Corrosion Science 80 (2014) 482–486

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Corrosion Science

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Insights into surface–adsorbate interactions in corrosion inhibitionprocesses at the molecular level

0010-938X/$ - see front matter � 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.corsci.2013.11.062

⇑ Corresponding author. Tel.: +90 322 3386084x2789; fax: +90 322 3386830.E-mail address: ozcanm@cu.edu.tr (M. Özcan).

Muzaffer Özcan a,⇑, Daniele Toffoli b, Hande Üstünel c, _Ilyas Dehri d

a Department of Science and Technology Education, Çukurova University, 01330 Adana, Turkeyb Department of Chemistry, Middle East Technical University, 06531 Ankara, Turkeyc Department of Physics, Middle East Technical University, 06531 Ankara, Turkeyd Department of Chemistry, Çukurova University, 01330 Adana, Turkey

a r t i c l e i n f o a b s t r a c t

Article history:Received 12 August 2013Accepted 30 November 2013Available online 9 December 2013

Keywords:B. EISB. Modeling studiesC. Acid corrosionC. Acid inhibition

2-((3-Methylpyridine-2-imino)methyl)phenol (MPIMP) was investigated as a potential corrosion inhibi-tor for mild steel in 0.5 M HCl solution using impedance spectroscopy (IS). Changes in impedance param-eters indicated that adsorption of MPIMP occurred on the mild steel surface. Three stable adsorptionconfigurations for MPIMP on the Fe(110) surface were identified as a result of geometry optimizationstarting from several adsorption geometries using density functional theory (DFT). Involvement of thedelocalized p-electrons of the aromatic rings in the interaction provides extra stabilization to the flatadsorption configurations.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Acid solutions are widely used in various areas of industry. Met-als are vulnerable to corrosion in acidic environments; therefore,the protection of metals against corrosion in such environmentsis important. Although several methods of protection exist, theuse of inhibitors is the most practical. Inhibitors are required tobe not only effective but also economical. For this purpose,imine-group-containing compounds, which can be synthesizedfrom cheap starting materials, are often used in corrosion inhibitorresearch [1–6]. The interest in compounds that contain S, N, and Oatoms in aromatic rings is also a consequence of efficient protocolsthat assure high purity by minimizing the formation of byproducts.

Clarification of the interaction between inhibitor molecules andsurface metal atoms at the molecular level is important in terms offinding new and effective inhibitors. Theoretical approaches, to-gether with experimental ones, are effective in analyzing the nat-ure and the strength of this interaction; however, a large portionof the published studies are focused on isolated inhibitor mole-cules and neglect the effects of surface metal atoms [7–16]. Mosttheoretical works to date make use of the electronic properties ofthe gas-phase molecule to explain the inhibition efficiency of theadsorbed species, while fewer, more elaborate computational stud-

ies attempted at an accurate description of the inhibitor–surfaceinteraction. Earlier works by Jiang and Adams [17], and Jiang,Adams, and Sun [18] used plane-wave density functional theory(DFT) and the generalized-gradient approximation (GGA), to char-acterize the interaction of benzotriazole (BTA) and the Cu(111)and Cu2O (111) surfaces, respectively. More recent DFT studieson similar systems were performed by Kokalj et al. [19,20], whilethe interaction of benzimidazole (BIMD) and benzotriazole (BTA)with the Fe(110), Cu(111), and Al(111) surfaces was the subjectof the study by Kovacevic et al. [21]. Two very recent studies ofthe interaction of imidazole (IMD) and the Fe(100) surface byMendes et al. [22] and by Kokalj [23] are worth mentioning. It isevident that the use of a realistic model that closely representsthe real system effectively promotes both the theoretical investiga-tion and synthesis of better corrosion inhibitors.

The objective of this paper is to first investigate the effect of2-((3-methylpyridine-2-imino)methyl)phenol (MPIMP) on mildsteel corrosion in a 0.5 M HCl solution using impedance spectros-copy (IS) and to subsequently clarify its interaction with theFe(110) surface at the molecular level using density functionaltheory (DFT). The chemical structure of MPIMP is shown inFig. 1.

The plan of the paper is as follows. The experimental and com-putational details are reported in Sections 2 and 3, respectively. Adiscussion of the results is reported in Section 4, while conclusionsare reported in the final section, Section 5.

Fig. 1. Chemical structure of 2-((3-methylpyridine-2-imino)methyl)phenol(MPIMP).

M. Özcan et al. / Corrosion Science 80 (2014) 482–486 483

2. Experimental details

The effect of 2-((3-methylpyridine-2-imino)methyl)phenol(MPIMP) on mild steel corrosion in a 0.5 M HCl solution was stud-ied with impedance spectroscopy (IS).

The working mild steel electrode was in the form of a cylindri-cal rod having the composition in wt.%: C, 0.17; Mn, 1.40; S, 0.045;P, 0.045; N, 0.009 and the remainder iron. Its surface area subjectedto the test solution was 0.5 cm2 while the rest of it was placed in apolyester resin. The test solution was 0.5 M HCl solution and vari-ous concentrations (ranging from 0.1 to 5 mM) of MPIMP werestudied. Prior to each measurement, the working electrode waspretreated with a successive grade emery papers up to 1200, de-greased in acetone, rinsed with distilled water, dried with soft pa-per, and then directly put in an open glass cell containing 100 mLof solution. All experiments were carried out at 25 ± 1 �C in stag-nant solutions after 0.5 h of exposure.

The impedance studies were carried out in a three electrode cellin which the reference electrode was an Ag/AgCl (3 M KCl) and thecounter electrode was a platinum sheet. Response of the systemsto ac excitation, 5 mV peak to peak, in a frequency range of100 kHz–10 mHz was measured instantaneously with CHI 604BAC electrochemical analyzer at open circuit potential, Eocp, of theworking electrode.

The construction of adsorption isotherm from IS results andextracting the standard free energy of adsorption (DG�ads) valuewas realized as described elsewhere [24].

R1 CPE1

R2

Fig. 2. Complex plane plots of the mild steel/0.5 M HCl solution + X mM MPIMPsystem. R1 is the solution resistance, CPE1 is the constant phase element, whereasR2 denotes the polarization resistance.

3. Theoretical details

The calculations were performed using plane-wave pseudopo-tential density functional theory [25,26] with the gradient-cor-rected approximation (GGA). The Perdew–Becke–Ernzerhof (PBE)exchange–correlation functional [27] as implemented in the Quan-tum Espresso suite of codes [28] was used in all calculations andthe open-source program XCrysden [29] was used for visualizationand to produce the figures. For both the isolated molecules and theslab geometries the plane-wave basis is characterized by a kineticenergy cut-off of 35 Ry and a corresponding cut-off of 350 Ry hasbeen used for the charge density. The optimized geometry of thegas-phase inhibitor molecule agrees very well with preliminary re-sults of quantum mechanical calculations performed by employingthe B3LYP/6-311++G(d,p) method and the Gaussian 09 suite of pro-grams [30].

As a preliminary study to test the method, the lattice constantof bulk bcc Fe was calculated to be 2.82 Å, in good agreement withprevious theoretical and experimental work [31]. At this latticeconstant, the total magnetization was found to be 2.24 lB per atomonce again in good agreement with previous work [32]. Asymmet-ric 1 � 1 slabs of four layers were used to model the Fe(110) sur-face. The coordinates of the atoms of the bottom layer were fixed to

the bulk positions with a vacuum region between periodic imagesof about 12 Å. The total magnetic moment per atom of the four-layer slab was calculated to be 2.52 lB in ferromagnetic order.

The inhibitor molecule was then adsorbed in different initialconfigurations on one side of the slab, and the thickness of the vac-uum region between images was set to at least 13 Å. The molecularadsorption was modeled in a 4-layer 6 � 4 supercell, consisting of96 Fe atoms; the spin-polarized calculations at the gamma pointwere carried out by using the Marzari–Vanderbilt smearing witha width of 0.01 Ry. The coordinates of the iron atoms of the bottomlayer were kept fixed at the bulk position while all other atomswere allowed to relax during geometry optimization. Adsorptionenergies are calculated using the formula:

Eb ¼ Esurfþadtot � Esurf

tot � Eadtot ð1Þ

where the first term is the total energy of the full system (sur-face + adsorbate), the second term is the energy of the bareFe(110) surface and the last term is the energy of the gas-phasemolecule. According to this definition, the binding energies of stableadsorbates are negative. Charge density differences, defined as:

Dqð~rÞ ¼ qsurfþadð~rÞ � qsurfð~rÞ � qadð~rÞ ð2Þ

were also computed for all stable adsorption geometries, in order tocharacterize the interaction of the adsorbate with the surface. In Eq.(2), the first term is the density of the full system (surface + adsor-bate) while the second and third terms are the charge densities ofthe bare Fe(110) surface and the molecule at the relaxed nuclearconfiguration of the full system.

4. Results and discussion

Fig. 2 shows the variation of the complex plane plots withMPIMP and its concentration.

Excluding the dc limits, where small inductive behavior isemphasized due to the frequency-related polarity change, theshapes of the complex plane plots are very similar to that of theblank solution in the presence of MPIMP.

Because the frequency range covers several decades, a largeamount of noise from instrumental sources may lead to errors in

Fig. 3. Langmuir adsorption isotherm plot for mild steel in 0.5 M HCl solution in thepresence of various concentrations of MPIMP.

484 M. Özcan et al. / Corrosion Science 80 (2014) 482–486

the measurements, which is of vital importance for the analysis ofthe experimental results. The quality of our data was verified bythe Kramers–Kronig (K–K) transforms. A good agreement exists be-tween the data for both components for all of the data sets, with amaximum average error of 3% [33].

A circuit composed of a parallel combination of a capacitor anda resistor, both in series with the other resistor, cannot representour systems because they show frequency distribution. Consider-ing the shapes of the complex plane plots, we proposed and pro-duced a circuit model using the ZView software package(Scribner Associates, Inc.), which is configured to obtain the fittingparameters. The quality of the fits was evaluated using the chi-squared of which low value is the key point when determiningthe appropriate circuit model. Here, the chi-squared values werearound 3 � 10�3, which indicates a good quality of our fits.

In light of the previously discussed data, the equivalent circuitshown as an inset of Fig. 2 was determined, where the resistanceR1 is the resistance of the solution Rs, CPE1 reflects a frequency-distributed double-layer capacitance Cdl, and the resistance R2 isthe polarization resistance Rp. The impedance of the CPE is ex-pressed as [34]:

ZCPE ¼ Yo jxð Þn� ��1 ð3Þ

where Yo is a proportionality coefficient and n has a meaning of thephase shift depending upon its whole number value, CPE reduces tothe classical elements: C, R, L. Numerous authors have used CPE inmodeling by relating it to different physical phenomena. In ourstudy, the CPE is attributed to the difference between the responseof both the metal and solution sides of the double layer to alternat-ing current and the capacitive and faradic effects of the double layer[35].

The impedance parameters we acquired by fitting the above-mentioned circuit to the complex-plane plots are presented inTable 1.

As evident from the results in Table 1, the value of Rp increaseswith increasing MPIMP concentration. The value of the proportion-ality coefficient Yo of CPE varies on a regular basis with concentra-tion. The recalculation of Yo in terms of capacitance could serve as abasis for an approximate comparison between the capacitivebehaviors of different corrosion systems. The capacitance valueswere determined from CPE parameters, Yo and n, using the follow-ing equation [36]:

Cdl ¼ Yo x00m� �n�1 ð4Þ

A similar decrement tendency can be observed for the capaci-tance as a function of the concentration of MPIMP. The n valueexhibits an opposite trend in the studied concentration range,which suggests that the initial surface heterogeneity decreases asa result of the adsorption of MPIMP onto the most active adsorp-tion sites [37,38].

Changes in impedance parameters allowed us to draw conclu-sions about the adsorption of MPIMP onto the mild steel surface.To elucidate the mode of adsorption, we fit the experimental re-sults to a series of adsorption isotherms. The best fit was obtained

Table 1Impedance parameters acquired from complex plane plots in 0.5 M HCl solution in the ab

Mol. Ci (mM) �Eocp (mV, Ag/AgCl) Rp (X cm2)

Blank – 478 113.7MPIMP 0.1 476 236.0

0.5 472 309.11.0 471 444.05.0 471 701.6

with Langmuir adsorption isotherm (Fig. 3). The linearity of theplot in Fig. 3 seems to meet the requirements of the isotherm;however, a careful inspection reveals that its slope deviates slightlyfrom unity (1.161). This behavior is attributed to the interactionbetween the adsorbate molecules on the metal surface [24]. Thevalue of standard free energy of adsorption (DG�ads) was found as�0.33 eV which reveals the strong adsorptive interaction of MPIMPwith the surface metal atoms.

DFT was used to obtain a molecular-level understanding of theexperimental findings. Three stable adsorption configurationswere identified and are shown in Fig. 4, together with their respec-tive adsorption energies.

In the first of the two stable flat adsorption configurations (leftpanels of Fig. 4), the O atom of the hydroxyl group is directly on topof a surface Fe atom. The calculated Fe–O bond distance is 1.94 Å,and the computed adsorption energy indicates a strong surface–adsorbate interaction. Upon adsorption, the hydrogen atom ofthe hydroxyl group migrates toward the N atom of the iminegroup. Geometry optimization starting from initial configurationsin which the O atom of the hydroxyl group is not on top of a surfaceFe atom gives a second stable geometry (central panels of Fig. 4) inwhich the N atom of the imine group is bonded to a surface Featom. In this configuration, the calculated Fe–N bond distance is1.99 Å. During adsorption, the hydroxyl group moves away fromthe surface and no intramolecular H-transfer occurs. Both configu-rations are characterized by very similar adsorption energies(�2.77 eV and �2.76 eV, respectively). The adsorption energiesare consistent with the value of �1.2 eV by Kovacevic et al. forthe flat BIMD adsorption on Fe(110) surface [21]. The fact thatthe adsorption energy of MPIMP is more than twice the value forBIMD can be related to the presence of only one benzene ring inBIMD. A third adsorption configuration was identified in whichthe molecular plane of the adsorbate is perpendicular to the sur-face (right panels of Fig. 4). In this case, the interaction betweenthe surface and the adsorbate is only through the O atom of the

sence and in the presence of various concentrations of MPIMP.

CPEdl Cdl (�106 s X�1 cm�2)

Yo (�106 sn X�1 cm�2) n (0–1)

198.0 0.799 80.169.2 0.851 34.462.8 0.849 30.933.5 0.898 20.842.8 0.858 23.8

Fig. 4. Three stable adsorption configurations of MPIMP on Fe(110) surface together with their adsorption energies. (upper panels: top view. Lower panels: side view.).

M. Özcan et al. / Corrosion Science 80 (2014) 482–486 485

hydroxyl group and the surface Fe atom directly beneath it, whichis displaced by approximately 0.5 Å in the direction of the surfacenormal. The calculated Fe–O bond distance in this case is 1.98 Å. Asa result of the Fe–O interaction, an intramolecular H-transfer fromthe hydroxyl group to the imine group occurs. The computedadsorption energy (�0.60 eV) is rather low compared to that char-acteristic of the flat configurations, mainly because the p-molecu-lar orbitals are involved in the interaction in the latterconfigurations. This finding is also in good agreement with the re-sults of Kovacevic et al., where the adsorption energy for the per-pendicular adsorption mode of BIMD on Fe(110) surface was�0.80 eV [21].

To better characterize the surface–adsorbate interaction, wepresent, in the upper panels of Fig. 5, a plot of the charge densitydifference function, Eq. (2), for all three adsorption configurations.

The large values of the adsorption energies for the two flatconfigurations are apparently a consequence of the strong inter-action of the delocalized p-electrons of the aromatic rings withthe surface Fe atoms. This is further corroborated from the anal-ysis of the projected density of states (PDOS) given in the lowerpanels of Fig. 5. In the DOS and PDOS calculations, a Gaussianbroadening of 0.02 Ry was used. Furthermore, the density ofstates is projected to the MPIMP molecule and the Fe atoms be-neath it. In the case of the p�d molecule–Fe interaction, themolecular PDOS is relatively unstructured in the vicinity of theFermi energy for both flat configurations. This behavior of themolecular PDOS, given in the left and central panels of Fig. 5,should be contrasted with that corresponding to the perpendicu-lar adsorption configuration.

Fig. 5. Charge density differences (upper panels) and density of states projected to mol(Electron-rich and electron-deficient regions are represented with red and blue color, rereader is referred to the web version of this article.)

Although the calculations overestimate the adsorption energieswith respect to the experimental finding, both point toward astrong interaction of the inhibitor molecule with the surface. Alikely explanation of this overestimation is the neglect of solventeffects in the calculations, and was illustrated recently by Kovace-vic et al. for the adsorption of azole molecules on the Cu(111) sur-face [39]. A consistent ab initio inclusion of solvent effects on theadsorption of the inhibitor molecule on a solid surface is a compli-cated task. The rather limited number of published studies so farrelied on simplifying models such as the explicit treatment of avery small number of water molecules for the adsorption of IMDon the Fe(110) surface [22] or the use of a continuum solvationmodel and the use of gas-phase adsorption geometries for theadsorption of azole molecules on the Cu(111) surface [39], whichhamper a quantitative assessment of solvent effects. Nonetheless,it can be safely concluded, especially in view of the results pre-sented in Ref. [39], that solvent effects are likely to decrease theadsorption energy since upon adsorption of the inhibitor moleculeon the solid surface (i) pre-adsorbed water molecules are dis-placed, and (ii) the adsorbate must lose at least some of the watermolecules of its solvation shell. Moreover, the possibility of waterdissociation on the iron surface must also be taken into account inan accurate treatment of the effects of solvation [40]. However, thepresent results are still relevant since it can reasonably be assumedthat the more important mechanism of adsorbate–surface bonding,i.e. the interaction of the delocalized p-electrons of the aromaticrings with the surface Fe atoms, is at least partially maintainedin the presence of solvent.

ecule and Fe (lower panels) for the three stable adsorption configurations in Fig. 4.spectively.). (For interpretation of the references to colour in this figure legend, the

486 M. Özcan et al. / Corrosion Science 80 (2014) 482–486

5. Conclusions

The corrosion of mild steel in a 0.5 M hydrochloric acid solutionwas inhibited by MPIMP to some extent in the concentration rangestudied. The relatively high value of DG�ads reveals that MPIMPinteracts strongly with the mild steel surface. Three stable end con-figurations on the Fe(110) surface were theoretically identified forMPIMP, with the flat adsorption configurations being the most sta-ble. The computed adsorption energy values also confirm thestrong interaction between MPIMP molecules and the surface me-tal atoms.

Acknowledgements

Muzaffer Özcan and _Ilyas Dehri would like to thank the Çukur-ova University Research Fund for the financial support. DanieleToffoli and Hande Üstünel wish to thank ULAKBIM (TR-GRID) forcomputational resources.

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