Ajuga orientalis L. Extract as a Green Corrosion Inhibitor of Aluminum in an Acidic Solution: An Experimental and DFT Study

Abstract

The inhibitory effect of A. orientalis L. extract (AO) on aluminum corrosion in a 1.0 M HCl solution was investigated utilizing weight loss, electrochemical polarization, electrochemical impedance spectroscopy (EIS), and scanning electron microscopy (SEM). The results show that AO is a potent inhibitor in an acidic environment, and that the inhibition potency increases with concentration. Temperature investigations showed that, in an acidic medium, the efficiency decreased, increased, and then decreased as the temperature rose. Adsorption isotherms from Freundlich, Temkin, El Awady, and Redlich–Peterson (R-P) approximated the inhibitor’s adsorption properties. For the inhibitory behavior, a physical and chemical adsorption mechanism is proposed. The adsorption process’s thermodynamic parameters (Ea, ΔH*, and ΔS*) were determined and explained. The inhibitor, AO, was identified as a mixed-type (anodic and cathodic) inhibitor based on polarization studies. According to the SEM findings, the inhibitor partially covers the metal surface, providing it with a respectable level of protection. The weight loss, electrochemical polarization, EIS, scanning electron microscopy (SEM), and quantum chemical calculations show a strong agreement, indicating that the AO extract is a highly effective inhibitor of aluminum in an acidic solution.

1. Introduction

The issue of corrosion is one that practically all metals and alloys face. Corrosion happens when metals and alloys are subjected to specific environmental factors. Rust is frequently produced when the metal in question reacts with its environment. A metal surface and oxygen interact physiochemically to generate oxides or salts, which is referred to as corrosion [1,2]. A lot of work has been performed in the last few years to figure out what causes rust, how it works, and what factors have a great effect on the lifetime of metallic materials [3].

Because of its low density and, thus, low weight, Al and its alloys have been widely used in a variety of sectors. Al and Al-alloys are also widely used due to their high electrical conductivity, thermal characteristics, and superior corrosion resistance. However, aluminum corrosion can occur under specific conditions, making its prevention a key scientific challenge [1,2,3,4,5,6,7,8]. Corrosion on aluminum surfaces is usually quite visible, even in its early stages, as a general etching, pitting, or roughness of the aluminum surfaces. This reaction is accompanied by a change in the oxidation state of Al from 0 to +3. These three electrons are captured by 3H⁺. Aluminum corrosion produces aluminum hydroxide Al(OH)₃, which is a water-insoluble, white, gelatinous precipitate [9].

There are several ways to avoid corrosion, but they all generally involve taking precautions to keep metal surfaces isolated from corrosive conditions or changing the environment in some way [10].

The three main categories of corrosion prevention are cathodic, anodic, or mixed corrosion inhibitor procedures. Anodic or cathodic corrosion reactions can be stopped by covering the metal surface or changing the activation energy of the redox process during corrosion [11].

The majority of corrosion inhibitors are poisonous, expensive, and non-biodegradable manmade compounds. As a result, finding ecologically friendly inhibitors is desirable. The importance of plant extracts has grown as a result of their status as a sustainable, eco-friendly, and readily accessible source of a diverse array of inhibitors. Natural compounds have been employed to prevent the corrosion of many metals in a variety of situations in the past. Researchers have found that green corrosion inhibitors provide places for electrons to move, and functional groups with oxygen, nitrogen, sulfur, and phosphorous atoms provide electrons to help the inhibitor stick to the metal’s surface [12,13,14,15,16,17,18,19,20]. Complex organic species, like anthocyanins, diterpenoids, sterols, ionones, iridoids, flavonoids, glycosides, alkaloids, tannins, anolides, and triterpenes, are thought to be the reason why the extracts of the plants are so good at stopping corrosion [11,12,13,14,15,16,17,18,19,20]. Several techniques are used to track the impacts of corrosion and to monitor the corrosion process. These include weight loss, Tafel polarization, hydrogen penetration, linear polarization resistance, and other techniques [15].

In recent studies on corrosion inhibitors, researchers have increasingly turned to quantum chemistry techniques to improve the effectiveness of potential inhibitors [21,22]. The use of the density functional theory (DFT) and computer science has provided valuable tools for studying natural product molecules in this context. The DFT approach has proven particularly useful, as it offers the improved treatment of electron interactions compared to post-Hartree–Fock (HF) methods [22,23]. The DFT has been extensively applied to quantify various characteristics, such as chemical structure, kinetic properties, and thermochemistry, across different types of carbohydrates.

Investigating the viability of employing A. orientalis methanolic extract (AO) as a corrosion inhibitor is the goal of the current investigation. Due to their accessibility and ease of application, a lot of publications on the use of natural substances or plant extracts as corrosion inhibitors have recently been published in the literature. This study examined AO as a corrosion inhibitor of aluminum in an acidic solution. The use of this plant as a corrosion inhibitor is not mentioned in any publication. This study also examined the impact of temperature on the effectiveness of inhibition, as well as the evaluation of some thermodynamic parameters using chemical and electrochemical methods. Furthermore, for the first time, this study utilizes a combination of weight loss analysis, electrochemical polarization, scanning electron microscopy (SEM), and quantum chemical calculations to investigate the protective efficiency of the AO methanolic extract for aluminum in an HCl solution.

2. Materials and Methods

2.1. Collection and Pretreatment of Plant Samples

The ariel parts of A. orientalis (AO) were collected from the Ajloun region throughout the flowering season. Each sample was cleaned with running water before being dried for 30 days. Before extraction, the dried plant was powdered [18,23].

2.2. Preparation of Plant Extract

The crude was extracted from the solid matrix by using the Soxhlet extraction method. A 30 g portion of the ground plant was used, and the thimble was filled with it. The first step included extracting fatty acids using 500 mL of petroleum ether as a solvent. With 500 mL of methanol, the remaining plant matter was extracted over a period of around 24 h by reflux. The leftover crude was employed as a possible corrosion inhibitor once the solvent was dried using a rotary evaporator. A stock solution of the inhibitor was prepared by dissolving 1.0 g of the crude extract in 1000 mL of pure methanol (1000 ppm). All polarization and weight loss studies utilized diluted solutions of this stock.

2.3. LC-ESI-MS/MS

The secondary metabolized compounds of interest were screened using a Bruker Daltonik Impact II ESI-Q-TOF System (Berman, Germany) and Bruker Dalotonik Elute UHPLC system (Bremen, Germany) in negative (M-H) electrospray ionization modes similar to the procedure described in the literature [18,24].

2.4. Specimen Preparation

For the experiments using acidic media, rectangular, aluminum foil specimens with measurements of 3 cm in length, 1 cm in width, and 0.3 mm in thickness were employed. For additional experiments in an acidic medium, cylindrical, pure aluminum specimens that were 1.5 cm high and 2 cm in diameter were employed. Before performing all measurements, the specimens were polished using metallographic emery paper up to 1200 grits [16,17,18,19,20], rinsed with distilled water and acetone, and dried with tissue paper. To shield them from the outside environment, the samples were kept in a desiccator.

2.5. Weight Loss Measurements

Weight loss measurements were carried out for aluminum specimens in the absence and presence of the inhibitor at different concentrations (80, 120, 160, 200, 240, and 300 ppm) in a 1.0 M HCl solution. Aluminum samples were placed in test tubes with 15 mL of diluted solution, and weight loss measurements were taken for each exposure period of 2, 4, and 6 h at 30 °C. The experiment was repeated at temperatures of 35 °C, 40 °C, 45 °C, and 50 °C at a fixed time (4 h). A water thermostat that could be adjusted to 0.1 °C was used throughout this trial. The aluminum coupons were taken out of the test solution after the required time had passed, cleaned with distilled water and an acetone solution, thoroughly dried, and then reweighed. Using an electronic balance, the weight reduction was measured to the nearest 0.0001 g (Mettler HK 160, Mettler-Toledo Ltd., Leicester, UK). The mean value of the weight loss was reported after studies in triplicate were carried out.

2.6. Electrochemical Measurements

Two electrochemical techniques, namely Tafel polarization and electrochemical impedance spectroscopy (EIS), were used to study the corrosion behavior. All electrochemical measurements were carried out using a CorrTest potentiostat (CS350, Wuhan, China). The cell consisted of a platinum counter electrode, an Ag/AgCl reference electrode, and an aluminum rod (0.2 cm²) as the working electrode. Potentiodynamic polarization measurements were carried out at a scan rate of 1 mV s⁻¹ at ±250 mV with respect to the open circuit potential (OCP). The linear Tafel segments were extrapolated to the corrosion potential to obtain the corrosion current density. EIS measurements were performed for the open circuit potential (OCP) at room temperature at a frequency range of 100 kHz to 0.01 Hz and with an amplitude of 10 mV. All electrochemical results were analyzed using CorrTest software (CS Studio5 version). Each electrochemical measurement was run in triplicate to verify the reproducibility of the results.

2.7. Surface Analysis (Scanning Electron Microscopy (SEM))

A scanning electron microscope (SEM FEI Quanta 200, Geology Department, Faculty of Science, Yarmouk University/Jordan) was used to analyze the morphology of the aluminum specimens. The surface of the investigated aluminum specimens was analyzed before and after immersion for 4 h at 30 °C in 1.0 M of HCl in the absence and presence of the plant extract.

2.8. DFT Computational Details

This study utilized molecular calculations based on the DFT to explore the electronic properties of the major compounds that were found in the studied plant extract. The calculations were made in both the gas phase as well as the acidic solution employing the B3LYP functional as well as a 6-31G*(d,p) basis set. The molecular structures were optimized using Gaussian 09 (G09) software along with DFT-B3LYP functions [25]. Quantum chemical parameters that included the highest occupied molecular orbital energy (E_HOMO), the lowest unoccupied molecular orbital energy (E_LUMO), the energy gap (ΔE_gap) between E_HOMO as well as E_LUMO, and other relevant descriptors, such as the chemical potential (χ), global softness (σ), absolute hardness (η), fraction of electron transferred (ΔN), and electrophilicity index (ω), were determined [26]. These computed parameters were obtained from the calculations, offering insights into the compounds’ electronic structure as well as reactivity. The computational details provided in this study assist in developing a better understanding of the chemical characteristics of the compounds being investigated, as well as their possible applications.

3. Results and Discussion

3.1. Identification and Elucidation of the Compounds Using LC-MS/MS

The methanol extract of AO was further analyzed by LC-ESI-MS/MS [18,24]. The results indicate that Succinic acid (1), Catechol (2), 8-O-acetylharpagide (3), 3,7,3′,4′,5′-Pentahydroxyflavone (4), and Kaempferol-7-O-glucoside (5) are the main components detected in the crude extract (Figure 1) [18,23,24].

3.2. Effect of Inhibitor Concentration

At 30 °C, for various immersion times (2 h, 4 h, and 6 h), for various concentrations of the extract (80–300 ppm), and in the presence and absence of AO, the weight loss (∆W) of aluminum in 1.0 M of HCl was examined. The reduction in weight was quantified to the closest 0.0001 g. Equation (1) provides the weight loss:

$$\mathsf{\Delta }\mathrm{W}=\mathrm{W}-{\mathrm{W}}^{\mathrm{o}}$$

(1)

where W and W^o are the weigh losses of the aluminum specimens in the presence and absence of the inhibitors (AO), respectively. Figure 2 shows the weight loss (∆W) as a function of the immersion time in the 1.0 M HCl solution. Different concentrations of AO were used at 30 °C. Aluminum weight loss was measured over a period in both the presence and absence of various concentrations of AO. Figure 2 demonstrates that the ∆W values (mg) of Al decrease as the inhibitor concentration increases. This is because the metal increases the surface coverage with an increase in AO concentration, which effectively separates the aluminum surface from the medium [13,15,27].

The inhibition efficiency (%IE) and the extent of metal surface coverage (θ) are calculated according to Equation (2):

$$\%\mathrm{I}\mathrm{E}=\mathsf{\theta }\times 100=[1-{\displaystyle \frac{\mathrm{W}}{{\mathrm{W}}^0}}]\times 100$$

(2)

Table 1. Inhibition efficiencies of Al using different concentrations of AO at 30 °C.

Conc. (ppm)	(%IE)
	(2 h)	(4 h)	(6 h)
80	23.3	55.3	60.9
120	26.7	61.2	63.9
160	30.2	62.9	67.0
200	46.5	67.6	69.6
240	53.5	70.6	71.7
300	58.1	72.9	78.3

summarizes all the results of the calculated inhibition efficiencies at 30 °C in the presence of the inhibitor. These tests were conducted at 30 °C at different time periods using different inhibitor concentrations. The highest efficiency in an acidic medium (1.0 M HCl) was (78.3%), which was obtained after 6 h at the maximum tested concentration of the inhibitor (300 mg/L). The capacity of organic molecules to bind to metal surfaces is the major factor that determines how effective they are at preventing corrosion. This adsorption may take place when organic inhibitor molecules displace water molecules [28].

3.3. Effect of Temperature

We noticed that the efficiency in an acidic medium decreases with the increasing temperature until the temperature reaches 40 °C, and then begins to increase until the temperature reaches 50 °C (Figure 3). This is the result of physical adsorption, which then turns into chemical adsorption. Similar results have been reported in the literature for other cases and are similarly explained [29,30].

In this study, the impact of changing the temperature on the corrosion rate was investigated. Five different temperatures (30, 35, 40, 45, and 50 °C) were used at different concentrations of AO as the inhibitor. The corrosion rate of Al is estimated by using Equation (3) (

Table 2. Corrosion rates (mg/h.cm²) at various temperatures in 1.0 M of HCl.

Conc. (ppm)	Rc (mg/h·cm2)
	303 K	308 K	313 K	318 K	323 K
0	0.071	0.092	0.108	0.171	0.336
80	0.032	0.050	0.064	0.085	0.146
120	0.028	0.046	0.058	0.076	0.119
160	0.026	0.042	0.050	0.064	0.088
200	0.023	0.038	0.045	0.061	0.068
240	0.021	0.030	0.042	0.053	0.060
300	0.019	0.026	0.039	0.044	0.053

):

$$R_c={\displaystyle \frac{\mathsf{\Delta }W}{A\times t}}$$

(3)

where R_c is the corrosion rate, ΔW is the weight loss in mg cm, A is the area in cm², and t is the time in hours.

The Al corrosion rate (R_C) varies, as can be seen in Table 2, when different inhibitor concentrations are present during constant immersion in 1.0 M of HCl. For this experiment, a 4 h immersion period was chosen. The results demonstrate that, when the temperature rises, corrosion rates also rise. Usually, raising the temperature speeds up corrosion, which in turn accelerates the metal’s rate of dissolution [20].

3.4. Thermodynamic Considerations

The activation energy (Ea) for the corrosion of Al in 1.0 M of the HCl solution in the absence and presence of different concentrations of AO were calculated using the Arrhenius-type Equation (4):

$$Log{R}_c=LogA-{\displaystyle \frac{E_a}{2.303RT}}$$

(4)

According to the data, the corrosion rates in both inhibited and uninhibited solutions increase with the rising temperature, whereas they decrease as the inhibitor concentration rises.

The temperature dependence of the corrosion rate can be seen as an Arrhenius-type process, the rate of which is determined by Equation (4):

Figure 4 shows the plots of log (Rc) versus 1/T for 1.0 M HCl solutions with and without the inhibitor. Calculated activation energy (Ea) values are listed in

Table 3. E_a, ΔH*, and ΔS* values at various concentrations of AO in 1.0 M of HCl.

Conc. (mg/L)	R2	∆S* (J/mol. K)	Ea (kJ/mol)	∆H* (kJ/mol)
0	0.9159	−0.08	60.49	57.89
80	0.9760	−0.09	58.21	55.61
120	0.9815	−0.10	56.04	53.44
160	0.9782	−0.13	46.17	43.57
200	0.9482	−0.14	43.41	40.80
240	0.9685	−0.14	43.24	40.63
300	0.9614	−0.15	41.40	38.80

.

$$Log\left({\displaystyle \frac{R_c}{T}}\right)=Log\left({\displaystyle \frac{R}{Nh}}\right)+{\displaystyle \frac{{\mathsf{\Delta }S}^{*}}{2.303R}}-{\displaystyle \frac{{\mathsf{\Delta }H}^{*}}{2.303RT}}$$

(5)

The thermodynamic characteristics of activation, such as ΔH* and ΔS*, were computed using the transition state Equation (5).

As a result, a straight line is obtained when log (Rc/T) is plotted versus (1/T). This plot is shown in Figure 4. The slope (−ΔH*/2.303R) and intercept (log(R/Nh)) + (ΔS*/2.303R) of each line are used to calculate ΔH* and ΔS** values. Table 3 shows the results. It is obvious that Ea values are lower in the presence of the varied concentrations of AO than in their absence. Corrosive inhibitors that rely on weak electrostatic forces are less effective at higher temperatures, while stronger chemisorptive inhibitors (which form chemical bonds with the surface) tend to perform better in such conditions. This result, related to a decrease in the activation energy with increasing the temperature and an increase in the inhibitory efficiency, points to a chemisorption process [31,32]. As we have already mentioned, AO shows that the limiting species chemisorb onto the aluminum surface in an acidic solution [33].

The enthalpy of activation values continuously reduced from 57.89 kJ/mol to 38.80 kJ/mol from the uninhibited solution to the greatest inhibitor concentration (300 mg/L) in the acidic solution. The positive values of ΔH* indicate that the dissolution of aluminum in an acidic medium is endothermic, meaning the process requires the absorption of heat from surrounding environment.

Chemical adsorption is thought to be the cause of the inhibitory action in situations like these, where ΔH*-inhibited < ΔH*-uninhibited, and then continuously decreased with the rise in inhibitor concentration. However, the enthalpy values in this study are greater than the typical physical adsorption heat, but less than the typical chemical adsorption heat, indicating that both physical and chemical adsorption processes are likely comprehensive adsorption [34].

ΔS* values are negative, implying that the activation complex is the rate-determining step signifying an association rather than a dissociation mechanism, resulting in reduced disordering [35,36,37].

3.5. Adsorption Behavior

The ability of a corrosion inhibitor to be absorbed on the metal surface determines its efficiency. Adsorption isotherms provide information on the interaction of adsorbed particles not only with one another, but also with a metal surface; therefore, it is critical to understand the adsorption mechanism, which can provide key information about the inhibitor’s and the metal surface’s reactance [38]. To determine which adsorption isotherm model best explains adsorption, the corrosion rate (Rc) and the size of inhibitor surface coverage (θ) were fitted into the various adsorption isotherm models. Langmuir, Temkin, Frumkin, Freundlich, El Awady, Redlich–Peterson (R-P), Dubinin–Radushkevich, and Flory Huggins adsorption isotherms are the most often used isotherm models in corrosion research.

Different types of adsorption equations were tested in an acidic medium, and the results of AO adsorption on an aluminum surface were applicable to R-P adsorption, Freundlich, Temkin, and El Awady isotherms.

The experimental results for the tested inhibitor were used to calculate the Freundlich adsorption isotherm:

$$\log \mathsf{\theta }=\log {\mathrm{K}}_{\mathrm{ads}}+(1/\mathrm{n})\log \mathrm{C}$$

(6)

where θ is the size of the surface covered, C is the concentration, K_ads is a constant associated with the adsorptive equilibrium constant, and n is a constant that depends on the nature of the adsorbent.

Figure 5a depicts the plot of logθ against log C derived from the aforesaid Freundlich equation.

Table 4. Adsorption parameters for the adsorption of AO on aluminum in 1.0 M of HCl for a 4 h immersion period at different temperatures.

Adsorption Isotherm	Temp. (K)	303	308	313	318	323
Freundlich Adsorption Isotherm $\log \mathsf{\theta }=\log {\mathrm{K}}_{\mathrm{ads}}+(1/\mathrm{n})\log \mathrm{C}$	R2	0.9868	0.9717	0.9836	0.9882	0.9665
	Slope	0.2113	0.3513	0.3572	0.2930	0.3207
	Intercept	−0.6584	−1.0242	−1.0660	−0.8579	−0.8509
	Kads	0.2196	0.0946	0.0859	0.1387	0.1410
	ΔGads (kJ/mol)	−30.99	−29.34	−29.57	−31.31	−31.84
	1/n	0.2113	0.3513	0.3572	0.2930	0.3207
Temkin Isotherm $\theta =-{\displaystyle \frac{1}{2a}}LnC-{\displaystyle \frac{1}{2a}}Ln{K}_{ads}$	R2	0.9853	0.9497	0.9863	0.9822	0.9748
	Slope	0.3107	0.4616	0.4271	0.4130	0.5177
	Intercept	−0.0400	−0.4478	−0.4082	−0.2914	−0.4158
	Log K	−0.1287	−0.9702	−0.9559	−0.7055	−0.8030
	K	0.7434	0.1071	0.1107	0.1970	0.1574
	a	7.41	4.99	5.39	5.58	4.45
	ΔGads (kJ/mol)	−34.06	−29.66	−30.23	−32.23	−32.14
El Awady Adsorption Isotherm $Log\left({\displaystyle \frac{\theta }{1-\theta }}\right)=Log{K}_{ads}+yLogC$	R2	0.982	0.940	0.987	0.975	0.984
	slope	0.595	0.841	0.756	0.776	1.150
	Intercept	−1.047	−1.726	−1.606	−1.494	−2.086
	1/y	1.682	1.190	1.323	1.288	0.870
	Kads	0.090	0.019	0.025	0.032	0.008
Redlich–Peterson (R-P) Isotherm $Ln\left(K_R{\displaystyle \frac{C_e}{\theta }}-1\right)=Ln\left(a_R\right)+\beta Ln(C_e)$	R2	0.9990	0.9914	0.9949	0.9979	0.9924
	slope	1.2613	1.5227	1.5424	1.4058	1.4542
	Intercept	−1.8800	−3.5225	−3.7372	−2.7402	−2.7802
	αR	0.1526	0.0295	0.0238	0.0646	0.0620
	β	1.2613	1.5227	1.5424	1.4058	1.4542
	KR	1

summarizes the equilibrium constants, K_ads, for the adsorption of AO on aluminum in an acidic solution at various temperatures obtained using the regression equation of the linear plot in Figure 5a.

According to each parameter calculated for each isotherm mentioned above, the best isotherm will be the Freundlich one, in an acidic medium. The R² values are excellent and the K_ads values correspond to the behavior of the inhibitor, which decreased when the temperature was raised from 303 K to 313 K, but the value then increased when the temperature was raised from 318 K to 323 K.

In general, values of ΔG_ads around −20 kJ mol⁻¹ or lower are consistent with electrostatic contact, while values around −40 kJ mol⁻¹ or higher are associated with chemical interactions [39]. In this study, ΔG_ads values are higher than for normal physical adsorption but lower than for typical chemical adsorption, indicating that both physical and chemical adsorption activities are likely to occur, and ΔG_ads values are negative, showing that the adsorption process is spontaneous [39]. The value of K is an approximation of the adsorption capacity, whereas 1/n is a function of adsorption strength in the adsorption process [38]. The (n⁻¹) values are less than one in the acidic medium at all temperatures. This indicates normal adsorption and a favorable sorption process [38].

The Temkin model is another well-known adsorption isotherm that has also been widely used to describe the mechanism of action of corrosion inhibitors. It offers some insights into the type of interactions occurring in the adsorbed layer, in contrast to others discussed to date. This is how the model is expressed:

$$e^{-2a\theta }=K_{ads}C$$

(7)

Based on the sign of the parameter, the molecular interaction parameter is utilized to identify whether attraction or repulsion occurs in the adsorbed layer. To obtain linear plots of θ against ln C (Figure 5b), the equation’s linearized form can be used.

$$\theta =-{\displaystyle \frac{1}{2a}}LnC-{\displaystyle \frac{1}{2a}}Ln{K}_{ads}$$

(8)

The K_ads and ΔG_ads values are evaluated and presented in Table 4. The value of K_ads describes the strength with which the inhibitor molecules bind to the metal surface.

The El Awady isotherm was used to study the strength of adsorption of AO on the surface of Al, as well as the likelihood of the creation of a multi-molecular layer of adsorption (Figure 5c):

$$Log\left({\displaystyle \frac{\theta }{1-\theta }}\right)=Log{K}_{ads}+yLogC$$

(9)

where y is the number of inhibitor molecules that can fit in a single active site, θ is the size of the surface covered, C is the concentration, and K_ads is a constant associated with the adsorptive equilibrium constant.

$$K_{ads}=K^{{\displaystyle \frac{1}{y}}}$$

(10)

If the value of 1/y is less than one, the inhibitor may create many layers on the metal surface, and if it is more than one, the inhibitor molecule will occupy multiple active sites [40]. The values of 1/y that were obtained were greater than one, indicating that each inhibitory molecule was affixed to many active sites on the Al surface. It might be because AO contains several compounds.

The Redlich–Peterson (R-P) isotherm can be applied to both homogeneous and heterogeneous systems due to its great degree of adaptability. The R-P isotherm, in contrast to the Langmuir, Freundlich, and D-R isotherms, has three parameters in a single equation [41]. The R-P isotherm has a linear form, which is:

$$Ln\left(K_R{\displaystyle \frac{C_e}{\theta }}-1\right)=Ln\left(a_R\right)+\beta Ln(C_e)$$

(11)

where β is an exponent between 0 and 1, K_R (L/g) and α_R (L/mg) ^1/β are the R-P isotherm constants, respectively. The R-P isotherm approximates Henry’s law at low concentrations and approaches the Freundlich isotherm at high concentrations. This isotherm has three parameters; hence, the use of linear regression analysis is more difficult. To apply this isotherm, the isotherm parameter K_R (K_R = 1) was varied in order to produce the highest regression, R², for the linear plot of ln[Ce/θ − 1] against lnCe. The slope and intercept of this plot are displayed in Figure 5d, and the constants α_R, β, and R were calculated. Table 4 presents the obtained regression R², α_R, and β values.

3.6. Potentiostatic Polarization Measurements

To examine the impact of the inhibitor (AO) on the corrosion behavior of the Al electrode, polarization measurements were performed. Tafel plots (potential-versus-log current) are shown in Figure 6. The cathodic and anodic Tafel curves were used to compute the corrosion current. Along the linear part of each curve, a straight line can be superimposed. The slope of the straight line fits of the linear regions of the anodic and cathodic Tafel yields the Tafel constants βa and βc, respectively, whereas the slope of the current-potential curve close to the corrosion potential determines the polarization resistance (Rp) in Ωcm².

Table 5. Electrochemical corrosion parameters of aluminum in the absence and presence of various concentration of AO in 1.0 M of HCl.

[inhibitor] (mg/L)	Ecorr (V)	Icorr (mA/cm2)	βa (mV/dec)	−βc (mV/dec)	RP (kΩcm2)	I%	Rc mm/y
Blank	−0.794	18.68	413.87	199.23	3.13	-	80.32
120	−0.798	12.27	560.16	204.40	5.30	34.31	52.76
200	−0.805	8.788	578.40	183.64	6.89	52.90	37.79
300	−0.807	6.710	645.28	198.79	9.82	64.00	28.85

summarizes other data, including the corrosion potential (E_corr), corrosion current density (I_corr), polarization resistance (Rp), and corrosion rate (Rc).

Table 6. Electrochemical impedance parameters for Al corrosion in the 1.0 M HCl solution containing various concentrations of AO.

[OA] (mol/L)	RS Ωcm2	Rct Ωcm2	n	Cdl μF·cm−2	Yo (Ω−1 sn cm−2)	I.E.
Blank	1.29	32.82	0.74	594.88	2.43 × 10−3
120	2.24	57.87	0.74	484.46	1.65 × 10−3	43.29
200	1.76	87.15	0.73	360.75	1.21 × 10−3	62.34
300	2.51	102.13	0.74	430.32	1.29 × 10−3	67.87

shows that, as the concentration of the inhibitor increases, the corrosion current density (I_corr) decreases. This clearly shows that AO stops the aluminum from rusting in acidic conditions. Both anodic and cathodic processes are suppressed, as is shown by the polarization curves for the acidic medium (Figure 6). According to the results in Table 5, the corrosion potential (E_corr) and corrosion current density (I_corr) values alter as the inhibitor concentration increases. Additionally, it was noted by [42,43] that, if an inhibitor’s corrosion potential displacement is greater than 85 mV relative to the blank’s corrosion potential, the inhibitor can be categorized as either cathodic or anodic. Aluminum’s corrosion potential (E_Corr) is little altered by the extract when compared to a blank, shifting by around (4.2–13.6) mV cathodically in an acidic solution. According to this finding, the extract decreases the anodic dissolution and delays the cathodic hydrogen evolution reaction. It also operates as a mixed-type inhibitor. By regulating both the anodic and cathodic processes, polyphenolic substances clearly prevent corrosion [44,45]. The possibility of protonated species of the extract components in acidic solutions could explain this. The protonated species are likely to compete with the hydrogen ions at the aluminum cathodic sites, which will slow down the release of hydrogen.

The electrons of aromatic rings and the lone pair electrons of oxygen atoms participate in adsorption at the anodic sites, which reduces aluminum’s anodic dissolution. The significantly reduced corrosion current (I_corr) and corrosion rate, along with an increase in polarization resistance (RP) values, provide additional proof that the effectiveness of the inhibition increased with the extract concentration and reached a maximum value at 300 ppm in the acidic medium. These findings are in line with the previously discussed weight loss measurements. The corrosion rate (Rc) is computed as follows:

$$R_c={\displaystyle \frac{0.129\times {E.Wt\times I}_{corr}}{d.A}}$$

(12)

I_corr = corrosion current (μA/cm²), E.Wt = equivalent weight of Al, d = density of Al, g/cm³, and A = area in cm².

The presence of AO significantly slows down the corrosion rate, which causes both the anodic and cathodic curves to move to lower current densities. In other words, the inhibitor (AO) in the 1.0 M HCl solution slows both the cathodic and anodic processes of aluminum electrodes.

Electrochemical impedance spectroscopy (EIS).

The Nyquist plots displayed in Figure 7 reveal semicircles for all systems over the studied frequency range. The diameter of the semicircles in the presence of AO is larger than that in the blank solution, and increases with the inhibitor concentration. This indicates that the impedance of the inhibited substrate increases with the inhibitor concentration. It is clear from the figure that there is a single semicircle that shows a single charge transfer process during dissolution. The impedance spectra were analyzed by fitting information to the equivalent circuit model (Figure 8). In the equivalent circuit model, Rs represents the solution resistance between the working and reference electrodes; R_ct is the charge transfer resistance, and it corresponds to the resistance between the metal and outer Helmholtz plane [46,47].

The impedance of a CPE is presented as:

$$\mathrm{Z}\left(\mathrm{C}\mathrm{P}\mathrm{E}\right)={Y_o}^{-1}{\left(j\omega \right)}^{-n}$$

(13)

where j is the imaginary root, ω is the angular frequency, Y_o is the magnitude, and n is the exponential term, whereas ω is the angular frequency (ω = 2πf, the frequency in Hz) and n is the phase-shift, which provdes details about the degree of surface inhomogeneity.

The impedance data listed in the Table 6 indicate that the addition of the extract increases the values of R_ct and reduces the value of the electrochemical double-layer capacitance (C_dl). The increase in the R_ct value is attributed to the formation of the protective film on the metal/solution interface [40,46]. The decrease in C_dl indicates the increase in the thickness of the electric double layer [47]. The interfacial double-layer capacitance (C_dl) values are estimated using Formula (14):

$$C_{dl}={Y_o\left(2\pi f_{max}\right)}^{n-1}$$

(14)

where f_max is the frequency at which the imaginary component of the impedance attains a maximum value (Z″_max).

This result suggests that the extract molecules inhibit the corrosion of Al by adsorption on the Al surface, thereby causing an increase in R_ct values and a decrease in C_dl values [48].

The inhibition efficiency from the impedance data was estimated by comparing the values of the charge transfer resistance in the absence and presence of the inhibitor as follows:

$$\%IE=\left[{\displaystyle \frac{R_{ct}^i-R_{ct}^o}{R_{ct}^i}}\right]\times 100$$

(15)

where the values of the charge transfer resistance with and without AO are denoted by Rⁱ_ct and R^o_ct, respectively. The magnitude and trend of the obtained values presented in Table 6 are in close agreement with those determined from gravimetric measurements and electrochemical polarization measurements.

3.7. Scanning Electron Microscope (SEM)

The surface morphology of the tested aluminum is determined by scanning electron microscopy. The surface morphology of Al exposed to 1.0 M of HCl in the absence of plant extract is shown in Figure 9B. These data point to uniformly severe corrosion and the production of adherent amorphous corrosion products in the absence of an inhibitor. Such corroded patches may have formed as a result of aggressive H⁺ assault in acidic environments, which led to the dissolution of the alumina layer.

The metal surface is only partially covered with the inhibitor, providing it with a decent amount of protection, according to the SEM results for aluminum in the presence of the inhibitor. In the presence of hydrochloric acid, it is also obvious that the surface is covered with the inhibitor (Figure 9B–D). The efficiency of AO as an inhibitor in acidic environments is demonstrated by scanning electron micrographs, which reveal that increasing the inhibitor concentration induces an increase in the quantity of an adsorbed protective coating of the inhibitor molecules on the aluminum surface.

3.8. Quantum Chemical Calculation

The Frontier molecular orbital theory (FMO) provides an explanation for the adsorption ability of molecules on metal surfaces and their chemical reactivity. The interaction between the molecules’ HOMO and LUMO levels is what primarily determines this reactivity [49]. In this study, DFT calculations were conducted for the main compounds (1, 2, 3, 4, and 5) found in the methanol extract of AO. Both gas phase and acidic solution (HCl) conditions were considered. Figure 10 illustrates the optimized geometry of these major compounds, as well as the characteristics of their molecular orbitals (HOMO and LUMO).

The reactivity of a molecule toward adsorption on an Al-metallic surface can be assessed using ∆E_gap. A decrease in ∆E_gap indicates increased reactivity and a higher inhibitor efficiency, as it enhances the stability of the formed complex between the major organic compound and the surface [50,51]. The concepts of σ and η are also introduced based on ∆E_gap. σ is closely associated with the molecule’s polarizability, where a softer molecule with a smaller ∆E_gap is more easily polarized, and thus more reactive [21,26,51]. Quantum chemical and molecular dynamics parameters, such as ∆E_gap, σ, η, X, ΔN, and ω, were calculated for the identified major compounds (1, 2, 3, 4, and 5), as presented in

Table 7. Calculated quantum parameters for main components of methanol extract of AO (X_Al = 3.209, η_Al = 2.776 [18,48]).

Quantum Parameters	1		2		3		4		5
	Gas	Acidic	Gas	Acidic	Gas	Acidic	Gas	Acidic	Gas	Acidic
EHOMO (eV)	−7.874	−7.891	−5.960	−6.086	−6.454	−6.549	−6.088	−6.113	−5.874	−6.068
ELUMO (eV)	−0.583	−0.527	−0.385	−0.434	−0.605	−0.414	−1.935	−2.082	−1.649	−1.921
∆Egap (eV)	7.291	7.364	5.575	5.652	5.849	6.135	4.153	4.031	4.225	4.147
σ	0.274	0.271	0.358	0.353	0.341	0.325	0.481	0.496	0.473	0.482
η	3.645	3.682	2.787	2.826	2.924	3.067	2.076	2.015	2.112	2.073
X	4.228	4.209	3.172	3.26	3.529	3.481	4.011	4.097	3.761	3.994
ω	1.412	1.398	1.847	1.821	1.76	1.678	2.479	2.554	2.437	2.483
ΔN	0.079	0.077	0.003	0.004	0.0281	0.023	0.082	0.0927	0.056	0.08
Dipole moment µ (Debye)	0.0117	0.015	1.447	1.91	7.376	9.658	6.021	8.317	7.421	10.833

.

The order of the ∆E_gap values for the five major components of the AO extract, both in gas and acidic solutions, follows the pattern 4 < 5 < 2 < 3 < 1. Among these compounds, Compound 4 stands out with the highest σ value and the smallest η value. Additionally, it exhibits the highest ω value compared to the other inhibitors in both gas and acidic solutions. The ω value is an indicator of the inhibitor’s electron-accepting ability from metal surfaces. In the case of Compound 4, its high ω value signifies its strong capability to accept electrons from aluminum (Al). This is further supported by its elevated ELUMO value, which reflects its high electron-accepting capacity from Al. Moreover, the ΔN values reveal that most of the electrons transferred to the Al surface originate from Compound 4 molecules. With ΔN values of 0.082 in the gas phase and 0.0927 in the presence of HCl, Compound 4 surpasses the other compounds in this regard. As a general trend, the inhibition efficiency of organic inhibitors tends to increase with a higher electron-donating ability at the metal’s surface, particularly when ΔN is less than 3.6 [52]. In this context, all the examined compounds can be classified as green inhibitors due to their ΔN values falling below 3.6. However, Compound 4 emerges as the most effective inhibitor across all phases. In summary, the major components of AO extract exhibit varying ∆E_gap values, with Compound 4 demonstrating superior characteristics, such as high σ and ω values. It is also the primary source of electron transfer to the Al surface, making it the most efficient inhibitor among the studied compounds in both gas and acidic environments.

3.9. Mechanism of Inhibition

These N, O, and S atoms and aromatic rings are found in a lot of green rust inhibitors that come from plant extracts, amino acids, or natural oils. They are often chosen because they are non-toxic and biodegradable, which means they protect well while causing little harm to the Earth [12,13,14,15,16,17,18,19,20]. The findings suggest that compounds 1, 2, 3, 4, and 5 can adhere to the surface by donating electrons from electron-rich regions to the vacant d orbitals of Al. Additionally, they can accept electrons from the Al surface, forming a back-donating bond, which depends on the optimized structure’s orientation of the inhibitor in space. Notably, Compound 4 exhibits the highest adsorption ability on the Al surface by donating the unshared pair of electrons from O atoms to the vacant d-orbitals of Al. Consequently, it is expected that the inhibition efficiency of the AO extract primarily arises from the adsorption of Compound 4 on the Al surface.

Furthermore, there are two adsorption modes for inhibitors on the Al surface in gas and acidic environments: physisorption and chemisorption. The extent of adsorption depends on the difference between the chemical potential of the Al metal and the inhibitors. The calculated ∆Gads for Compound 4 is −18.517 in the gas phase and −20.50 in the acidic medium. The ∆G_ads value is higher than that of typical physical adsorption, but lower than that of typical chemical adsorption. This indicates the likelihood of both physical and chemical adsorption occurring, and the negative ΔG_ads values confirm that the adsorption process is spontaneous. These values fall within the range of zero to −40 kJ/mol, indicating the favorable nature of the adsorption process [21,26,52].

4. Conclusions

From the current investigation, the following primary conclusions may be drawn:

• The findings of weight loss experiments and polarization techniques suggest that A. orientalis crude (AO) is useful as a green corrosion inhibitor for aluminum in an acidic medium.
• The efficiency in an acidic medium decreases with an increasing temperature, until the temperature of 40 °C is attained, and then increases until the temperature of 50 °C is reached. The efficiency increases with increasing concentrations of A. orientalis crude (AO) to reach a maximum value of 300 ppm at 50 °C.
• It was discovered that the activation energy (Ea) for the dissolution of pure aluminum in solution is higher in the absence of an inhibitor than it is in the presence of an inhibitor in an acidic medium.
• The widely used isotherm models (Freundlich, Temkin, El Awady, and Redlich–Peterson (R-P) adsorption isotherm models) were used to investigate the equilibrium isotherms for the adsorption of AO on aluminum in HCl at different temperatures.
• The free Gibbs energy (ΔG_ads) value demonstrates that the inhibitory mechanism could be attributed to comprehensive physical and chemical adsorption in an acidic medium (1.0 M of HCl), and the sign of the free energy of adsorption suggests that the process is spontaneous.
• Polarization tests revealed that the inhibitor (AO) is an anodic and cathodic mixed-type inhibitor.
• EIS plots indicated that the charge transfer resistances increase with increasing the concentration of the extract.
• The SEM findings reveal that the inhibitor (AO) partially covers the metal surface, providing it with a respectable level of protection.
• Compound 4 demonstrates the best corrosion inhibition on the Al metal surface.
• Experimental and DFT calculations show an excellent agreement, validating the accuracy of the theoretical predictions.