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Article

Environmentally Benign Grape Seed Oil for Corrosion Inhibition: Cutting-Edge Computational Modeling Techniques Revealing the Intermolecular and Intramolecular Synergistic Inhibition Action

by
Ahmed Batah
1,
Aisha H. Al-Moubaraki
2,
Ehteram A. Noor
2,
Jamilah M. Al-Ahmari
2,
Azza A. Al-Ghamdi
2,
Omar Id El Mouden
1,
Rachid Salghi
1,3,
Maryam Chafiq
4,*,
Abdelkarim Chaouiki
4,* and
Young Gun Ko
4,*
1
Laboratory of Applied Chemistry and Environment, ENSA, University Ibn Zohr, P.O. Box 1136, Agadir 80000, Morocco
2
Department of Chemistry, Faculty of Sciences—Alfaisaliah Campus, University of Jeddah, Jeddah 21589, Saudi Arabia
3
Euromed Research Center, Euromed Polytechnic School, Eco-Campus, Euromed University of Fes, Fes-Meknes Road, Fes 30030, Morocco
4
Materials Electrochemistry Laboratory, School of Materials Science and Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea
*
Authors to whom correspondence should be addressed.
Coatings 2024, 14(1), 77; https://doi.org/10.3390/coatings14010077
Submission received: 14 December 2023 / Revised: 4 January 2024 / Accepted: 4 January 2024 / Published: 5 January 2024
(This article belongs to the Section Corrosion, Wear and Erosion)
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Abstract

:
The growing interest in eco-friendly alternatives has sparked research into essential oils as corrosion inhibitors, offering an innovative approach. Investigating their unique properties, researchers aim to advance corrosion engineering for a sustainable future. Despite promising lab results, the exact mechanism of their action in corrosion engineering is not fully understood, highlighting the need for further exploration. Using computational modeling, we explored how grape seed oil (GSO) compounds interact with carbon steel (C38) surfaces, unraveling the inhibitive properties against corrosion. Employing various simulation methods, such as density functional theory (DFT), density functional-based tight-binding (DFTB), and molecular dynamics (MD), this study validates experimental findings and unveils novel insights into the underlying mechanisms of these interactions. Quantitative analysis quantifies the inter- and intramolecular synergistic effect and suggests that the LA@OA promotes the charge-transfer process. DFTB calculations reveal that the synergistic action in the parallel adsorption configuration of LA and OA molecules is sufficiently strong to form a stable adsorption layer on the Fe surface with a large negative value of Eads (6.74 eV). Experimental results demonstrated that the inhibition performance of GSO extract exhibited a notable increase with increasing concentrations, reaching a higher efficiency of 79% at 0.5 g/L of GSO. EIS results demonstrated that the existence of the GSO inhibitor film increases the resistance of the charge transfer (about 80 Ω cm2 at 0.5 g/L), indicating the superior barrier anticorrosion properties of the formed film. The theoretical results validate the exceptional anticorrosion performance and provide compelling evidence of the remarkable ability to prevent corrosion of C38 substrate. The findings offer potential pathways for the development of eco-friendly alternatives and interestingly provide a foundation understanding in the field.

1. Introduction

Experimental investigations have consistently demonstrated the remarkable adsorption properties of natural oil components towards various environmental materials. However, due to the intricate and dynamic nature of natural products and their constituents, characterizing the interaction, structure, and dynamics at the molecular scale is a challenging task that cannot be easily achieved experimentally. Hence, relying solely on laboratory research has its limitations, and, increasingly, experimentalists are seeking collaborative solutions through computational techniques. The cutting-edge advancements in computer science and technology have revolutionized the scientific landscape, enabling researchers to harness the power of computational methods to enhance their experimental findings and address some of the most pressing environmental challenges facing our understanding. These computational methods have emerged as a pivotal tool that complements the traditional laboratory approaches, paving the way for a more efficient and cost-effective approach to research [1,2]. By combining the power of computer simulations with experimental data, we can unravel the molecular domain and gain a deeper understanding of the complexities of the natural environment. This synergy between computational and experimental techniques promises to revolutionize the field of environmental research and pave the way for innovative solutions for the next generations of science. In this context, a wide range of computational models and methods are being developed and applied to investigate the geometric and electronic properties of complexes, including bonding configuration, adsorption energy, charge-transfer properties, and interaction mechanisms. The adsorption energy, in particular, is a key parameter that reflects the adsorption capacity of the organic inhibitors and is influenced by various factors, such as the properties of the compounds and metal surface, the adsorption configuration, and the interaction mechanism. Furthermore, theoretical analysis can also provide essential molecular-level insights into the adsorption mechanism beyond just adsorption energy calculations. Based on the general criterion in the corrosion field, theoretical calculations have been widely used to support the experimental data or even to correlate some molecular electronic properties with the inhibition performance of such organic inhibitor. Although there have been many studies in the corrosion field that have applied computational calculations to support the experimental data, they have all focused on developing the best formulations or correlating the molecular electronic properties with the inhibition performance of such organic inhibitors, and there has been limited research comparing the intramolecular and intermolecular synergistic inhibition effect of green corrosion inhibitors.
The need for an effective corrosion inhibitor that is both eco-friendly and efficient is more pressing than ever before. Moreover, the use of acidic solvents is prevalent in several industrial sectors for various applications, such as cleaning, rust removal, and descaling [3,4,5]. Hydrochloric acid, in particular, is one of the most widely used acidic solvents in various industries [6,7,8]. In such industries, mild steel is the most commonly used metal, owing to its excellent mechanical properties, high tensile strength, thermal stability, manufacturability, and cost-effectiveness [9,10]. However, the susceptibility of carbon steel (C38) to corrosion in acidic environments, especially in the presence of chloride ions, is a major concern. The damage caused by corrosion can result in significant safety issues, production losses, and environmental hazards [11,12,13]. It is well known that the corrosion rates are generally governed by several interrelated factors, among them the phenomenon of diffusion, where the movement of ions can either expedite or retard corrosion. Temperature, another critical parameter, consistently exerts influence; higher temperatures generally intensify corrosion reactions. In addition, the conductivity of the medium significantly impacts corrosion kinetics by influencing the ease with which electrons move. The type of ions present is a decisive factor, with specific ions either promoting or inhibiting corrosion. Furthermore, pH levels play a key role in corrosion dynamics, affecting the electrochemical balance and altering material susceptibility to degradation. Moreover, the electrochemical potential, a fundamental parameter, governs the direction and extent of corrosion reactions, influencing the overall rate. Interestingly, the interconnected nature of these factors collectively shapes the intricate process of corrosion across diverse environmental conditions [14,15,16,17]. To prevent the detrimental effects of corrosion on carbon steel in acidic environments, the use of corrosion inhibitors has been widely studied. Corrosion inhibitors work by adsorbing onto the metal surface and forming a protective layer that inhibits the corrosion reaction. A vast number of studies have been dedicated to the development of efficient corrosion inhibitors for carbon steel in acidic media. However, many of these inhibitors often suffer from drawbacks, such as toxicity, high cost, and negative environmental impact [10,18,19]. Therefore, the need for eco-friendly and efficient corrosion inhibitors for steel in acidic media is of utmost importance. To address this issue, grape seed oil is one such eco-friendly and efficient corrosion inhibitor that has shown immense promise in recent studies [20,21,22,23,24,25,26,27]. Grape seed oil (GSO) is a natural and renewable source of polyphenols, which have been found to possess excellent antioxidant properties. These properties make grape seed oil a potential candidate as a corrosion inhibitor for mild steel in acidic environments.
In this context, the potential of grape seed oil as an eco-friendly corrosion inhibitor for carbon steel in 1.0 M HCl solution is investigated. The inhibiting power of grape oil was evaluated using gravimetric analyses, electrochemical tests, surface characterization, as well as DFT simulations. The study reveals that grape oil significantly enhances the corrosion resistance of C38, acting as a mixed-type inhibitor. The Langmuir isotherm model was used to evaluate the adsorption of the corrosion inhibition of C38, and the adsorption thermodynamic parameters were computed and interpreted. Gas chromatography identified the fatty acids present in grape oil. The results indicate that GSO exhibits significant corrosion inhibition properties at all concentrations tested and can form a stable adsorption layer on the surface of C38, even at high temperatures. This work provides valuable insights into the potential of grape seed oil as a promising eco-friendly corrosion inhibitor for carbon steel in acidic environments. This research presents a comprehensive investigation into the inhibitory performance of grape seed oil as a corrosion inhibitor for carbon steel (C38) in hydrochloric acid (HCl) solutions. Moreover, the inter- and intra amolecular interactions and adsorption patterns of major compounds in grape seed oil molecules on the metal surface were studied using multiscale computational modeling. The modeling process involved the use of different simulation techniques, namely density functional theory (DFT), density functional-based tight-binding (DFTB), and molecular dynamic (MD) simulations. This was undertaken to both verify the experimental observations and to gain a better understanding of the types of interactions involved. The findings of this study not only pave the way for the development of eco-friendly and efficient corrosion inhibitors for mild steel in acidic environments but also cultivate a complete grasp of new insights into the mechanisms underlying their interactions.

2. Materials and Methods

2.1. General Computational Details

The use of theoretical chemistry provides a valuable tool for understanding the electronic properties and adsorption mechanisms underlying the inhibition of corrosion. By analyzing the properties of the organic–metal interface, including quantum chemical (QC) properties and interfacial behavior, it is possible to gain insight into the molecular mechanisms underlying corrosion inhibition. To achieve this, various levels of theory, including DFT, DFTB, and MD modeling, were utilized to study the molecule’s adsorption behavior and match it with its structural characteristics, providing a comprehensive understanding of the underlying mechanisms involved. In this vein, and to investigate the interactions between Fe2+ and grape seed extract components, the molecule complexes were modeled using Gaussian 16 W software (Rev: C.01) [28], and the interactions were analyzed by optimizing the geometries of all metal-ion–inhibitor systems in water with the B3LYP functional and 6-311++G(d,p) basis set [29,30]. The polarizable continuum model (PCM) model [30] in the Gaussian package was also implemented during the optimization process. The DFTB method was employed to investigate the interactions between inhibitors and metal at the molecular level using DFTB+ software (version 1.3). The Slater–Koster trans3d DFTB parameters, supplemented with an empirical dispersion correction, were utilized for accurate simulations. To account for Coulombic interactions between atomic partial charges, a self-consistent charge (SCC) formalism was applied, with an SCC tolerance set to 10−8, a Broyden mixing scheme, and 0.01 smearing to expedite convergence. For the bulk lattice optimization, an 8 × 8 × 8 k-points grid in the Brillouin zone was employed, while a 2 × 2 × 1 k-points grid was used for analyzing molecule–iron interactions. To represent the iron crystal, it was cleaved along its stable (110) direction, and the resulting iron layer was utilized for further investigations. MD simulations of the tested molecules were conducted using the Forcite module within the Materials Studio 2020 package. To simulate the adsorption behavior of the molecules, the Fe (110) surface was cleaved, and periodic simulation boxes were established with dimensions of 39.93 × 39.93 × 77.04 Å3. Additionally, a vacuum slab of 40 Å was included to replicate real-world conditions. In the initial MD simulation models, the molecules were randomly positioned in the solution box at a height of 10 Å from the Fe (110) surface. This deliberate placement aimed to prevent any immediate impact on the initial electron distribution of the Fe substrate. MD simulations were carried out under the NVT canonical ensemble at 298 K, employing a COMPASS force field with a simulation time of 500 ps and a step time of 1 fs. To ensure accuracy, single energy calculations based on the final equilibrium configurations were performed, with the bottom iron atoms relaxed. The entire MD calculations were performed with consistent precision, providing a thorough exploration of the system’s energy and behavior. Additional details about the computational models used in this study were constructed, building upon our previous work [31,32].

2.2. Plant Material and GSO Extraction

In August 2022, an extraction process was carried out to obtain grape seed oil (GSO) from samples collected in the Ouneine commune within the Souss-Massa region of Morocco. After meticulous cleaning to eliminate impurities, the grape seeds were dried, ground into small fragments via grinding, and then subjected to hydrodistillation using a Clevenger apparatus. This distillation process was conducted for 8 h and was repeated three times, and the average yield was calculated. The resulting GSO was weighed, stored in sealed dark vials, and kept at a temperature of 5 °C for further analysis. A voucher sample was placed in the herbarium at the Laboratory of Biotechnology, located within the National School of Applied Sciences, Ibn Zohr University, Morocco. The chemical composition of GSO was identified and quantified by gas chromatography coupled with mass spectrometry (GC/MS). A schematic of GSO extraction and the major available components in the extract are presented in Figure 1 and Table 1, respectively. The analysis of the results shows that GSO contains palmitic acid (7.33%), palmitoleic acid (0.098%), heptadecanoic acid (0.067%), stearic acid (4.52%), oleic acid (19.02%), linoleic acid (67.11%), α-linolenic acid (0.21%), arachidonic acid (0.20%), gadoleic acid (0.15%), and behenic acid (0.10%).

2.3. Weight Loss and Electrochemical Techniques

The investigation focused on assessing the corrosion rate and inhibition performance of GSO extract for C38 steel in an HCl environment, employing the weight loss method at a temperature of 298 K. The procedure involved meticulously drying and weighing the metal sample surfaces of each steel specimen after they were washed and immersed in corrosive solutions with and without the inhibitor for 24 h. The specimens were collected, cleaned, dried, and then reweighted by high-precision analytical balance to determine the corrosion rate. The electrochemical characteristics were assessed in 1 M HCl solution utilizing both potentiodynamic polarization (PDP) and electrochemical impedance tests. These evaluations were performed utilizing a three-electrode system, consisting of a working electrode with a 1 cm2 exposed area, a platinum plate functioning as the counter electrode, and Ag/AgCl serving as the reference electrode. The testing equipment employed was the Corrtest Volta lab potentiostat/galvanostat, which was manufactured in Hubei, China. All electrochemical measurements were performed in 1 M HCl solution with and without different concentrations of GSO extract. Prior to polarization measurement, the working electrode was immersed in the HCl solution for 30 min to obtain a relatively stable open-circuit potential (OCP). The potentiodynamic scans were carried out over a potential range of −0.8 to +0.2 V relative to the OCP at a scan rate of 1 mV s−1. Meanwhile, the electrochemical impedance spectroscopy (EIS) measurements were performed by applying AC voltage with frequency ranging from 0.01 to 105 Hz at an amplitude of 10 mV rms sinusoidal perturbation vs. OCP. All electrochemical experiments were repeated at least three times to ensure reproducibility.
The examination of thermodynamic activation parameters in response to temperature variations was conducted through experiments employing the PDP method. These experiments were systematically performed at different temperatures, ranging from 298 K to 328 K. Detailed information regarding the experimental apparatus can be found in our previous research [33,34,35,36].

3. Results and Discussion

3.1. Revealing Nature’s Strength: Understanding the Corrosion Inhibition Mechanisms of GSO through Computational Perspectives

To elucidate the mechanism by which GSO components act as corrosion inhibitors, the inhibitory properties of major components on corrosion were analyzed through quantum chemical calculations, providing insights into their adsorption mechanism on metal surfaces. The study found that two key molecules—oleic acid (OA) and linoleic acid (LA)—played a synergistic role in inhibiting corrosion, as shown in Figure 2. Analysis of the molecules’ frontier molecular orbital (FMO) distribution revealed that the highest occupied molecular orbital (HOMO) was mainly located on the aliphatic chain (Figure 2b), particularly the central carbon–carbon bond (C=C) while the lowest unoccupied molecular orbital (LUMO) was primarily distributed on the carboxyl group (–COOH) (Figure 2c). According to FMO theory, we can infer that the inhibitor molecule’s HOMO donates electrons to an Fe 3d empty orbit to form coordination bonds and the electron-accepting ability of –COOH groups is reflected in the location of their LUMO orbitals. These findings offer insights into the adsorption active sites of the inhibitor molecules and shed light on the mechanism underlying their corrosion inhibition properties. To gain a better understanding of how OA@LA molecules adhere to the C38 surface, total density of state (TDOS) and partial density of state (PDOS) of the OA@LA system were provided. Based on the TDOS and PDOS, the chemical reaction occurs due to interactions between LA and OA inhibitors, and the hybridization peak is mainly located within the region of 0 to 5 eV and −12 to −8 eV. Moreover, it is found that in most valence molecular orbitals, the LA and OA have comparable amounts of contribution, indicating that the synergistic between LA and OA molecules enhances the electron transfer characteristics of the system. The positive and negative regions in the OPDOS indicate the presence of bonding and antibonding molecular orbitals, respectively, within the energy range corresponding to the strong hybridization between the two inhibitor molecules.
To quantitatively discuss the inter- and intramolecular synergistic effect of OA@LA, electrostatic potential (ESP) distribution, ESP-mapped molecular vdW surface, reduced density gradient (RDG), interaction region indicator (IRI), and average local ionization energy analysis (ALIE) were conducted. Figure 3a,b clearly reveal the charge distribution and possible reaction sites. The green color indicates the positively charged regions, while the red color suggests negatively charged regions. As displayed in Figure 3a, the ESP of the molecular surface near the oxygen atoms has the most negative value (−43.28 kcal/mol, −30.85 kcal/mol), owing to the negative contribution of lone-pair electrons of –COOH groups. In addition, the carbon–carbon bonds occupy the green area with smaller ESP values, indicating that these regions are also considerable for chemical reaction. Cyan and yellow spheres correspond to the minima and maxima of ESP points, respectively. As displayed in Figure 3c,d, the value and the corresponding color reveal that the hydrogen bond (blue isosurface) and vdW interaction (green isosurface) play a decisive role in the noncovalent interaction between LA and OA molecules. Interestingly, the IRI isosurface in Figure 3e indicates that electron density in the central carbon–carbon bond region of the LA molecule is large and implies that the bonding effect is strong, suggesting the intermolecular charge transfer between the bonding and antibonding orbitals. The latter plays a dominant role in synergistic action between LA and OA molecules. These results are confirmed by the ALIE isosurface (Figure 3f), in which cyan spheres correspond to the minimum points of the ALIE on the surface of LA@OA system, which reflected the sites where the electrophilic reaction was easy to occur. The blue color highlights the regions with relatively low ALIE values, which means that these regions are more prone to the electrophilic reaction. Results from the ALIE demonstrate that the C=C group also made a greater contribution for providing lone-pair electrons.
To study the inter- and intramolecular synergistic action of LA@OA on the charge-transfer behavior between LA@OA and an Fe atom, the electronic properties of the LA@OA–Fe system were explored by DFT calculations. The optimized complex model based on a single optimized LA@OA and one Fe atom reveals that LA and OA molecules are positioned in a parallel arrangement and effectively coordinate with the Fe atom (Figure 4a). The synergistic action of LA@OA with metal can be explained on the basis of the distribution of MO energy levels and inter-–intrafragment interactions. The low-lying HOMO orbitals are formed by combining the orbitals of the metal and the LA@OA in a specific way, which results in a derivative of their combination (Figure 4b). It is clear from Figure 4c that the energy gap is significantly decreased from 5.83 eV to 2.88 eV, which indicates that the LA@OA promotes charge transfer to form stable complexes with the Fe surface. Notably, the synergistic effects of δginter (mainly with COOH groups) and δgintra (tail of the molecule) made these interactions strong to form stable complexes and strong interactions with the Fe atom (Figure 4d–f).
To further clarify the synergism action and the donor–acceptor relationship in the LA@OA system, Hirshfeld surface (HS) and fingerprint plot analyses were performed by evaluating the electron density with promolecular approximation, as shown in Figure 5. The isosurface in Figure 5a,b displayed the HS of the LA and OA fragments, and dnorm is the mapped function. The red parts exhibit a small dnorm value and indicate close proximity, which is a result of H-bond interaction. Additionally, in the fingerprint plot (Figure 5c,d), only one spike at the bottom left region for both systems (i.e., LA onto OA and OA onto LA) was detected. The results indicate that the LA molecule works as the hydrogen bond acceptor because the value of di is larger than de, while the OA molecule behaves as the H-bond donor due to the smaller di value. These findings confirm again the strong donor–acceptor behavior as well as the inter-/intramolecular synergistic effect between LA and OA molecules.
In order to determine the interfacial mechanism and adsorption configuration of LA@OA, first-principles DFT calculations were conducted. Two initial configurations of LA@OA were considered, and their corresponding stable configurations are displayed in Figure 6. The results show that LA and OA molecules in their parallel and perpendicular patterns have a tendency to migrate toward the Fe interface and interact with it via COOH groups. Compared with initial configurations (inset), the side and top views of both geometries clearly indicate that the adsorption of LA and OA molecules is through the bonding of O atoms on the Fe surface. As expected, the parallel configuration is energetically more favorable, suggesting the formation of a more stable structure which can maximize the surface coverage of Fe (Figure 6a). Further, the significant alteration in the geometry resulting from vertical adsorption is likely due to the inclination of the molecules to assume an angled position as compared to the initial configuration (Figure 6b). The adsorption energy (Eads) for each optimized model was calculated, and the results reveal that the inter- and intramolecular synergistic action in the parallel adsorption configuration of LA and OA molecules is sufficiently strong to form uniform and stable adsorption layers on the Fe surface with a large negative value of Eads (−6.74 eV). Owing to the synergistic action of LA@OA, the adsorption of LA and OA molecules in their vertical geometry retains strong interaction with Eads = −6.10 eV, which demonstrates the adsorption capability of LA and OA molecules. This is also confirmed by the bond lengths of O–Fe in both parallel and perpendicular configurations which are within the range of 2.01–2.31 Å. These values are close to the sum of the covalent radii of O and Fe (rcov (O–Fe) = 0.69 Å + 1.32 Å = 2.01 Å).
We can infer that the adsorption ability of LA and OA molecules on the Fe surface is mainly due to the synergistic effect of LA@OA, which greatly enhances the electron transfer and bonding interaction and thereby the formation of stable inhibitor films with exceptional corrosion protection. The synergistic action and adsorption behavior of LA and OA were also simulated by MD simulations. Figure 7 displays the adsorption behavior of LA and OA molecules during a simulation time of 500 ps. Comparatively, the behavior of LA and OA is changed after 100 ps of MD, and the inhibitor molecules could adsorb on the Fe surface via carboxylic acid as the main active groups to form coordinate bonds (Figure 7b). After 250 ps, it is observed that LA and OA molecules are oriented parallel to the Fe (110) plane surface, representing the high ability of these molecules to adsorb on the Fe surface via parallel configuration (Figure 7c). The final configuration after 500 ps (Figure 7d) shows that LA and OA are more attracted to the metal surface and that the biggest change in the adsorption behavior of LA and OA molecules caused by their interaction with the Fe surface is affected by the synergistic action of LA@OA, which helps to enhance the surface coverage and, therefore, strong inter- and intramolecular interactions [37,38,39,40,41].

3.2. Anticorrosion Performance

Experimental investigations were carried out to examine the impact of inhibitor concentration on the efficacy of corrosion rate inhibition at 298 K in the absence and presence of the GSO inhibitor. The results revealed that with increasing inhibitor concentration, the inhibition efficiency improved, indicating that at higher concentrations, the inhibitor formed a more compact layer on the C38 surface due to better adhesion of inhibitor molecules to the metallic surface. Additionally, the results depicted in Figure 8a demonstrate that an increase in inhibitor concentration resulted in a decrease in the corrosion rate values due to an increase in the covering surface area on the metal surface [42,43,44]. These outcomes are attributed to the accumulation and adsorption activities of the GSO molecules on the metallic surface [45,46,47,48,49]. Therefore, it can be hypothesized that an increase in inhibitor concentration leads to a significant improvement in adsorption up to the optimal concentration of 0.5 g/L, which results in complete coverage of all active zones on the surface exposed to the corrosive medium. To comprehend the protective mechanism of the GSO inhibitor, a polarization test was carried out (depicted in Figure 8b). The outcomes showed that the protective mechanism remained consistent across different inhibitor concentrations. From PDP results, compared with the blank sample, the cathode slope of the solution with the GSO extract has no obvious change, and the anode slope has obvious change, indicating that the GSO extract can alter the anodic dissolution of C38 steel. At the same time, the similarity in shape in both uninhibited and inhibited solutions indicates that the C38 steel corrosion reaction mechanism does not change after the addition of GSO extract, which is well-observed from the parallel form of cathodic lines. It is crucial to recognize that multiple factors can influence electrode polarization. When corrosion inhibitors are introduced into the solution, their molecules tend to adsorb onto the surface of the carbon steel, forming a protective film. This adsorption alters the properties of the interface between the solution and the carbon steel, thereby influencing the observed changes in the Tafel parameters [50,51]. On the other hand, in line with findings from several investigations, the deviation observed in the corrosion potential (Ecorr) towards anodic or cathodic potentials serves as a crucial parameter for characterizing the type of tested inhibitor. Generally, a shift surpassing 85 mV classifies the compound as either an anodic or cathodic inhibitor, while a shift below 85 mV suggests a predominantly mixed-type inhibition mechanism. Upon meticulous examination of the Ecorr values presented in Table 2, it is apparent that across all tested concentrations relative to the blank test, the displacement remains consistently below 85 mV. This consistent trend indicates that GSO extract primarily functions as a mixed-type inhibitor. Mixed-type inhibitors reduce the corrosion rate of both anodic and cathodic reactions without inducing changes to the corrosion mechanism. Additionally, the computed electrochemical parameters (outlined in Table 2) revealed that an increase in GSO extract concentration resulted in the development of a superior protective film and a reduction in the corrosion rate. At the same time, the inhibition efficiency of the extract inhibitor increases with the increase in GSO concentration. The effect of different concentrations of GSO on the characteristics of the anticorrosion barrier formed on the C38 substrate was evaluated using the EIS method (Figure 8c–e). To decouple the various electrochemical processes occurring at the metal–solution interface, each impedance response was fitted, and the fitting process considered both the physical and chemical conditions of the system. The impedance responses were interpreted using a circuit model, as illustrated in Figure 8c (inset). In this model, the fitting parameters Rs and Rct represent the solution resistance and charge-transfer resistance, respectively. Additionally, the model incorporates the CPE, which signifies the double-layer capacitance and is defined by its components, namely admittance (Q) and exponent (n). Introducing the CPE in lieu of a purely capacitive element played a vital role in addressing the heterogeneity inherent in the working electrode. Considering the real-world corrosion process in practical environments, the significance of capacitance was deemed minimal, particularly because corrosion typically does not involve an external source of electrical current. Consequently, when characterizing the corrosion properties of the protective layer, the effectiveness of the extract in inhibiting corrosion could be assessed through the evaluation of the charge-transfer resistance parameter. The Nyquist and Bode diagrams revealed that the inhibitory effect was significantly enhanced as the concentration of the inhibitor increased, reaching an optimal concentration of 0.5 g/L. These findings were further corroborated by the fitting of the EIS data presented in Table 3. The impedance responses for all systems and concentrations consisted primarily of one capacitive loop and one inductive loop at high and low frequencies, respectively. The results suggested that all the systems with the inhibitor exhibited similar behavior, indicating a comparable corrosion inhibition effect. However, at the optimal concentration, larger capacitive loops were observed, indicating superior performance against corrosion of the C38 substrate (Table 3). Therefore, it can be concluded that the C38 surface was more thoroughly covered by adsorbed layers of GSO at an optimal concentration of 0.5 g/L when displacement reactions occurred between the metal and inhibitor. This efficient blocking of charge and mass transfer resulted in the reduction in the corrosion of the metal alloy [52]. In addition, the effectiveness of corrosion inhibitor on a metal substrate was examined through adsorption isotherms, which can reveal how inhibitor particles directly or indirectly adsorb to the metal surface and reduce contact between aggressive species and the metal. Various models, including the Langmuir, Temkin, and Freundlich, were assessed to determine the most appropriate adsorption isotherm. Results showed that the Langmuir model was the most suitable, as evidenced by a slope and regression coefficient nearing unity (Figure 8f). By analyzing the Kads values (Table 4), it was concluded that the GSO components had the strongest affinity for adsorbing onto the C38 surface. A higher Kads value indicated a more robust and effective adsorbed layer on the metal surface, resulting in superior surface coverage [50,53,54,55].
The inhibitory effect of natural GSO on steel corrosion at different inhibitor concentrations was investigated over a temperature range of 298 to 328 K. Polarization curves of C38 were obtained in a 1 M HCl medium before and after adding GSO at a concentration of 0.5 g/L, following a 30 min immersion time. Figure 9a,b show the effect of temperature on the polarization curves of steel without and with the optimal concentration of GSO, respectively. Table 5 presents the corrosion current densities (Icorr), steel corrosion potentials (Ecorr), Tafel slopes, and inhibitor efficiency as a function of temperature. The results indicate that temperature has no significant effect on the overall shape of the polarization curve’s cathodic and anodic branches and only slightly alters the steel’s corrosion potential (Ecorr) in 1 M HCl, both with and without the inhibitor. However, current densities increase as temperature increases. The cathodic curves are parallel, indicating the pure activation mechanism of H+ ion reduction on the steel surface throughout the temperature range [56,57,58]. Furthermore, the increase in corrosion current with the temperature in the presence of the inhibitor is much lower than in the control, confirming the strength of GSO as an inhibitor over the studied temperature range. From Figure 9c,d, the calculated value of Ea is higher than the value obtained without inhibitor (Table 6), suggesting that GSO has a potent inhibitory effect by raising the energy barrier for the corrosion process. The positive signs of the enthalpies (ΔH*) reflect the endothermic nature of the steel dissolution process [59,60]. Additionally, it is observed that the activation energy and activation enthalpy vary depending on the inhibitor concentration, indicating that the dissolution reaction will be further blocked on the metallic surface sites [61,62,63]. Moreover, the high negative values of ΔS* during the activation process can be attributed to the formation of an activated complex represented by association or fixation, resulting in losses in the degrees of freedom of the system during the inhibition process [64,65,66].

3.3. Microstructural Morphology

The effects of the GSO inhibitor on the corrosion behavior of C38 steel in 1 M hydrochloric acid were investigated by examining the surface of the steel after 24 h of immersion in the acid. The metallic surface was observed under two conditions: in the presence and absence of the GSO inhibitor. Without the GSO inhibitor, significant surface damage was observed, with cracks and micropores indicating corrosion pitting occurring over most of the surface at a uniform rate, as seen in Figure 10a. In contrast, the surface of the steel in the presence of 0.5 g/L of GSO, as shown in Figure 10b, appeared smooth, suggesting that the GSO inhibitor effectively prevented the corrosion of the C38 steel. The inhibitory effect of GSO can be attributed to its ability to limit the access of the corrosive electrolyte to the surface of the steel, thereby reducing the rate of corrosion. The mechanism by which GSO inhibits the corrosion of C38 steel can be attributed to the formation of a protective layer of adsorbed molecules on the surface of the steel. This layer acts as a barrier preventing the corrosive electrolyte from reaching the underlying steel and causing corrosion. The protective layer is formed by the adsorption of the molecules of grape seed oil onto the surface of the steel, and this adsorption is facilitated by the presence of the acid, confirming its inhibitory effect. Moreover, and in order to investigate the impact of an organic layer on the chemical composition of the surface of C38 steel, EDS (energy-dispersive X-ray spectroscopy) analysis was conducted on both protected and unprotected samples, and the results are presented in Figure 10c,d. The EDS analysis of the unprotected sample, shown in Figure 10c, revealed the elemental composition of the surface of the steel, with no evidence of any organic layer. However, in the protected sample (Figure 10d), the presence of an organic layer was confirmed, and differences were observed in the elemental composition of this layer. Specifically, the carbon peak in the EDS analysis corresponds to the carbon atoms of the major components of the GSO extract, indicating that the organic layer was formed from the GSO inhibitor. These results suggest that the formation of a stable organic layer on the surface of C38 steel can effectively prevent corrosion phenomena [67,68,69]. The proposed mechanism for the inhibitory effect of GSO on C38 steel corrosion involves the formation of a protective organic layer on the metal surface (Figure 10e). This layer acts as a physical barrier limiting the access of the corrosive electrolyte and preventing electrochemical reactions. The GSO extract’s active sites as well as their functional groups contribute to the formation of the organic layer, which stabilizes the surface against corrosion.

4. Conclusions

In summary, this study focused on understanding the interaction between GSO extract and the C38 surface, with the goal of developing an organic layer that can protect metallic materials from corrosion in harsh environments. Comprehensive theoretical prediction assessments were conducted before the experimental studies, indicating that specific molecules were anticipated to exhibit a robust affinity for the C38 surface due to their exceptional electronic and structural properties. From this perspective, electrochemical and characterization techniques were employed to examine the corrosion inhibition performance of GSO extract in HCl solution. Theoretical findings indicated that both LA (linoleic acid) and OA (oleic acid) molecules, whether in parallel or perpendicular arrangements, exhibit a propensity to interact with an Fe surface. This interaction is particularly facilitated through the carboxyl groups, and, interestingly, the parallel orientation is energetically favored, as evidenced by DFTB calculations. Owing to the excellent donor–acceptor characteristics exhibited by both molecules and the synergistic effects resulting from inter- and intramolecular interactions, it is conceivable that strong chemical bonds may form between LA@OA molecules and Fe atoms, characterized by a notably higher adsorption energy value (−6.74 eV). The experimental results clearly indicate that the inhibition efficiency of GSO extract depends on its concentration. Notably, the findings demonstrate a remarkable inhibition performance, reaching approximately 79% at a concentration of 0.5 g/L against C38 corrosion. Electrochemical analyses further revealed that when compared to the blank solution, GSO extract substantially enhanced corrosion resistance while reducing corrosion current density. The adsorption behavior aligns with the Langmuir isotherm model, supporting a mode of mixed physical and chemical interactions. Through meticulous control of concentration and temperature parameters, it is observed that the adsorption capability of LA and OA molecules on the Fe surface is predominantly attributed to the synergistic influence of LA@OA. This synergistic effect significantly amplifies electron transfer and bonding interactions, consequently leading to the formation of stable inhibitor films that offer exceptional corrosion protection. This was verified by the surface analyses. By elucidating the interfacial mechanism of LA@OA molecules, this study has revealed the importance of the structural design of corrosion inhibitors in effectively facilitating the corrosion inhibition process.

Author Contributions

A.B.: investigation, formal analysis, writing–original draft; A.H.A.-M.: formal analysis, funding acquisition, data curation; E.A.N.: formal analysis, data curation; J.M.A.-A.: formal analysis, funding acquisition; A.A.A.-G.: data curation, funding acquisition; O.I.E.M.: formal analysis; R.S.: formal analysis; M.C.: conceptualization, methodology, investigation, writing–original draft, writing—review and editing; A.C.: conceptualization, investigation, methodology, writing–original draft, writing—review and editing, supervision; Y.G.K.: funding acquisition, writing–review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Fundamental-Core National Project of the National Research Foundation (NRF) funded by the Ministry of Science and ICT, Republic of Korea (2022R1F1A1072739).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All results of this study are included in the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Schematic of GSO extraction and the major available components in the extract. (a) Schematic illustration of the extraction process. (b) Structure of a ripe grape berry. (c) Electrostatic potential distribution on the whole molecular surface of major components in the extract.
Figure 1. Schematic of GSO extraction and the major available components in the extract. (a) Schematic illustration of the extraction process. (b) Structure of a ripe grape berry. (c) Electrostatic potential distribution on the whole molecular surface of major components in the extract.
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Figure 2. Electronic and physicochemical properties of LA@OA system based on FMO density distributions. (a) Optimized structure; (b) HOMO; (c) LUMO; (d) TDOS, PDOS, and OPDOS of the LA@OA system.
Figure 2. Electronic and physicochemical properties of LA@OA system based on FMO density distributions. (a) Optimized structure; (b) HOMO; (c) LUMO; (d) TDOS, PDOS, and OPDOS of the LA@OA system.
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Figure 3. (a) Electrostatic potential (ESP); (b) ESP statistical distribution on LA@OA molecular surface area with isosurface = 0.002 (surface local maxima and minima of ESP are marked with yellow and cyan spheres, respectively). The weak interaction regions characterized by (c) RDG isosurface; (d) scatter plot of RDG versus electron density (ρ) multiplied by the sign of the second Hessian eigenvalue (λ2); (e) interaction region indicator (isosurface = 2); (f) ALIE isosurface and the minimum points distribution on LA@OA molecular area (unit: kcal/mol).
Figure 3. (a) Electrostatic potential (ESP); (b) ESP statistical distribution on LA@OA molecular surface area with isosurface = 0.002 (surface local maxima and minima of ESP are marked with yellow and cyan spheres, respectively). The weak interaction regions characterized by (c) RDG isosurface; (d) scatter plot of RDG versus electron density (ρ) multiplied by the sign of the second Hessian eigenvalue (λ2); (e) interaction region indicator (isosurface = 2); (f) ALIE isosurface and the minimum points distribution on LA@OA molecular area (unit: kcal/mol).
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Figure 4. (a–c) The electronic properties and charge-transfer behavior of LA@OA interacted with Fe and its molecular orbital interactions. (d,e) IGM analysis and (f) scatter plots of RDG showing the inter- and intramolecular interaction.
Figure 4. (a–c) The electronic properties and charge-transfer behavior of LA@OA interacted with Fe and its molecular orbital interactions. (d,e) IGM analysis and (f) scatter plots of RDG showing the inter- and intramolecular interaction.
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Figure 5. The Hirshfeld surface analysis and corresponding fingerprint plot: (a,c) LA onto OA; (b,d) OA onto LA.
Figure 5. The Hirshfeld surface analysis and corresponding fingerprint plot: (a,c) LA onto OA; (b,d) OA onto LA.
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Figure 6. The side and top views of the final configuration for a combination of LA and OA molecules adsorbing on Fe(110) surface. (a) Parallel and (b) perpendicular adsorption patterns. The inset structure is the initial structure before adsorption.
Figure 6. The side and top views of the final configuration for a combination of LA and OA molecules adsorbing on Fe(110) surface. (a) Parallel and (b) perpendicular adsorption patterns. The inset structure is the initial structure before adsorption.
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Figure 7. Adsorption behavior of LA and OA molecules simulated by MD simulations. Geometrical and configurational changes after (a) 20 ps, (b) 100 ps, (c) 250 ps, and (d) 500 ps.
Figure 7. Adsorption behavior of LA and OA molecules simulated by MD simulations. Geometrical and configurational changes after (a) 20 ps, (b) 100 ps, (c) 250 ps, and (d) 500 ps.
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Figure 8. Anticorrosion performance results of GSO. (a) Variation of CR and inhibition performance with the concentration of GSO inhibitor in 1.0 M HCl. (b) Polarization curves of C38 with and without GSO at 298 K. (c–e) Nyquist (inset: equivalent electrical circuit employed for fitting EIS data), Bode impedance modulus, and phase angle plots for C38 corrosion, respectively. (f) Langmuir adsorption isotherm of GSO on the C38 surface at 298 K.
Figure 8. Anticorrosion performance results of GSO. (a) Variation of CR and inhibition performance with the concentration of GSO inhibitor in 1.0 M HCl. (b) Polarization curves of C38 with and without GSO at 298 K. (c–e) Nyquist (inset: equivalent electrical circuit employed for fitting EIS data), Bode impedance modulus, and phase angle plots for C38 corrosion, respectively. (f) Langmuir adsorption isotherm of GSO on the C38 surface at 298 K.
Coatings 14 00077 g008
Coatings 14 00077 g009
Figure 9. PDP curves for C38 (a) without and (b) with GSO at different temperatures. Dependence of (c) ln Icorr and (d) ln (Icorr/T) with the temperature in the absence and presence of GSO extract.
Figure 9. PDP curves for C38 (a) without and (b) with GSO at different temperatures. Dependence of (c) ln Icorr and (d) ln (Icorr/T) with the temperature in the absence and presence of GSO extract.
Coatings 14 00077 g009
Coatings 14 00077 g010
Figure 10. SEM images and their corresponding EDS compositional results for (a,c) bare C38 surface immersed in 1 M HCl alone and (b,d) after 24 h of immersion in 1 M HCl + 0.5 g/L GSO. (e) The proposed anticorrosive mechanism of GSO inhibitor on C38 surface.
Figure 10. SEM images and their corresponding EDS compositional results for (a,c) bare C38 surface immersed in 1 M HCl alone and (b,d) after 24 h of immersion in 1 M HCl + 0.5 g/L GSO. (e) The proposed anticorrosive mechanism of GSO inhibitor on C38 surface.
Coatings 14 00077 g010
Table 1. Lipid composition of GSO.
Table 1. Lipid composition of GSO.
Name Composition (%)
PA7.33 ± 0.02
PAA0.098 ± 0.05
HA0.06 ± 0.01
SA4.52 ± 0.05
OA19.02 ± 0.10
LA67.11 ± 0.12
α-LA0.21 ± 0.02
AC0.19 ± 0.02
GA0.15 ± 0.02
BA0.10 ± 0.03
The data presented in this study are reported as the mean value with the standard deviation indicated. PA: palmitic acid; PAA: palmitoleic acid; HA: heptadecanoic acid; SA: stearic acid. OA: oleic acid; LA: linoleic acid; α-LA: α-linolenic acid; AC: arachidonic acid; GA: gadoleic acid; BA: behenic acid.
Table 2. Polarization parameters of C38 in the presence of varying concentrations of GSO at 298 K.
Table 2. Polarization parameters of C38 in the presence of varying concentrations of GSO at 298 K.
InhibitorConcentration
(g/L)		−Ecorr
(mV/SCE)		−βc
(mV dec−1)		βa
(mV dec−1)		Icorr
(μA cm−2)		IEI
(%)
1 M HCl-463.1 ± 0.5168.2 ± 0.5123.4 ± 0.6636.1 ± 0.4-
GSO0.5 465.2 ± 0.2191.7 ± 0.276.3 ± 0.7147.1 ± 0.376.98
0.3 464.1 ± 0.1196.8 ± 0.673.8 ± 0.2238.2 ± 0.762.67
0.1 470.0 ± 0.3195.4 ± 0.194.4 ± 0.4287.0 ± 0.554.97
0.05 470.5 ± 0.2194.6 ± 0.880.1 ± 0.3328.1 ± 0.248.42
Table 3. The EIS parameters estimated from the impedance spectra of C38 with and without GSO at 298 K.
Table 3. The EIS parameters estimated from the impedance spectra of C38 with and without GSO at 298 K.
InhibitorConcentration (g/L)Rct (Ω cm2)Cdl (μF/cm2)Ect (%)
1 M HCl-18.1 ± 1.5221.16 ± 2.05-
GSO0.5 80.2 ± 0.6132.69 ± 1.1577.5
0.3 50.1 ± 0.8212.31 ± 1.9864.0
0.1 40.2 ± 0.7265.39 ± 0.8755.1
0.05 35.1 ± 0.9303.30 ± 1.2648.57
Table 4. Linear regression parameters obtained from fitted line of Figure 8f.
Table 4. Linear regression parameters obtained from fitted line of Figure 8f.
InhibitorKads (L/g)R2 Δ G ads ° (kJ/mol)
GSO2.160.99042−11.85
Table 5. Temperature effect on electrochemical parameters.
Table 5. Temperature effect on electrochemical parameters.
MediumTemperature
(K)		−Ecorr (mV/SCE)Icorr (µA/cm2)−βc
(mV/dec) 		EI
(%)
1 M HCl298 ± 1463.1 ± 0.5636.1 ± 0.4168.2 ± 0.5-
308 ± 1467.2 ± 0.2896.4 ± 0.2165.1 ± 0.1-
318 ± 1470.1 ± 0.63428.1 ± 0.7167.4 ± 0.6-
328 ± 1477.0 ± 0.86720.2 ± 0.7164.3 ± 0.8-
1 M HCl + GSO298 ± 1465.2 ± 0.2147.1 ± 0.3191.7 ± 0.276.98
308 ± 1477.4 ± 0.3221.3 ± 0.3189.1 ± 0.475.33
318 ± 1493.6 ± 0.5798.5 ± 0.6188.5 ± 0.576.72
328 ± 1504.3 ± 0.61613.6 ± 0.7190.8 ± 0.675.99
Table 6. Thermodynamic parameters for C38 with and without GSO.
Table 6. Thermodynamic parameters for C38 with and without GSO.
Medium∆H* (kJ/mol)∆S* (J/mol K)Ea (kJ/mol)
1 M HCl33.79−191.5336.38
1 M HCl + GSO34.64−200.8737.24
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Batah, A.; Al-Moubaraki, A.H.; Noor, E.A.; Al-Ahmari, J.M.; Al-Ghamdi, A.A.; Id El Mouden, O.; Salghi, R.; Chafiq, M.; Chaouiki, A.; Ko, Y.G. Environmentally Benign Grape Seed Oil for Corrosion Inhibition: Cutting-Edge Computational Modeling Techniques Revealing the Intermolecular and Intramolecular Synergistic Inhibition Action. Coatings 2024, 14, 77. https://doi.org/10.3390/coatings14010077

AMA Style

Batah A, Al-Moubaraki AH, Noor EA, Al-Ahmari JM, Al-Ghamdi AA, Id El Mouden O, Salghi R, Chafiq M, Chaouiki A, Ko YG. Environmentally Benign Grape Seed Oil for Corrosion Inhibition: Cutting-Edge Computational Modeling Techniques Revealing the Intermolecular and Intramolecular Synergistic Inhibition Action. Coatings. 2024; 14(1):77. https://doi.org/10.3390/coatings14010077

Chicago/Turabian Style

Batah, Ahmed, Aisha H. Al-Moubaraki, Ehteram A. Noor, Jamilah M. Al-Ahmari, Azza A. Al-Ghamdi, Omar Id El Mouden, Rachid Salghi, Maryam Chafiq, Abdelkarim Chaouiki, and Young Gun Ko. 2024. "Environmentally Benign Grape Seed Oil for Corrosion Inhibition: Cutting-Edge Computational Modeling Techniques Revealing the Intermolecular and Intramolecular Synergistic Inhibition Action" Coatings 14, no. 1: 77. https://doi.org/10.3390/coatings14010077

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