVA). This model was adjusted by the coefficient of determination (R²), which quantitatively helps assess how much each variable influences the response variable (LSS) [1,36,37].

The ANOVA analysis results, using the independent variables immersion time, duty cycle, and electrolyte concentration, to the dependent variable (LSS), are presented in

Table 5. ANOVA with LSS as the dependent variable.

Factor	DF	Sum of Squares	F-Value	p-Value
Model	10	10.9766	2.03	0.200
Time	1	2.0328	3.75	0.101
Duty Cycle	1	0.7273	1.34	0.291
Concentration	1	4.1203	7.60	0.033 *
Time2	1	1.5398	2.84	0.143
Duty Cycle2	1	0.1024	0.19	0.679
Concentration2	1	0.5192	0.96	0.365
Time × Duty Cycle	1	0.3856	0.71	0.431
Time × Concentration	1	0.0521	0.10	0.767
Duty Cycle × Concentration	1	0.5717	1.06	0.344
Lack-of-Fit	4	3.0860	9.35	0.099
Error Pure	2	0.1651
R2	75.15%

* Significant factor for the statistical model.

.

It was found that the F value (responsible for checking whether a term or the model itself is associated with the response variable) for the model was 2.03, implying that the adopted model is not significant in the response variable (LSS), and also showing that there is a 20% probability of the F value being due to noise. This study observed that the only factor significantly influencing the dependent factor is the electrolyte concentration (X3). As the “p-value” is less than 0.05, it indicates that this factor has a significant effect on the response variable. Furthermore, when analyzing the coefficient of determination (R²), the model explains 75.15% of the PEO + welding process variability. However, the statistical model did not demonstrate significance in explaining the variability, considering its p-value (0.200), which is greater than 0.05 [23,29,37].

It can be inferred that the model is not significant, due to the complex mechanisms of the PEO process added to the oxy-fuel welding process (which still requires optimization), as already presented in a previous study [35,38].

To evaluate the influence of each independent variable on the dependent variable, Equation (2), called effect size (η²), can be used. This equation considers the sum of squares of factors, blocks, and/or the statistical model itself to quantify variability within a data set [39].

$${\eta }^2={\displaystyle \frac{SS}{SST}}\times 100$$

(2)

where “SS” is the sum of squares of the specific factor, which quantifies the variability attributed to a specific factor within the statistical model, and “SST” is the total sum of squares of the model, which represents the total variability observed in the data, accounting for both the explanatory variables and the error [39]. Based on Equation (2), the effect of each factor was 14.29% for immersion time, 5.11% for duty cycle, and 28.96% for concentration. It is observed that the pure model error influences only 1.16% of the total process variability.

3.2. Contact Angle of Aluminum Surfaces

Contact angle analysis is a good indicator to reveal the hydrophobicity of the material surface. It can also be applied to surface adhesion, as the smaller the angle the better its wettability, and its value is strongly dependent on the micro- or nanostructure of the surface of the material [9]. Considering the untreated samples and the treated sample that exhibited the highest resistance value (9.5 MPa), contact angle analysis was conducted (Figure 4). The results indicated an angle of 72.4 ± 4.0° for the untreated sample and 37.0 ± 4.3° for the treated sample, representing a 48.9% reduction. This significant decrease in the contact angle suggests a substantial improvement in the adhesion of the thermoplastic matrix.

3.3. Fractographic Evaluation of the Aluminum/Composite Interface

After obtaining the PEO process parameters and conducting the lap shear test, the fractured surfaces were visually characterized following the ASTM 5573-99 (2019) standard [40] to analyze the failure modes at the interface.

Figure 5 shows the surfaces of the aluminum and thermoplastic composite samples, highlighting the joined regions. It is observed that there were mixed-mode fractures, with three different types. The yellow arrows indicate a small region with adhesive failure, as there was no polymer matrix in that region in the aluminum sample after the assembly rupture, representing 16.64%. The blue arrows indicate a polymer matrix’s cohesive failure, where the matrix remained on the aluminum sample, representing 34.02%. Finally, the red arrows indicate a light fiber failure, with the reinforcement of the composite exposed both outside the laminate sample and on the aluminum sample, representing 49.34% of the total fracture [41]. It is also possible to observe the edge effect at the boundaries of the composite sample, indicating an excessive tightening in the assembly during the welding process, with the matrix reaching the glass transition temperature and flowing to the edges, a phenomenon previously observed in other studies [19,24,30,39].

In Figure 6, the different stages of deformation in the samples during the lap shear test are shown, and on the right, a real image after fracture is observed. Noticeably, the aluminum sample exhibited considerable deformation after the test, which is attributed to the material condition. In this study, AA2024-O aluminum was used, where the “O” designation signifies annealed material, characterized by high ductility and significant plastic deformation (purple arrow in Figure 6) [42,43,44].

Although the PEI/glass fiber sample did not show deformation like the aluminum alloy, it exhibited an edge effect (green arrow), which is attributed to excessive tightening and the thermoplastic matrix softening phase, leading to flow towards the edges of the sample, as shown in Figure 6 and observed in other studies [19,24,30]. Studying this effect is crucial because it can result in delamination in the composite material, impacting the integrity of structures and/or substructures [45,46,47].

3.4. Coating Corrosion Resistance

The data from the linear polarization measurements are presented in

Table 6. Corrosion potential (E_corr), corrosion current density (j_corr), pit corrosion (E_pit), and corrosion rate (CR).

	Ecorr (V)	jcorr (A/cm2)	Epit (V)	CR (mm/Year)
AA2024	−0.64	7.4 × 10−5	−0.55	9.6 × 10−2
AA2024 (PEO)	−0.47	1.1 × 10−7	+ 0.85	1.5 × 10−4

, and the polarization curves of treated and untreated aluminum samples are shown in Figure 7. In the figures, E_corr and j_corr represent the corrosion potential and corrosion current density, respectively. Additionally, E_pit indicates the potential where a breakdown of the anodic layer occurs and localized corrosion (pitting) begins. The corrosion rate (CR) in mm/year is presented in Table 6 and is calculated using Equation (3).

$$CR={\displaystyle \frac{3.27\times {10}^{-3}\times j_{corr}\times W}{\rho }}$$

(3)

where CR is the corrosion rate (mm/year); j_corr is the corrosion current density (A/cm²); W is the equivalent mass of the material studied (according to ASTM G102: 2015 [48]), and $\rho$ is the specific mass of the material studied (g/cm³).

In general, it is observed that the PEO treatment made the aluminum sample much more corrosion-resistant compared to the untreated sample, both in terms of nobility (corrosion potential, E_corr) and corrosion rate (current density, j_corr). A higher potential on the y-axis indicates a greater nobility of material, with less interaction with the aggressive environment. Moreover, being more shifted to the left on the x-axis (Log (i)) of the graph indicates higher corrosion resistance [2,49,50].

The data from Table 6 and Figure 7 demonstrate that the PEO treatment significantly increased the corrosion resistance of the AA2024 aluminum alloy. The pitting potential (E_pit) indicates the oxide layer’s durability until its breakdown. In the untreated sample, the rupture points were subtle, around −0.55 V, with subsequent attempts at passivation. In contrast, the PEO-treated sample exhibited a more pronounced pitting potential at +0.85 V, characterized by a clear breakdown of the anodic curve and a sudden increase in corrosion current density [2,19,51].

The PEO treatment on the AA2024-O alloy significantly increased its corrosion resistance, with a reduction in corrosion rate of approximately 99.84% compared to the untreated sample (Equation (4)).

$$Reduction CR={\displaystyle \frac{(CR AA2024 untreated-CR AA2024 treated)}{CR AA2024 untreated}}\times 100$$

(4)

This improvement in resistance is attributed to the formation of an oxide layer acting as a barrier, consistent with findings from other studies demonstrating that PEO treatments indeed decrease the corrosion rate in aluminum alloys [52,53].

The noise observed at the end of the polarization curve corrosion test may indicate an attempt at repassivation of the alloy, reflecting changes in the surface state as it tries to form a protective layer. However, the test interruption due to the equipment reaching its “overlay” suggests that the continuous scanning method may have introduced inaccuracies. Continuous sweeps can distort the half-sweep curve, affecting corrosion potential and current density. Furthermore, traditional analysis techniques can introduce errors, especially in small ranges of superpotentials. Therefore, although noise may suggest repassivation, it is crucial to consider experimental limitations when interpreting results [54,55].

Figure 8 shows scanning electron microscopy images of the AA2024 aluminum alloy: an untreated sample (a, b) and a sample treated with the PEO process in experiment 3 (c, d).

The treated sample (c, d) exhibits a surface with a compact morphology and few pores, featuring a thin coating with a thickness of 1.7 ± 0.5 µm. This is attributed to both the applied electrical regime, with a final voltage of around 320 V and a constant current in 60 mA, and the electrolyte used (Na₂B₄O₇·10H₂O), which allowed the development of a compact and thin layer. Other authors have observed that morphology strongly depends on the applied electrical potential; higher potentials result in thicker oxide coatings due to the dielectric layer breakdown [2,11,56].

The PEO coating showed a low number of pores, which can be explained by the electron avalanche that occurs during the process. This phenomenon generates rapid ionization and an intense electrical discharge, leading to the uniform melting and solidification of the material, minimizing the formation of pores on the coating surface. Thus, the high energy density provided by the electron avalanche contributes to a more compact and homogeneous structure. This phenomenon causes localized temperatures to briefly reach between 10,000 K and 25,000 K, followed by rapid cooling with the aqueous solution [8,57].

It is observed that the untreated sample in Figure 8a,b exhibits pores with distinct morphologies across the surface, indicated by the yellow arrows. Within these pores, microcracks are visible, which could potentially allow the substrate to be exposed to a chloride-rich environment, thereby increasing the corrosion rate, as illustrated in Figure 9.

As already reported in the literature, Cl⁻ ions interact with AlOH functional groups, reacting to form soluble aluminum chloride, as shown in Equation (5). This process leads to an increase in surface acidity due to the hydrolysis of Al³⁺ ions [58,59,60].

$$Al({OH)}_3+{3Cl}^{-}\to {AlCl}_3+{3OH}^{-}$$

(5)

The passive layer of the alloy allows Cl⁻ ions to penetrate easily, reaching the base material and promoting localized corrosion. However, the PEO treatment facilitated the growth of a thicker oxide layer with lower porosity, effectively mitigating the interaction of the alloy with Cl⁻ ions. This phenomenon has also been observed in other studies [61,62].

4. Conclusions

In this study, the PEO process was used to grow a thin alumina oxide (Al₂O₃) layer on the AA2024-O aluminum alloy. The objective was to improve the alloy’s adhesion with the PEI/glass fiber thermoplastic composite using OFW, ensuring good mechanical performance (LSS).

Considering the strength of the aluminum/composite interface, the PEO treatment improved the shear strength, with lap shear values ranging from 5.7 to 9.5 MPa, a significant improvement compared to untreated aluminum (2.2 MPa). This improvement is attributed to the increase in surface area provided by the oxide coating, thus improving mechanical interlocking with the polymer matrix. Moreover, the wettability of the anodized surface was better, from 72.4° to 37°, which corroborates the increase in adhesion.

From the ANOVA analysis, it was found that the statistical model is not significant (R² = 75.15%), with the model presenting a p-value of 0.200. Only the concentration of the solution (X3) showed significance with a p-value of 0.033. Additional analyses were carried out to determine the effect size (η²) of each factor. It was found that the electrolyte concentration influenced 28.96%, followed by the immersion time at 14.29%, followed by the duty cycle at 5.11%.

The corrosion analysis demonstrated that the PEO treatment is effective in mitigating localized corrosion in the AA2024 alloy by creating a thin barrier oxide layer that seals pores and defects, thereby further improving the material’s corrosion resistance. The treated sample exhibited higher corrosion potentials and significantly lower corrosion rates, with an improvement of 99.84%. These findings underscore the effectiveness of PEO treatments in enhancing the corrosion resistance of aluminum alloys in saline environments.