Quantum chemical calculations, molecular dynamics simulation and

Journal of the Taiwan Institute of Chemical Engineers 68 (2016) 461–480

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Quantum chemical calculations, molecular dynamics simulation and experimental studies of using some azo dyes as corrosion inhibitors for iron. Part 1: Mono-azo dye derivatives Loutfy H. Madkour a,∗, Savas¸ Kaya b, Cemal Kaya b, Lei Guo c a b c

Chemistry Department, Faculty of Science and Arts, Baljarashi, Al-Baha University, P.O. Box 1988 Al-Baha, Saudi Arabia Cumhuriyet University, Faculty of Science, Department of Chemistry, 58140 Sivas, Turkey School of Material & Chemical Engieering, Tongren University, Tongren 554300, PR China

a r t i c l e

i n f o

Article history: Received 6 January 2016 Revised 14 August 2016 Accepted 10 September 2016 Available online 1 October 2016 Keywords: Density functional theory Molecular dynamics simulation Corrosion Mono-azo dyes Iron Adsorption

a b s t r a c t This study consists of two parts. In the first part, the inhibitive performance of six mono-azo dye (MAD_1–6) derivatives was investigated experimentally (gravimetric, thermometric, UV–visible spectrophotometric and electrochemical potentiostatic methods) and computationally against corrosion of Fe metal in 2 M HNO3 and 2 M NaOH solutions. Density functional theory (DFT) calculations and molecular dynamics simulation (MDS) approach were performed. Quantum chemical parameters such as the highest occupied molecular orbital energy (EHOMO ), lowest unoccupied molecular orbital energy (ELUMO ), the energy gap between ELUMO and EHOMO (E), dipole moment (D), chemical hardness (η), softness (σ ), electronegativity (χ ), proton affinity, global electrophilicity (ω), global nucleophilicity (ε ) and total energy (sum of electronic and zero-point energies) were calculated and discussed with the help of HF/SDD, HF/6311 G, HF/6-31++G, B3LYP/SDD, B3LYP/6-311 G and B3LYP/6-31++G methods. Polarization measurements indicate that (MAD) compounds are of mixed-type inhibitor in acidic, act mainly as cathodic in alkaline solution. Kinetic model involving binding constant (Kb ), active sites (1/y) and standard free energy values of adsorption (࢞Go ) were compared with the parameters of equilibrium constant (Kads ), lateral interaction (f) and (࢞Go ), that obtained from Frumkin adsorption isotherm model. Then, we calculated binding energies on Fe (110) surface of the inhibitors. The theoretical data obtained are in good agreement with the experimental inhibition efficiency results. © 2016 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

1. Introduction Metals and alloys used in many engineering applications are susceptible to corrosion in aqueous media. Iron and its alloys, the most widely used among them, is also highly susceptible to corrosion, especially in acidic and alkaline media [1–5]. One of the best known methods for corrosion protection is the use of inhibitors [6,7]. Different types of organic compounds have been reported to act as inhibitors of corrosion [8–14]. Azo dyes as the most widely used as inhibitors class is controlled by its economic availability, its efficiency to inhibit the substrate material and its environmental side effects [15–19]; their application in various fields, such as the dyeing of textiles, and fibbers [20]. The presence of –N=N– group in azo dye molecules enhances their adsorption ability and

∗

Corresponding author. fax: +966 77247272. E-mail addresses: [email protected], [email protected] (L.H. Madkour).

[email protected],

corrosion inhibition efficiency. The planarity (π ) and lone pair of electrons present on the N atoms are the important structural features that determine the adsorption of these molecules on to the metal surface [1]. The inhibition effect was also found to depend on some physicochemical and electronic properties of the organic inhibitor which relate to its functional groups, steric effects, electronic density on donor atoms, and orbital character of donating electrons [21]. Quantum chemical methods have already proven to be very useful in determining the molecular structure as well as elucidating the electronic structure and reactivity [22] of potent inhibitors [23]. Thus, it has become a common practice to carry out quantum chemical calculations in corrosion inhibition studies. The predicted properties of reasonable accuracy can be obtained from density functional theory (DFT) calculations [24,25]. Some quantum chemical parameters, which influence the electronic interaction between surface atoms and inhibitors, are the energy of highest occupied molecular orbital (EHOMO ), the energy of lowest unoccupied molecular orbital (ELUMO ), the energy gap EHOMO − ELUMO (E) and dipole moment (D), chemical hardness

http://dx.doi.org/10.1016/j.jtice.2016.09.015 1876-1070/© 2016 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

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L.H. Madkour et al. / Journal of the Taiwan Institute of Chemical Engineers 68 (2016) 461–480

(η), softness (σ ), electronegativity (χ ), proton affinity, global electrophilicity (ω), global nucleophilicity (ε ) and total energy (sum of electronic and zero-point energies). Previously, some work has been done in our laboratory on using mono– and bis–azo dye compounds as inhibitors on aluminum in HCl and NaOH solutions [26]. The aim of the present study was to investigate and compare the inhibition of corrosion of iron in 2.0 M HNO3 and 2.0 M NaOH solutions by six synthesized mono-azo dye derivatives shown in Fig. 1 at 303 K. We have determined the inhibition efficiencies of these compounds using weight loss, thermometric, spectroscopy measurements and polarization curves method. Theoretical studies on electronic and molecular structures of substituted mono-azo dyes were carried out with the help of quantum chemical calculations and molecular dynamics simulations (MDS) approach to determine the most effective corrosion inhibitor among them.

HO

N

N

OH

Mono-α-naphthyl amine (MAD_1)

HO

N

N

OH

Mono-β -naphthyl amine (MAD_2)

R= α -Naphthyl; the compound namely mono-α -naphthyl amine (MAD_1) β - Naphthyl; the compound namely mono -β -naphthyl amine (MAD_2) C6 H4 OMe-p; the compound namely mono -p-anisidine (MAD_3) C6 H4 Me-p; the compound namely mono -p-toluidine (MAD_4) C6 H4 Me-o; the compound namely mono -o-toluidine (MAD_5) C6 H4 Me-m; the compound namely mono -m-toluidine (MAD_6) 2. Experimental details

HO

N

N

OMe

OH

Mono-p-anisidine (MAD_3)

HO

N

N

Me

2.1. Synthesis of the mono-azo dye compounds OH

The investigated mono-azo dye (MAD_1–6) derivatives were synthesized by diazotization of primary aromatic amines and coupling with the corresponding naphthol derivatives in the ratio 1:1. The compounds are purified and characterized by elemental analysis, IR, UV–visible spectroscopic investigation; mass spectroscopy and 1 Hnmr spectra spectroscopy techniques. The inhibitor solutions were prepared by dissolving the appropriate amount in 10 cm3 Analar ethanol. The desired volume of the free inhibitor was added to the electrolyte solution. The ratio of ethanol was kept constant for each test. This stock solution was used for all experimental purposes. The concentration range of azo dye inhibitors employed was 5 × 10−7 M – 10−4 M at 303 K. The chemical structure and IUPAC name of synthesized azo dye compounds are given in Fig. 1. The corrosion tests were performed on iron specimens of following composition (wt. %): C = 0.16, Mn = 0.37, Si = 0.05, S = 0.015 and remainder Fe. Iron specimens of size 2.0 × 2.0 × 0.1 and 10 × 1 × 0.l cm were used for weight loss and thermometric measurements, respectively. Solution of 2.0 M HNO3 and 2.0 M NaOH were prepared by dilution of Analar analytical grade using double distilled water.

Mono-p-toluidine (MAD_4)

Me HO

N

N

OH

Mono-o-toluidine

(MAD_5)

Me HO

N

N

OH

2.2. Measurements

Mono-m-toluidine 2.2.1. Weight loss measurements Weight loss experiments were done according to the standard methods as reported in literature [27]. The corrosion rates,

(MAD_6)

Fig. 1. Chemical molecular structures of synthesized mono-azo dye (MAD_1-6) derivatives.


463

CR (mg cm−2 h−1 ) were calculated according to the following equation [28,29]:

CR = (W b − W a )/At

(1)

where Wb and Wa are coupon weights measured before and after immersion in the test solutions, A is the exposed area and t is the exposure time (5h). The inhibition efficiency IE (%) was calculated according to the following equation [30]:

IE (% ) =

CR − CR (inh ) × 100 CR

(2)

where CR and CR (inh) are the values of corrosion rate (mg cm−2 h−1 ) of iron in uninhibited and inhibited solutions, respectively. 2.2.2. Thermometric measurements The reaction vessel used was basically the same as that described by Mylius [31]. An iron piece (10 × 1 × 0.l cm) was immersed in 30 cm3 of either 2.0 M HNO3 and/or 2.0 M NaOH in the absence and presence of additives, and the temperature of the system was followed as a function of time. The procedure for the determination of the metal dissolution rate by the thermometric method has been described previously [31,32]. The reaction number (RN) is defined [33] as:

RN =

(Tmax − Ti )

(3)

t

where Tmax and Ti , are the maximum and initial temperatures, respectively, and t is the time (in minutes) required to reach the maximum temperature. The percent reduction in RN [34,35] is then given as:

%reduction in RN =

(RN f ree − RN inh ) RN f ree

× 100

(4)

2.2.3. Electrochemical measurements A conventional three – electrode cell was used with a 1.0 cm2 Pt sheet as the counter electrode which was separated from the main cell compartment by a glass sinter. The potentials of the working electrode were referred to a saturated calomel electrode (SCE). In order to avoid contamination, the reference electrode was connected to the working- electrode through a salt bridge filled with the test solution. The tip of the bridge was pressed against the working electrode in order to compensate the ohmic drop. Prior to each experimental measurement, the solution under investigation (25 cm3 ) was freed of oxygen by passing prewashed pure nitrogen through it for a sufficient time. Measurements were performed on a planar disk electrode (A = 1 cm2 ). The iron electrodes were carefully degreased, and the edges were masked by appropriate resins (Duracryle, Spofa–Dental, and Praha). The surface of the iron electrodes were prepared by mechanical grinding and polishing as given elsewhere [2–5,8–10,35]. The electrodes were rinsed in an ultrasonic bath containing bid stilled water and finally washed with bid stilled water immediately before being immersed in the cell. The pretreatment procedure was repeated before each experiment. Anodic and cathodic potentiostatic polarization of iron electrodes were measured with a (Wenking Potentioscan model POS 73). Potentials and currents were determined by digital multi meters. Corrosion current densities (Icorr ) were determined by extrapolation of the anodic and cathodic Tafel lines to the free corrosion potential value (Ecorr ). Each experiment was conducted with a freshly prepared solution and with newly polished electrodes. The cell temperature was kept constant at 303.0 ± l.0 K in an ultrathermostat. The inhibition efficiencies at different inhibitor concentrations were calculated using the following equation:

IE (% ) =

Icorr − Icorr (inh ) × 100 Icorr

(5)

Fig. 2. Absorption spectra of Fe ions containing 10−4 M (MAD_1) and (MAD_5) in 2.0 M HNO3 ; and (MAD_6) in 2.0 M NaOH: (a) without inhibitors (b) with inhibitors at 303 K.

where Icorr and Icorr (inh) are the corrosion current densities for uninhibited and inhibited solutions, respectively.

2.2.4. Spectrophotometric measurements UV–visible absorption spectrophotometric method was applied on the corrosive solutions produced from the corrosion of iron samples, either without or with (MAD_1) and (MAD_5) in 2.0 M HNO3 ; and (MAD_6) in 2.0 M NaOH, respectively. All the spectra measurements were carried out using a Perkin–Elmer UV–Visible Lambda 2 spectrophotometer, as shown in Fig. 2.

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given as follows. It is important to note that nucleophilicity (ε ) is known as the multiplicative inverse of the electrophilicity [48].

3. Computational details 3.1. Quantum chemical calculations Density Functional Theory (DFT) is one of the most important theories that have been presented to predict the reactivity or stability of chemical species. Nowadays, theoretical methods based on DFT have been very popular [36]. In the present study, DFT calculations were carried out using Gaussian 9.0 Program [37]. The input files of studied molecules were prepared with Gauss View 5.0.8 [38]. A full optimization was performed up to a higher basis set denoted by 6-31G++ (d, p) because this basis set gives more accurate results in terms of the determination of geometries and electronic properties for a wide range of organic compounds. The calculations in both gas and aqueous phases were also made using other levels of theory such as HF and DFT/B3LYP methods with SDD, 6-31++G (d, p) and 6-31 G basis sets. In parallel with developments in both quantum chemistry and DFT, based on the ionization energy and electron affinities of chemical species (atom, ion or molecule), quantum chemical description such as chemical hardness (η), chemical potential (μ) and electronegativity (χ ) are defined as follows [39–41].

η=

I−A 2

χ = −μ =

(6) I+A 2

(7)

Pearson who introduced the chemical hardness concept described as the multiplicative inverse of chemical hardness the softness (σ ) [42,43].

σ=

1

(8)

η

One of the theorems that provide great facilities to computational chemists has been proposed by Koopmans [44]. This theorem presents an alternative method to predict the ionization energies and electron affinities of chemical compounds. According to the theorem, the negative of the highest occupied molecular orbital energy and the negative of the lowest unoccupied molecular orbital energy corresponds to ionization energy and electron affinity, respectively (-EHOMO = I and –ELUMO = A). If so, within the framework of aforementioned theorem, one can write the following mathematical formulas for chemical hardness, electronegativity and chemical potential [45].

η=

ELUMO − EHOMO 2

μ = −χ =

ELUMO + EHOMO 2

(9)

(10)

Proton affinity (PA) is one of the most important indicators of electron donating abilities [46] of molecules because there is a remarkable correlation gas phase basicity and proton affinity. Proton affinities of molecules can be compared with the help of via following equations.

PA = E(pro) − (E(non−pro) + EH + )

(11)

where, Enon-pro and Epro are the energies of the non-protonated and protonated inhibitors, respectively. EH + is the energy of H+ ion and was calculated as:

EH + = E ( H3 O+ ) − E ( H2 O )

(12)

According to global electrophilicity index (ω) proposed by Parr [47], the electrophilicity of any chemical species is associated with its electronegativity and hardness and is defined mathematically as

ω=

μ2 χ 2 = 2η 2η

ε = 1/ω

(13) (14)

3.2. Molecular dynamics simulation Molecular dynamics simulations (MDS) is very popular for the investigation regarding the interaction between the inhibitor molecule and the concerned metal surface. The interaction between mono-azodye inhibitors and the iron surface was simulated using Forcite module of Materials Studio 6.0 program developed by Accelrys Inc. [49,50]. Herein, we had chosen the Fe (110) surface, which is a density packed surface and was the most stable [51] to simulate the adsorption process. Five layers of iron atoms were used to ensure that the depth of the surface was greater than the non-bond cutoff radius used in the calculation. The MD simulation was performed at 303 K controlled by the Andersen thermostat, NVT ensemble, with a time step of 1.0 fs and simulation time of 10 0 0 ps, using the COMPASS [52] force field. Non-bond Interactions, Van der Waals and electrostatic, were set as atom-based summation method and Ewald summation method, respectively, with a cutoff radius of 1.55 nm. Details of simulation process can be referred to some previous literature [53].The interaction energy between the inhibitor molecules and the Fe (110) surface is calculated by Eq. (15)

Einteraction = Etotal − (Esurface + Einhibitor )

(15)

Herein, the total energy of the surface and inhibitor molecule is designated as Etotal , Esurface is the surface energy without the inhibitor and Einhibitor is the energy of the adsorbed inhibitor on the surface. The binding energy of the inhibitor molecule is expressed as Ebinding = −Einteraction . 4. Results and discussion The inhibition efficiencies of the six synthesized mono-azo dye (MAD_1–6) derivatives on the corrosion of iron in 2.0 M HNO3 and 2.0 M NaOH solutions using chemical (gravimetric, thermometric, UV–visible spectrophotometric) and electrochemical potentiostatic polarization measurements were investigated. Quantum chemical calculations and molecular dynamics simulation (MDS) studies were applied, discussed and correlated with the experimental methods. The calculated binding energies of the azodye molecules on (110) Fe surface demonstrated that these molecules are very effective inhibitors against the corrosion of iron in HNO3 and NaOH media. The obtained results in the study are given in detail below. 4.1. Gravimetric measurements The gravimetric method (weight loss) is probably the most widely used method of inhibition assessment [54–60]. Corroborative results between weight loss and other techniques have been reported [61,62]. It is the most accurate and precise method for determining metal corrosion rate because the experiment is easy to replicate and, although long exposure times may be involved, the relatively simple procedure reduces the propensity to introduce systematic errors. The effect of addition of different (MAD_1–6) derivatives at various concentrations on the iron corrosion in 2.0 M HNO3 and 2.0 M NaOH solutions was studied by weight loss measurements at 303 K after 5–6 h immersion. The values of inhibition efficiency IE (%) and surface coverage (θ ) obtained from weight loss


465

Table 1 Corrosion parameters obtained from weight loss measurements for iron in 2.0 M HNO3 containing various concentrations of the synthesized mono-azo dye (MAD_1–6) inhibitors at 303 K. Inhibitor type, Conc. (M)

5 × 10−7 1 × 10− 6 5 × 10− 6 1 × 10− 5 5 × 10− 5 1 × 10− 4

(MAD_1)

(MAD_2)

(MAD_3)

(MAD_4)

(MAD_5)

(MAD_6)

θ

IE (%)

θ

IE (%)

θ

IE (%)

θ

IE (%)

θ

IE (%)

θ

IE (%)

0.647 0.671 0.676 0.685 0.746 0.785

64.7 67.1 67.6 68.5 74.6 78.5

0.647 0.656 0.659 0.672 0.733 0.776

64.7 65.6 65.9 67.2 73.3 77.6

0.643 0.644 0.646 0.657 0.729 0.764

64.3 64.4 64.6 65.7 72.9 76.4

0.613 0.615 0.624 0.654 0.720 0.750

61.3 61.5 62.4 65.4 72.0 75.0

0.610 0.611 0.613 0.645 0.711 0.740

61.0 61.1 61.3 64.5 71.1 74.0

0.610 0.616 0.626 0.644 0.711 0.735

61.0 61.6 62.6 64.4 71.1 73.5

measurements are listed in Table 1. The corrosion rate values (mg cm−2 h−1 ) of iron in 2.0 M HNO3 and 2.0 M NaOH solutions, respectively, decrease as the concentration of inhibitor increase. The results show that the IE (%) and (θ ) values increase as the concentration of the inhibitor increases from 5 × 10−7 – 1 × 10−4 M. The maximum inhibition efficiency was about 78.5% at 1 × 10−4 M for (MAD_1). From Table 1, it is clear that the order of inhibition efficiency of (MAD_1–6) derivatives is as follows: (MAD_1)> (MAD_2)> (MAD_3)> (MAD_4)> (MAD_5)> (MAD_6).The adsorption isotherm experiments were performed to have more insights into the mechanism of corrosion inhibition, since it describes the molecular interaction of the inhibitor molecules with the active sites on the iron surface [63]. The surface coverage, θ , was calculated according to the following equation:

θ=

CR0 − CR CR0 − CRm

(16)

Where, CR0 and CR are the corrosion rates of iron for uninhibited and inhibited solutions, respectively. CRm is the smallest corrosion rate. The surface coverage values (θ ) for different inhibitor concentration were tested by fitting to various isotherms and the models considered were [64]:

Temkin isotherm exp ( f.θ ) = kads .C

(17)

Langmuir isotherm(θ /1 − θ ) = kads .C

(18)

Frumkin isotherm(θ /1 − θ ) exp (−2 f.θ ) = kads .C

(19)

Freundluich isotherm θ = kads .C

(20)

Where kads is the equilibrium constant for adsorption process, C is the concentration of inhibitor and f is the energetic inhomogeneity. Attempts were made to fit the θ values to various isotherms including Langmuir, Temkin, Frumkin and Freundluich. By far the best fit is obtained with the Frumkin adsorption isotherm [64]. The plot of (θ ) vs. log C gave S-shaped curves, suggest that the adsorption of the investigated molecules on Fe surface obeyed the Frumkin adsorption isotherm, as shown in Fig. 3. Stabilizing effect [65] that comes from the complex compound formed indicates rearrangement of the charge density inside the molecule, thus shows its corrosion inhibition. This is supported by U.V. spectrophotometer analysis (Fig. 2), and also by conductivity measurements. 4.2. Thermometric measurements Thermometric curves of the iron electrode in 2.0 M HNO3 without and with addition of (MAD_1–6) derivatives at different concentrations are investigated and given in Fig. 4 for (MAD_1), (as example) for the studied derivatives. The values of thermometric parameters associated with thermometric measurements are listed in Table 2. It is evident that, the dissolution of iron in 2.0 M HNO3 starts from the moment of immersion. On increasing the concentration of the inhibitor from (5 × 10−7 – 1 × 10−4 M) the value of

Fig. 3. Variation of iron surface coverage (θ ) with the logarithmic concentrations of different substituted mono-azo dye derivatives in 2.0 M HNO3 at 303 K.

Tmax decreases, whereas the time (t) required reaching Tmax increases, and both factors cause a large decrease in (RN) and increasing of (% red RN) of the system [33], as shown in Table 2. This indicates that the studied synthesized mono-azo dye additives retard the dissolution presumably by strongly adsorption onto the iron surface. The extent of inhibition depends on the degree of the surface coverage (θ ) of the metal surface with the adsorbate. Iron, as an active element, always carries an air formed oxide, which specifically and very strongly adsorbs H+ and OH− ions. The dissolution of iron reactions takes place along the incubation period. The heat evolved from these reactions accelerates further dissolution of the oxide and activates the dissolution of the iron metal exposed to the aggressive medium. The relation between RN, time delay (࢞t) and/or log (࢞t) versus molar concentration of the additives confirms a two-step adsorption process [66], at first a monolayer of the adsorbed is formed on the iron electrode surface, and then it is followed by the adsorption of a second adsorbed layer or a chemical reaction leading to the deposition of the (azo dye-Fe complex) on the metal surface. The plot of t and/or log (t) as a function of log CIn yields a linear relation shape for the first region of the curve then a region of constancy; this reveals the completion of the adsorbed monolayer of the inhibitor. In thermometric measurements (% red RNIn ) values are taken as the measure for the corrosion inhibition efficiency (% In). Plots of % red RN versus molar concentration (CIn ) of the additives for iron corrosion in 2.0 M HNO3 are invariably sigmoidal in nature as shown in Fig. 5. The inhibition efficiency of the

466

L.H. Madkour et al. / Journal of the Taiwan Institute of Chemical Engineers 68 (2016) 461–480 Table 2 Effect of different concentrations of (MAD_1) on the thermometric parameters of iron in 2.0 M HNO3 . Conc. (M)

Log C(M)

Ti °C

Tmax °C

t min.

2.0 M HNO3 5 × 10− 7 1 × 10− 6 5 × 10− 6 1 × 10− 5 5 × 10− 5 1 × 10− 4

−6.3 −6.0 −5.3 −5.0 −4.3 −4.0

19.5 18.5 18 18 18 18 18

50.8 46.5 46.0 40.9 39.9 39.0 37.4

68 122 130 143 145 180 196

t min. – 54 62 75 77 112 128

Log t

ϴ

R.N.

% Red in R.N.

– 1.732 1.792 1.875 1.886 2.049 2.107

– 0.502 0.532 0.652 0.671 0.746 0.786

0.460 0.229 0.215 0.160 0.151 0.116 0.098

– 50.2 53.2 65.2 67.2 74.7 78.7

studied (MAD_1–6) derivatives depends on many factors, including the molecular size, heat of hydrogenation, mode of interaction with iron electrode surface, formation of metallic complexes and the charge density on the adsorption sites. Adsorption is expected to take place primarily through functional groups, essentially OH and OCH3 would depend on its charge density as reported [67]. The thermometric technique cannot be applied for the iron corrosion in alkaline media because of the formation of oxide films on the iron electrode surface, which formed only in near neutral and slightly alkaline solutions. 4.3. Potentiostatic polarization measurements

Fig. 4. Temperature vs. time curves of iron corrosion in 2.0 M HNO3 in presence of different concentrations of mono-α -naphthyl amine (MAD_1).

Polarization curves of the iron electrode in 2.0 M HNO3 and 2.0 M NaOH solutions, respectively, without and with addition of (MAD_1) derivative (as example) at different concentrations are shown in Fig. 6. The values of electrochemical parameters associated with polarization measurements, such as corrosion potential (Ecorr ), corrosion current densities (Icorr ) and Tafel slopes (β a, β c) are listed in Table 3. The inhibition efficiencies were calculated from Icorr values (Table 3) obtained from extrapolating Tafel lines to the corrosion potential according to Eq. (5). The values of corrosion current density (Icorr ) decreased in presence of (MAD_1–6) derivatives which suggests that the rate of electrochemical reaction was reduced due to the formation of a barrier layer over the iron surface by the inhibitor molecule. The parallel cathodic Tafel lines suggested that the addition of inhibitors to the 2.0 M HNO3 solution do not modify the hydrogen evolution mechanism and the reduction of H+ ions at the iron surface which occurs mainly through a charge-transfere mechanism. The shift in the anodic Tafel slope (β a) values may be due to the adsorption of nitrate ions/or inhibitor molecules onto the iron surface [68]. It is also clear that there is a shift towards cathodic region in the values of corrosion potential (Ecorr ), from the fact that β c > β a. The extent of adsorption of inhibitor molecules onto the metal surface in term of the surface coverage (θ ) was calculated using Eq. (21) [69]:

θ=

Fig. 5. Effect of substituted (MAD_1-6) derivatives on percentage reduction in reaction number (% red. in RN) for iron corrosion in 2.0 M HNO3 .

ICorr(uninh) − ICorr(inh) ICorr(uninh)

(21)

where ICorr (uninh) and ICorr (inh) are the corrosion current densities in the absence and presence of the inhibitors, respectively. From Table 3, it is also clear that the values of cathodic and anodic Tafel slope constant are slightly change and independent on the inhibitors concentrations, indicating that the inhibition role of these inhibitors is not through the interference on the reactions of metal dissolution and reduction of protons. . It is clear from the polarization curves (Fig. 6) that, the increase of the inhibitor concentrations decreases the corrosion current (Icorr ) which consequently increases the surface coverage values; and consequently increases the retardation of the iron dissolution in the acidic and alkaline media. The results show that (MAD_1) at 1 × 10−4 M produce the lowest Icorr (7.713 mA cm−2 ) and the maximum IE (%) obtained was 77.8% (Table 3).


467

Table 3 Potentiodynamic polarization corrosion parameters of Fe dissolution reaction in 2.0 M HNO3 and 2.0 M NaOH solutions in absence and presence of 10−4 M mono-(MAD_1-6) substituted azodye inhibitors at 303 ± 1 K. Inhibitor type

Corrosive solution

-Ecorr (mV(SCE))

Icorr (mA cm−2 )

-β c (V dec−1 )

β a (V dec−1 )

θ

IE (%)

Blank Blank MAD_ 1

2.0 M 2.0 M 2.0 M 2.0 M

HNO3 NaOH HNO3 NaOH

340 775 300 653

34.670 6.762 7.713 2.805

0.960 0.350 0.844 0.221

0.879 – 0.761 –

– – 0.778 0.5851

– – 77.8 58.5

MAD_ 2

2.0 M HNO3 2.0 M NaOH

305 646

8.184 2.612

0.844 0.251

0.752 –

0.763 0.5341

76.3 53.4

MAD_ 3


316 683

8.346 3.344

0.833 0.221

0.767 –

0.759 0.5054

75.9 50.5

MAD_ 4


295 650

9.690 3.712

0.830 0.224

0.780 –

0.721 0.4510

72.1 45.1

MAD_ 5


298 668

10.593 3.914

0.836 0.231

0.777 –

0.694 0.4211

69.4 42.1

MAD_ 6


320 700

10.656 4.185

0.841 0.267

0.761 –

0.692 0.3811

69.2 38.1

Fig. 6. Potentiostatic polarization curves of iron in (a) 2.0 M HNO3 and (b) 2.0 M NaOH solutions with the (MAD_1) in different concentrations at 303 K.

Thus, the studied mono-azo derivatives act as adsorptive inhibitors, i.e. they reduce anodic dissolution and also retard the hydrogen evolution reaction [70] via blocking the active reaction sites on the iron surface, or even can screen the covered part of the electrode; and therefore protect it from the action of the corrosion medium [71]. Mono-azo dyes were first adsorbed onto the metal surface and impeded by merely blocking the reaction sites of the

metal surface without affecting the anodic and cathodic reaction [72], which suggests the retardation of iron corrosion in inhibited solution with respect to uninhibited. According to Ferreira and others [73,74] if the displacement in (Ecorr ) values (i) >85 mV in inhibited system with respect to uninhibited, the inhibitor could be recognized as cathodic or anodic type and (ii) if displacement in Ecorr is MAD_ 2> MAD_ 3> MAD_ 4> MAD_ 5> MAD_ 6. The HOMO-LUMO energy gap (࢞E) is one of the parameters widely used to describe the chemical reactivity. This quantity exhibits the reactivity of molecules towards the metal surface. In fact, the roles on corrosion inhibition efficiencies of molecules of chemical hardness, softness and ࢞E can be discussed in the same paragraph because these quantum chemical parameters are closely associated with each other. Chemical hardness is a measure of the resistance towards electron cloud polarization or deformation of chemical species. Pearson [85] who introduced the chemical hardness concept in 1960 s stated that "hard molecules have a large HOMO-LUMO energy gap and soft molecules have a small HOMOLUMO gap". In other words, a small energy gap implies high polarizability and a large energy gap implies low polarizability. According to Maximum Hardness Principle [86,87] based on chemical hardness concept, “a chemical system tends to arrange itself so as to achieve maximum hardness and chemical hardness can be considered as a measure of stability.” With the framework of these information given, it can be said that soft molecules (small energy gap) acts good corrosion inhibitor and hard molecules (stable=large energy gap) are not good corrosion inhibitors. On the basis of the calculated chemical hardness, softness and energy gap given in the related tables, the corrosion inhibition efficiency ranking of studied mono-azo dye derivatives can be written as: MAD_ 1> MAD_ 2> MAD_ 3> MAD_ 5> MAD_ 4> MAD_ 6. Electronegativity can be described as the power of a chemical species to attract to electrons to itself and this quantity is widely used to estimate the inhibitive properties of molecules. To determine the fraction of electron transferred from the inhibitor molecules to metal surface, we used the Pearson method given by Eq. (11) [88]. It is seen from this equation that the fraction of electron transferred increases as the differences in electronegativity’s between metal and inhibitor molecules. According to Sanderson’s [89,90] electronegativity equalization principle, the electron transfer between metal and inhibitor continues until their electronegativity values become equal with each other.

N =

χF e − χinh 2(ηF e + ηinh )

(27)

where χ Fe and χ inh are electronegativity of Fe metal and electronegativity of inhibitor, respectively. ηFe and ηinh represent chemical hardness value of Fe metal and chemical hardness value of inhibitor, respectively. For Fe, the theoretical values of χ Fe and ηFe are 7 eV and 0 eV. Elnga [91] and co-workers noted that the inhibition efficiency increases with increasing of ࢞N value. Considering the electronegativity’s calculated for studied mono-azo dye derivatives in Tables 5 and 6 and the fraction of electron transferred values given in Table 9, the inhibition efficiency ranking of aforementioned molecules can be given as: MAD_ 1> MAD_ 3> MAD_ 2≈ MAD_ 4> MAD_ 5> MAD_ 6.


469

Table 5 Calculated quantum chemical parameters for neutral forms of studied mono-azo dye derivatives in gas phase (eV). ELUMO

I

A

E

η

σ

χ

PA

ω

ε

D (Debye)

Energy

HF/SDD Level MAD_1 −7.42169 MAD_2 −7.46006 MAD_3 −7.42713 −7.46850 MAD_4 MAD_5 −7.51884 MAD_6 −7.51639

1.36684 1.43432 1.68304 1.63732 1.55405 1.59079

7.42169 7.46006 7.42713 7.46850 7.51884 7.51639

−1.36684 −1.43432 −1.68304 −1.63732 −1.55405 −1.59079

8.78853 8.89438 9.11017 9.10582 9.07289 9.10718

4.39427 4.44719 4.55509 4.55291 4.53645 4.55359

0.22757 0.22486 0.21953 0.21964 0.22044 0.21961

3.02743 3.01287 2.87205 2.91559 2.98239 2.96280

−2.51920 −0.83722 −1.41495 −0.85926 −0.83170 −15.6291

1.04287 1.02057 0.90543 0.93354 0.98036 0.96387

0.95889 0.97984 1.10444 1.07119 1.02004 1.03748

0.8505 0.5733 1.6245 0.2040 0.8333 0.4267

−27852.27331 −27852.35944 −26798.05968 −24762.11131 −24762.04208 −24762.10353

HF/6-311 G Level MAD_1 −7.36373 MAD_2 −7.39421 MAD_3 −7.35883 MAD_4 −7.40591 MAD_5 −7.45816 MAD_6 −7.45543

1.46643 1.51759 1.76440 1.71052 1.63841 1.67379

7.36373 7.39421 7.35883 7.40591 7.45816 7.45543

−1.46643 −1.51759 −1.76440 −1.71052 −1.63841 −1.67379

8.83016 8.91180 9.12323 9.11643 9.09657 9.12922

4.41508 4.45590 4.56162 4.55822 4.54828 4.56461

0.22650 0.22442 0.21922 0.21938 0.21986 0.21908

2.94865 2.93831 2.79722 2.84769 2.90987 2.89082

−2.54875 −0.86114 −1.41919 −0.88637 −0.85630 −0.85973

0.98464 0.96879 0.85764 0.88953 0.93083 0.91540

1.01560 1.03222 1.16599 1.12419 1.07431 1.09242

0.9012 0.6664 1.5103 0.2232 0.8916 0.5101

−27854.66763 −27854.75115 −26800.26935 −24764.21550 −24764.14116 −24764.21517

HF/6-31++G Level MAD_1 −7.40945 MAD_2 −7.45026 MAD_3 −7.41707 MAD_4 −7.46033 MAD_5 −7.50931 MAD_6 −7.50714

0.98805 1.00356 1.01935 1.02533 0.99268 1.01445

7.40945 7.45026 7.41707 7.46033 7.50931 7.50714

−0.98805 −1.00356 −1.01935 −1.02533 −0.99268 −1.01445

8.39750 8.45383 8.43641 8.48567 8.50199 8.52158

4.19875 4.22691 4.21821 4.24283 4.25100 4.26079

0.23817 0.23658 0.23707 0.23569 0.23524 0.23470

3.21070 3.22335 3.19886 3.21750 3.25832 3.24634

−2.46527 −0.79243 −1.40739 −0.81523 −0.78674 −0.80756

1.22758 1.22903 1.21292 1.21998 1.24872 1.23671

0.81461 0.81365 0.82446 0.81969 0.80082 0.80860

0.7923 0.5289 1.5569 0.2180 0.8109 0.3920

−27849.92824 −27850.01679 −26795.38592 −24759.87966 −24759.81563 −24759.86986

B3LYP/SDD Level MAD_1 −5.36858 MAD_2 −5.40776 MAD_3 −5.28068 −5.36449 MAD_4 MAD_5 −5.40558 MAD_6 −5.40558

−2.41802 −2.34047 −2.15625 −2.21666 −2.28850 −2.25067

5.36858 5.40776 5.28068 5.36449 5.40558 5.40558

2.41802 2.34047 2.15625 2.21666 2.28850 2.25067

2.95055 3.06729 3.12444 3.14784 3.11709 3.15491

1.47528 1.53365 1.56222 1.57392 1.55854 1.57746

0.67784 0.65204 0.64012 0.63536 0.64162 0.63393

3.89330 3.87412 3.71847 3.79058 3.84704 3.82813

−2.94384 −0.82906 −1.06126 −0.85510 −0.80756 −0.80976

5.13727 4.89317 4.42543 4.56455 4.74793 4.64500

0.19466 0.20437 0.22597 0.21908 0.21062 0.21529

1.1595 0.8779 1.5062 0.3520 1.1343 0.6700

-28029.75580 −28029.81839 −26965.93713 −24919.81657 −24919.75834 −24919.80098

B3LYP/6-311 G Level MAD_1 −5.41320 MAD_2 −5.46164 MAD_3 −5.33320 −5.42300 MAD_4 MAD_5 −5.45538 MAD_6 −5.68450

−2.41095 −2.34700 −2.15815 −2.22945 −2.29911 −2.26373

5.41320 5.46164 5.33320 5.42300 5.45538 5.68450

2.41095 2.34700 2.15815 2.22945 2.29911 2.26373

3.00226 3.11464 3.17505 3.19355 3.15627 3.42077

1.50113 1.55732 1.58752 1.59678 1.57814 1.71039

0.66617 0.64213 0.62991 0.62626 0.63366 0.58466

3.91208 3.90432 3.74568 3.82622 3.87724 3.97412

−2.88244 −0.80813 −1.07710 −0.85159 −0.78468 −0.77736

5.09761 4.89422 4.41886 4.58423 4.76290 4.61698

0.19617 0.20432 0.22630 0.21814 0.20996 0.21659

1.1831 0.9859 1.3346 0.4767 1.2052 0.8021

−28032.96506 −28033.02299 −26968.82349 −24922.63003 −24922.57305 −24922.61599

B3LYP/6-31++G Level MAD_1 −5.47307 MAD_2 −5.52613 MAD_3 −5.40477 MAD_4 −5.48667 MAD_5 −5.52504 MAD_6 −5.53293

−2.49612 −2.43353 −2.25013 −2.31244 −2.39054 −2.35271

5.47307 5.52613 5.40477 5.48667 5.52504 5.53293

2.49612 2.43353 2.25013 2.31244 2.39054 2.35271

2.97695 3.09260 3.15464 3.17423 3.13450 3.18022

1.48847 1.54630 1.57732 1.58712 1.56725 1.59011

0.67183 0.64671 0.63399 0.63007 0.63806 0.62889

3.98459 3.97983 3.82745 3.89956 3.95779 3.94282

−2.79229 −0.70190 −0.97883 −0.71447 −0.68590 −0.68337

5.33331 5.12161 4.64375 4.79062 4.99732 4.88830

0.18750 0.19525 0.21534 0.20874 0.20011 0.20457

1.0181 0.8408 1.4107 0.3539 1.0898 0.6385

−28027.69518 −28027.76721 −26963.50983 −24917.86945 −24917.80588 −24917.85633

EHOMO

To determine the active sites of inhibitor molecules, properties such as neutral atomic charge, Fukui indices [92] and distribution of frontier orbital can be considered. In the predicting of atomic charges, Mulliken [93] population analysis is used. The atoms with the highest negative charge represent the high tendency on the metal surface. Molecules containing heteroatoms such as N, O, S exhibit high tendency for protonation in acidic medium. For this reason, the analysis of protonated forms of studied mono-azo dye derivatives. In the protonation process of molecules, we considered the electron density maps given in Fig. 7 for the molecules. Fig. 7 represents repartition of HOMO, LUMO densities, electrostatic potential structures of non-protonated and optimized structures of mono-azo dye (MAD_ 1–6) derivatives obtained from DFT at the B3LYP/6-31++G (d,p) basis set. In Tables 7 and 8, quantum chemical parameters calculated for protonated forms of studied molecules are presented. As stated above, proton affinity is a measure of electron donating abilities of molecules. From the light of data given in corresponding tables, the corrosion inhibition efficiency ranking in terms of proton affinities of the molecules obeys the order: MAD_ 1> MAD_ 3> MAD_ 2> MAD_ 4> MAD_ 5> MAD_ 6. The electrophilicity index (ω) is an important parameter that indicates the tendency of the inhibitor molecule to accept the electrons. Nucleophilicity (ε ) is physically the inverse of electrophilicity

(1/ω). For this reason, it should be stated that a molecule that have large electrophilicity value is ineffective against corrosion while a molecule that have large nucleophilicity value is a good corrosion inhibitor. Thus, for studied molecules, we can write the inhibition efficiency ranking as: MAD_ 3> MAD_ 4> MAD_ 6> MAD_ 5> MAD_ 2> MAD_ 1. Another important electronic parameter considered in corrosion studies is dipole moment (D). The dipole moment arises from nonuniform distribution of charges on the various atoms in a molecule and is used in the estimation of strength of intermolecular interactions. Some authors [80,94] reported that, the inhibition efficiency increases with increasing value of the dipole moment. On the other hand some authors [95,96] also reported that irregularities can be observed in the correlation between dipole moment with inhibition efficiency According to dipole moment values given in Tables 5 and 6, the inhibition efficiencies of mentioned compounds follow the order: MAD_ 3> MAD_ 1> MAD_ 5> MAD_ 2> MAD_ 6> MAD_ 4. 4.5. Molecular dynamics simulation (MDS) The use of the molecular dynamics simulations is a useful and modern tool [97,98] to investigate the interaction between inhibitors and metal surface. Thus in this study, molecular dynamics

470


Fig. 7. Repartition of HOMO, LUMO densities, ESP structures of non-protonated and optimized structures of mono-azo dye derivatives obtained from DFT at the B3LYP/631++G (d,p) basis set.


471

Table 6 Calculated quantum chemical parameters for neutral forms of studied mono-azo dye derivatives in aqueous phase (eV). ELUMO

I

A

E

η

σ

χ

PA

ω

ε

D (Debye)

Energy

HF/SDD Level MAD_1 -7.68592 MAD_2 −7.72837 MAD_3 −7.73435 −7.75857 MAD_4 MAD_5 −7.77245 MAD_6 −7.78714

1.10397 1.17989 1.39596 1.35269 1.28820 1.29201

7.68592 7.72837 7.73435 7.75857 7.77245 7.78714

−1.10397 −1.17989 −1.39596 −1.35269 −1.28820 −1.29201

8.78989 8.90826 9.13031 9.11126 9.06065 9.07915

4.39495 4.45413 4.56515 4.55563 4.53032 4.53958

0.22753 0.22451 0.21905 0.21951 0.22073 0.22028

3.29097 3.27424 3.16920 3.20294 3.24213 3.24757

−4.52573 −3.52915 −3.87447 −3.48341 −3.46674 −3.49946

1.23215 1.20345 1.10 0 05 1.12595 1.16011 1.16164

0.81159 0.83095 0.90905 0.88814 0.86198 0.86085

0.6161 0.1969 2.2876 0.5423 0.7104 0.4615

−27852.27331 −27852.35944 −26798.05968 −24762.11131 −24762.04208 −24762.10353


1.16466 1.26616 1.49011 1.44167 1.38017 1.38670

7.64020 7.66197 7.66714 7.69598 7.71394 7.72537

−1.16466 −1.26616 −1.49011 −1.44167 −1.38017 −1.38670

8.80486 8.92813 9.15725 9.13766 9.09412 9.11208

4.40243 4.46406 4.57862 4.56883 4.54706 4.55604

0.22715 0.22401 0.21841 0.21887 0.21992 0.21949

3.23777 3.19791 3.08852 3.12716 3.16689 3.16934

−4.53656 −3.50039 −3.87003 −3.46132 −3.45650 −3.41122

1.19061 1.14544 1.04168 1.07020 1.10282 1.10235

0.83990 0.87303 0.95999 0.93441 0.90677 0.90715

0.6803 0.2618 2.1642 0.4033 0.8127 0.4800

−27854.66763 −27854.75115 −26800.26935 −24764.21550 −24764.14116 −24764.21517


0.98805 1.12847 1.12139 1.12928 1.12466 1.13744

7.40945 7.70388 7.71367 7.73898 7.75531 7.76728

−0.98805 −1.12847 −1.12139 −1.12928 −1.12466 −1.13744

8.39750 8.83234 8.83506 8.86826 8.87996 8.90472

4.19875 4.41617 4.41753 4.43413 4.43998 4.45236

0.23817 0.22644 0.22637 0.22552 0.22523 0.22460

3.21070 3.28771 3.29614 3.30485 3.31533 3.31492

−4.48350 −3.45250 −3.85725 −3.41008 −3.41076 −3.42336

1.22758 1.22380 1.22971 1.23159 1.23777 1.23403

0.81461 0.81713 0.81320 0.81196 0.80790 0.81035

0.7923 0.1783 2.2556 0.60 0 0 0.7376 0.4154

−27849.92824 −27850.01679 −26795.38592 −24759.87966 −24759.81563 −24759.86986

B3LYP/SDD Level MAD_1 −5.60777 MAD_2 −5.63307 MAD_3 −5.56668 MAD_4 −5.62110 MAD_5 −5.63144 MAD_6 −5.65397

−2.75626 −2.66075 −2.51626 −2.56116 −2.61313 −2.59952

5.60777 5.63307 5.56668 5.62110 5.63144 5.65397

2.75626 2.66075 2.51626 2.56116 2.61313 2.59952

2.85150 2.97232 3.05042 3.05994 3.01831 3.05445

1.42575 1.48616 1.52521 1.52997 1.50916 1.52722

0.70138 0.67287 0.65565 0.65361 0.66262 0.65478

4.18201 4.14691 4.04147 4.09113 4.12229 4.12675

−4.82579 −3.32627 −3.51626 −3.29816 −3.29397 −3.32205

6.13334 5.78567 5.35449 5.46981 5.63005 5.57549

0.16304 0.17284 0.18676 0.18282 0.17762 0.17936

1.4742 0.7150 2.1846 0.4879 1.3813 0.8146

−28029.75580 −28029.81839 −26965.93713 −24919.81657 −24919.75834 −24919.80098

B3LYP/6-311 G Level MAD_1 −5.41320 MAD_2 −5.66627 MAD_3 −5.59879 −5.65784 MAD_4 MAD_5 −5.67035 MAD_6 −5.69103

−2.41095 −2.65095 −2.50592 −2.55843 −2.61068 −2.59354

5.41320 5.66627 5.59879 5.65784 5.67035 5.69103

2.41095 2.65095 2.50592 2.55843 2.61068 2.59354

3.00226 3.01532 3.09287 3.09940 3.05967 3.09750

1.50113 1.50766 1.54644 1.54970 1.52984 1.54875

0.66617 0.66328 0.64665 0.64529 0.65366 0.64568

3.91208 4.15861 4.05235 4.10814 4.14052 4.14229

−4.73191 −3.27212 −3.53988 −3.24570 −3.24570 −3.25979

5.09761 5.73540 5.30949 5.44517 5.60318 5.53948

0.19617 0.17436 0.18834 0.18365 0.17847 0.18052

1.1831 0.8175 2.0066 0.4617 1.5091 0.9308

−28032.96506 −28033.02299 −26968.82349 −24922.63003 −24922.57305 −24922.61599


−2.76742 −2.68987 −2.56850 −2.61313 −2.65993 −2.65014

5.67988 5.70464 5.65267 5.70491 5.71171 5.73784

2.76742 2.68987 2.56850 2.61313 2.65993 2.65014

2.91246 3.01477 3.08416 3.09178 3.05178 3.08770

1.45623 1.50739 1.54208 1.54589 1.52589 1.54385

0.68671 0.66340 0.64847 0.64688 0.65536 0.64773

4.22365 4.19725 4.11058 4.15902 4.18582 4.19399

−4.67288 −3.17497 −3.50733 −3.15513 −3.15418 −3.13883

6.12514 5.84354 5.47860 5.59466 5.74128 5.69665

0.16326 0.17113 0.18253 0.17874 0.17418 0.17554

1.1488 0.4636 2.1182 0.5661 1.2929 0.6888

−28027.69518 −28027.76721 −26963.50983 −24917.86945 −24917.80588 −24917.85633

EHOMO

simulation studies were performed to calculate the binding energies of these mono-azo dye derivatives on iron surface and to investigate whether there is a remarkable correlation between experimental inhibition efficiencies and binding energies for molecules considered in this study. The binding energies between Fe (110) surface and the six mono-azo dye (MAD_ 1–6) derivatives were obtained using Eq. (15). The close contacts between these compounds and Fe (110) metal surface as well as the best equilibrium adsorption configuration for the compounds considered are depicted in Fig. 8. The calculated binding energies are presented in Table 10. The obtained results given in Table 9 show that the binding energies calculated for the interactions between inhibitors and metal surface are very high. It is important to note that high binding energy leads to a more stable inhibitor/surface interaction [99]. The calculated binding energies are increased in the order arrangement: MAD_ 2> MAD_ 1> MAD_ 3> MAD_ 5> MAD_ 6> MAD_ 4. 4.6. Kinetic, adsorption isotherm and thermodynamics calculations Correlation between kinetic-thermodynamic model and Frumkin isotherm of the corrosion inhibition describe the behavior of the inhibitor molecules and provide information about the interaction of the inhibitor molecules with the electrode surface [100–102]. The adsorption of inhibitors at the metal-solution interface is rep-

resented as a substitution adsorption process between the inhibitor molecules (Inh(sol) ) and the water molecules on metallic surface (H2 Oads ):

Inh(sol) + x H2 Oads → Inh(ads) + H2 Osol

(28)

Where Inh(sol) and Inh(ads) are the inhibitor species dissolved in the aqueous solution and adsorbed onto the metallic surface, respectively. H2 O(ads) is the water molecules adsorbed on the metal surface and x is the ratio which represents the number of water molecules replaced by a single inhibitor molecule. Fitting of the gravimetric measurement data describes the mode of interaction occurred between the inhibitor molecules and the metal surface. Adsorption is a separation process involving two phases between which certain components can be described by two main types of interaction [100]: (1) physisorption which involves electrostatic forces between ionic charges at the metal/solution interface. The heat of adsorption is low and therefore this type of adsorption is stable only at relatively low temperatures and; (2) chemisorptions which involves charge sharing or charge transfer from the inhibitor molecules to the metal surface to form a coordinate type bond. In fact electron transfer is typically for transition metals having vacant low-energy electron orbital. Chemisorptions is typified by much stronger adsorption energy than physical adsorp-

472

L.H. Madkour et al. / Journal of the Taiwan Institute of Chemical Engineers 68 (2016) 461–480 Table 7 Calculated quantum chemical parameters for protonated forms of studied mono-azo dye derivatives in gas phase (eV). ELUMO

I

A

E

η

σ

χ

ω

ε

Energy

HF/SDD Level MAD_1 −10.65770 MAD_2 −9.92734 MAD_3 −9.67291 MAD_4 −10.81062 MAD_5 −10.95457 MAD_6 −10.93063

−3.80391 −1.95679 −1.72413 −1.93148 −1.96713 −1.95406

10.65770 9.92734 9.67291 10.81062 10.95457 10.93063

3.80391 1.95679 1.72413 1.93148 1.96713 1.95406

6.85379 7.97055 7.94878 8.87915 8.98745 8.97656

3.42689 3.98527 3.97439 4.43957 4.49372 4.48828

0.29181 0.25092 0.25161 0.22525 0.22253 0.22280

7.23080 5.94206 5.69852 6.37105 6.46085 6.44235

7.62856 4.42982 4.08529 4.57142 4.64454 4.62358

0.13109 0.22574 0.24478 0.21875 0.21531 0.21628

−27862.15251 −27860.55666 −26806.83463 −24770.33057 −24770.23378 −24785.09265


−3.66921 −1.91025 −1.61474 −1.88440 −1.91161 −1.90508

10.65661 9.91999 9.63155 10.77525 10.92763 10.88627

3.66921 1.91025 1.61474 1.88440 1.91161 1.90508

6.98739 8.00973 8.01681 8.89085 9.01602 8.98119

3.49370 4.00487 4.00840 4.44542 4.50801 4.49059

0.28623 0.24970 0.24948 0.22495 0.22183 0.22269

7.16291 5.91512 5.62314 6.32983 6.41962 6.39568

7.34283 4.36827 3.94418 4.50651 4.57093 4.55449

0.13619 0.22892 0.25354 0.22190 0.21877 0.21956

−27864.57638 −27862.97229 −26809.04854 −24772.46187 −24772.35746 −24772.43490


−3.76364 −2.96416 −2.42864 −2.96117 −2.98756 −2.98021

10.63565 9.92489 9.66937 10.81661 10.96002 10.93634

3.76364 2.96416 2.42864 2.96117 2.98756 2.98021

6.87202 6.96073 7.24073 7.85544 7.97245 7.95613

3.43601 3.48036 3.62037 3.92772 3.98623 3.97806

0.29104 0.28733 0.27622 0.25460 0.25086 0.25138

7.19965 6.44452 6.04900 6.88889 6.97379 6.95828

7.54289 5.96660 5.05341 6.04126 6.10022 6.08558

0.13258 0.16760 0.19789 0.16553 0.16393 0.16432

−27859.75351 −27858.16922 −26804.15331 −24768.05489 −24767.96237 −24768.03742


−6.86739 −5.44286 −5.17401 −5.45701 −5.50110 −5.48776

8.81411 8.20811 7.79503 8.65764 8.68404 8.70554

6.86739 5.44286 5.17401 5.45701 5.50110 5.48776

1.94672 2.76524 2.62102 3.20063 3.18294 3.21777

0.97336 1.38262 1.31051 1.60031 1.59147 1.60889

1.02737 0.72326 0.76306 0.62488 0.62835 0.62155

7.84075 6.82549 6.48452 7.05733 7.09257 7.09665

31.58001 16.84744 16.04300 15.56128 15.80441 15.65134

0.03167 0.05936 0.06233 0.06426 0.06327 0.06389

−28040.05964 −28038.00745 −26974.35839 −24928.03167 −24927.92590 −24927.97074

B3LYP/6-311 G Level MAD_1 −8.88622 MAD_2 −8.29355 MAD_3 −7.84565 MAD_4 −8.73800 MAD_5 −8.76703 MAD_6 −8.78962

−6.87501 −5.48831 −5.17673 −5.50463 −5.54545 −5.53484

8.88622 8.29355 7.84565 8.73800 8.76703 8.78962

6.87501 5.48831 5.17673 5.50463 5.54545 5.53484

2.01121 2.80524 2.66891 3.23336 3.22158 3.25478

1.00560 1.40262 1.33446 1.61668 1.61079 1.62739

0.99443 0.71295 0.74937 0.61855 0.62081 0.61448

7.88062 6.89093 6.51119 7.12132 7.15624 7.16223

30.87898 16.92720 15.88497 15.68433 15.89648 15.76068

0.03238 0.05908 0.06295 0.06376 0.06291 0.06345

−28043.20750 −28041.19112 −26977.26059 −24930.84162 −24930.71773 −24930.75335


−6.89297 −5.67797 −5.23225 −5.69974 −5.73512 −5.72804

8.90908 8.29736 7.89708 8.77574 8.80295 8.83261

6.89297 5.67797 5.23225 5.69974 5.73512 5.72804

2.01611 2.61939 2.66483 3.07600 3.06784 3.10457

1.00805 1.30969 1.33242 1.53800 1.53392 1.55229

0.99201 0.76354 0.75052 0.65020 0.65193 0.64421

7.90102 6.98767 6.56466 7.23774 7.26903 7.28033

30.96372 18.64080 16.17167 17.03021 17.22350 17.07262

0.03230 0.05365 0.06184 0.05872 0.05806 0.05857

−28037.84747 −28035.82911 −26971.84866 −24925.94392 −24925.85178 −24925.89970

EHOMO

tion. Such a bond is therefore more stable at higher temperatures. Basic information on the adsorption of inhibitor on metal surfaces can be provided by adsorption isotherm. Attempts were made to fit experimental data to various isotherms including Frumkin, Langmuir, Temkin, Freundlich, Bockris–Swinkels and Flory–Huggins isotherms. All these isotherms are of the general form [103]:

f (θ , x ) exp (−2αθ ) = KadsC

(29)

where f (θ , x) is the configurational factor which depends on the physical mode and the assumptions underlying the derivation of the isotherm, θ the degree of surface coverage, C the inhibitor concentration, x the size factor ratio, α the molecular interaction parameter, and Kads the equilibrium constant of the inhibitor adsorption process. In this study, correlation coefficient (R2 ) was used to determine the best fit isotherm which was obtained from Frumkin adsorption isotherm. According to this isotherm, θ is related to the inhibitor concentration by the following equation [104]:

exp (−2αθ ) = KadsC

(30)

where the molecular interaction parameter α can have both positive and negative values. Positive values of α indicates attraction forces between the adsorbed molecules while negative values indicate repulsive forces between the adsorbed molecules [104]. Upon

rearrangement of Eq. (30), the following equation is obtained:

θ = [1/(−2α )] ln (KadsC )

(31)

If the parameter f is defined as:

f = −2α

(32)

where f is the heterogeneous factor of the metal surface describing the molecular interactions in the adsorption layer and the heterogeneity of the metal surface. Eq. (32) clearly shows that the sign between f and α is reverse, that is, if α < 0, then f > 0; if α >0, then f < 0. Accordingly, if f > 0, mutual repulsion of molecules occurs and if f < 0 attraction takes place. If Eq. (32) is substituted into Eq. (31), then the Frumkin isotherm equation [105] has the following form:

θ = (1/ f ) ln (KadsC )

(33)

(θ ) could be calculated by the following relationship [106]:

θ = IE (% )/100

(34)

Eq. (33) can be transformed into:

θ = (1/ f ) ln Kads + (1/ f ) ln C

(35)

Eq. (35) is a different form of the Frumkin isotherm. The plot of

θ versus log C (Fig. 3) gives an S-shaped graph, suggest that the


473

Table 8 Calculated quantum chemical parameters for protonated forms of studied mono-azo dye derivatives in aqueous phase (eV). ELUMO

I

A

E

η

σ

χ

ω

ε

Energy

HF/SDD Level MAD_1 −8.03395 MAD_2 −8.27614 MAD_3 −7.89490 MAD_4 −8.50662 MAD_5 −8.53193 MAD_6 −8.55206

0.81907 0.84546 0.90533 0.92655 0.90206 0.91921

8.03395 8.27614 7.89490 8.50662 8.53193 8.55206

−0.81907 −0.84546 −0.90533 −0.92655 −0.90206 −0.91921

8.85302 9.12160 8.80023 9.43317 9.43399 9.47127

4.42651 4.56080 4.40012 4.71659 4.71699 4.73563

0.22591 0.21926 0.22727 0.21202 0.21200 0.21116

3.60744 3.71534 3.49479 3.79003 3.81493 3.81643

1.46997 1.51330 1.38786 1.52275 1.54269 1.53782

0.68029 0.66081 0.72053 0.65671 0.64822 0.65027

−27864.15904 −27863.24859 −26809.29415 −24772.95472 −24772.86882 −24772.96299

HF/6-311 G Level MAD_1 −8.0 0 075 MAD_2 −8.23477 MAD_3 −7.84102 MAD_4 −8.45192 MAD_5 −8.48158 MAD_6 −8.49682

−0.70832 0.88465 1.00166 0.98098 0.95921 0.95812

8.0 0 075 8.23477 7.84102 8.45192 8.48158 8.49682

0.70832 −0.88465 −1.00166 −0.98098 −0.95921 −0.95812

7.29244 9.11942 8.84268 9.43290 9.44079 9.45494

3.64622 4.55971 4.42134 4.71645 4.72040 4.72747

0.27426 0.21931 0.22618 0.21202 0.21185 0.21153

4.35454 3.67506 3.41968 3.73547 3.76119 3.76935

2.60023 1.48102 1.32247 1.47926 1.49845 1.50271

0.38458 0.67521 0.75616 0.67601 0.66736 0.66547

−27866.56419 −27865.61154 −26811.49938 −24775.03682 −24774.95766 −24774.98639


−0.78288 0.79431 0.86206 0.86696 0.84193 0.85798

8.00375 8.24484 7.87585 8.47641 8.49927 8.52077

0.78288 −0.79431 −0.86206 −0.86696 −0.84193 −0.85798

7.22087 9.03915 8.73792 9.34337 9.34120 9.37875

3.61044 4.51957 4.36896 4.67169 4.67060 4.68938

0.27697 0.22126 0.22889 0.21406 0.21411 0.21325

4.39331 3.72527 3.50689 3.80473 3.82867 3.83139

2.67297 1.53528 1.40747 1.54933 1.56926 1.56520

0.37412 0.65135 0.71050 0.64544 0.63724 0.63890

−27861.77174 −27860.82929 −26806.60317 −24770.64974 −24770.58639 −24770.65322


−4.05943 −3.00770 −2.93940 −2.94892 −2.97967 −2.99055

6.17839 6.23935 5.82383 6.26411 6.26329 6.28969

4.05943 3.00770 2.93940 2.94892 2.97967 2.99055

2.11897 3.23165 2.88443 3.31519 3.28362 3.29913

1.05948 1.61582 1.44221 1.65759 1.64181 1.64957

0.94386 0.61888 0.69338 0.60328 0.60908 0.60622

5.11891 4.62352 4.38161 4.60652 4.62148 4.64012

12.36604 6.61488 6.65592 6.40084 6.50443 6.52618

0.08087 0.15117 0.15024 0.15623 0.15374 0.15323

−28041.94159 −28040.50466 −26976.81339 −24930.47473 −24930.41231 −24930.48303

B3LYP/6-311 G Level MAD_1 −6.22302 MAD_2 −6.28452 MAD_3 −5.87607 MAD_4 −6.31173 MAD_5 −6.31364 MAD_6 −6.33813

−4.05317 −3.01885 −2.99518 −2.96498 −2.99436 −3.00280

6.22302 6.28452 5.87607 6.31173 6.31364 6.33813

4.05317 3.01885 2.99518 2.96498 2.99436 3.00280

2.16985 3.26566 2.88089 3.34675 3.31927 3.33533

1.08493 1.63283 1.44045 1.67338 1.65964 1.66766

0.92172 0.61243 0.69423 0.59759 0.60254 0.59964

5.13809 4.65169 4.43563 4.63835 4.65400 4.67046

12.16673 6.62597 6.82941 6.42841 6.52544 6.54006

0.08219 0.15092 0.14643 0.15556 0.15325 0.15290

−28045.05697 −28043.65511 −26979.72337 −24933.23573 −24933.17875 −24933.23578

B3LYP/6-31±+G Level MAD_1 −6.22003 MAD_2 −6.29921 MAD_3 −5.94465 MAD_4 −6.33377 MAD_5 −6.32996 MAD_6 −6.36479

−4.07439 −3.03872 −3.08389 −2.98511 −3.01804 −3.01749

6.22003 6.29921 5.94465 6.33377 6.32996 6.36479

4.07439 3.03872 3.08389 2.98511 3.01804 3.01749

2.14563 3.26049 2.86076 3.34866 3.31192 3.34730

1.07282 1.63025 1.43038 1.67433 1.65596 1.67365

0.93213 0.61340 0.69912 0.59725 0.60388 0.59750

5.14721 4.66897 4.51427 4.65944 4.67400 4.69114

12.34776 6.68587 7.12351 6.48331 6.59625 6.57450

0.08099 0.14957 0.14038 0.15424 0.15160 0.15210

−28039.72806 −28038.30218 −26974.37716 −24928.38458 −24928.32006 −24928.35516

EHOMO

adsorption of the investigated (MAD_1-6) derivatives on the iron obeyed the Frumkin adsorption isotherm. Straight lines of CI nh /θ versus CInh plots as shown in Fig. 9, indicate that the adsorption of the inhibitor molecules on the metal surface obeyed Frumkin adsorption model, this isotherm can be represented as:

CInh /θ = 1/Kads + CInh

(36)

The strong correlation coefficients of the fitted curves are around unity (r > 0.985). This reveals that the inhibition tendency of the inhibitors is due to the adsorption of the molecules on the Fe surface [107] (Table 11). The slopes of the CInh /θ versus CInh plots are close to ≡ 1.3 which indicates the ideal simulating and expected from Frumkin adsorption isotherm [107]. Kads values were

calculated from the intercepts of the straight lines on the CInh /θ axis [108]. The relatively high values of the adsorption equilibrium constant (Kads ) as given in Table 11, reflect the high adsorption ability of these molecules on iron surface. The value of Kads is related to the standard free energy of adsorption (G°ads ) by the following Eq. (37).

Kads = (1/55.5) exp(−DG◦ads /RT )

(37) mol−1 K−1 )

where R is the universal molar gas constant (kJ and T is the absolute temperature (K). The value of 55.5 is the molar concentration of water in solution expressed in mol L−1 .The calculated values of G°ads and Kads of the tested (MAD_1-6) inhibitors were listed in Table 11.

Table 9 Calculated fractions of electron transferred from the inhibitor molecules to metallic surface. Inhibitor

EHOMO (eV)

ELUMO (eV)

I (eV)

A (eV)

χ (eV)

η (eV)

࢞N

MAD_1 MAD_2 MAD_3 MAD_4 MAD_5 MAD_6

−5.47307 −5.52613 -5.40477 −5.48667 −5.52504 −5.53293

−2.49612 −2.43353 −2.25013 −2.31244 −2.39054 −2.35271

5.47307 5.52613 5.40477 5.48667 5.52504 5.53293

2.49612 2.43353 2.25013 2.31244 2.39054 2.35271

3.98459 3.97983 3.82745 3.89956 3.95779 3.94282

1.48847 1.54630 1.57732 1.58712 1.56725 1.59011

1.012 0.976 1.005 0.976 0.970 0.961

474


Fig. 8. Equilibrium adsorption configurations of the studied synthesized mono-azo dye (MAD_ 1-6) derivatives on Fe(110) surface.

Fig. 9. Relation between CInh and CInh /θ of the synthesized (MAD_1) and (MAD_6) for iron in 2.0 M HNO3 at 303 K.

Table 10 Interaction and binding energies of studied inhibitors adsorbed on Fe(110) surface. Systems

Ebinding (kcal mol−1 )

Fe(110) + MAD_1 Fe(110) + MAD_2 Fe(110) + MAD_3 Fe(110) + MAD_4 Fe(110) + MAD_5 Fe(110) + MAD_6

174.6 177.7 164.1 156.4 158.7 157.1

applicable in Fig. 10. As seen, satisfactory linear relation is observed for the studied (MAD_1-6) compounds. Hence, the suggested model fits the obtained experimental data. The slope of such lines is the number of inhibitor molecules occupying a single active site, (y) and the intercept is the binding constant (log K’). As mentioned, 1/y gives the number of active sites occupied by a single organic molecule and K’y is the equilibrium constant for the adsorption process. The binding constant (Kb ) corresponding to that obtained from the known adsorption isotherms curve fitting is given by the following equation: Kb = K (1/y )

The kinetic parameters calculated from Kinetic-thermodynamic model proposed by El-Awady et al. [109,110] is given in Eqs. (38) and (39) as following:

q/(1 − q ) = K [I]y

(38)

Or log (θ /1 − θ ) = log K + y log [I]

(39)

where y is the number of inhibitors molecules [I] occupying one active site, and K’ is a constant, if relationship (39) is plotted and

(40)

Table 11 comprises the values of 1/y and Kb for the studied mono-azodye inhibitors. This table show that the number of active sites occupied by one molecule is (1/y ≡ 2 - 10). Values of 1/y greater than unity implies the formation of multilayer of the inhibitor molecules on the metal surface, whereas, values of 1/y less than unity indicates that a given inhibitor molecule will occupy more than one active site [64]. According to the proposed kinetic-thermodynamic model, the adsorption takes place via formation of multilayer of the inhibitor molecules on the iron


475

Table 11 Fitting parameters of the kinetic-thermodynamic model and the Frumkin adsorption isotherms of the synthesized (MAD_1-6) inhibitors in 2.0 M HNO3 and 2.0 M NaOH solutions at 303 ± 1 K. Inhibitor type

MAD_ 1 MAD_ 2 MAD_ 3 MAD_ 4 MAD_ 5 MAD_ 6

Medium

2.0 M 2.0 M 2.0 M 2.0 M 2.0 M 2.0 M 2.0 M 2.0 M 2.0 M 2.0 M 2.0 M 2.0 M

HNO3 NaOH HNO3 NaOH HNO3 NaOH HNO3 NaOH HNO3 NaOH HNO3 NaOH

Kinetic model

Frumkin isotherm

1/y

Kb

−G°ads kJ mol−1

−f

Kads

−G°ads kJ mol−1

8.57 2.86 8.98 2.71 9.50 1.99 8.40 3.45 8.86 5.39 9.57 4.44

2.16 × 108 4707.10 2.01 × 108 11636.71 1.92 × 108 4042.06 4.48 × 107 1614.81 4.43 × 107 1164.87 7.52 × 107 980.97

38.21 11.18 38.03 13.46 37.91 10.80 34.25 8.49 34.22 7.67 35.55 7.23

23.42 40.46 23.70 36.70 24.08 41.44 24.52 44.03 24.85 45.86 25.03 50.73

36307 8394 34593 9772 32359 7568 29991 6745 28444 6151 27669 5058

16.33 12.64 16.20 13.03 16.04 12.38 15.81 12.09 15.71 11.86 15.64 11.37

Fig. 10. Application of kinetic-thermodynamic model on (MAD_1-6) inhibitors of iron in (a) 2.0 M HNO3 acid and (b) 2.0 M Na OH at 303 K.

electrode surface. The slope values do not equal unity (gradient slopes MAD_ 2> MAD_ 3> MAD_ 4> MAD_ 5> MAD_ 6, the data obtained from quantum chemical calculations and molecular dynamic simulations (MDS) are tabulated in Tables 5–10). Finally, we remark that we do not know the real structure of mono-azo dye films; instead these arguments are used to demonstrate the differences in inhibition efficiency of these molecules. In general, the adsorption of (MAD_1–6) molecules at the iron electrode surface depends on the molecular size, charge distribution and deformability of the active center as well as the charge on the metal surface undergoing corrosion. Thus, the increased formation of mono-azo dye-metal complexes leads to the formation of an insoluble film of the complex on the metal surface, which furnishes an additional inhibitive property to that of the investigated (MAD_1–6). Proposed structure of the MAD-Fe complex compounds formed between mono-azo dye inhibitors and Fe ions in acidic and alkaline corrosive solutions was shown in Fig. 11. Skeletal representation of the proposed mode of adsorption of the investigated (MAD_1- 6) inhibitors is shown in Fig. 12, which clearly indicates that, iron has greater affinity towards aromatic moieties and were found to adsorb benzene rings in a flat orientation. The substituent (MAD_3) shows the best performance (Fig. 13). This can be explained on the basis that compound (MAD_3) can be chemisorbed as a tri dentate surface ligand. The surface coordination is through the oxygen atoms from both the OH and OCH3 groups which raises the possibility of transferring the unshared electron of the molecule to iron in comparison to other derivatives and therefore results in a better adsorption [130]. It was concluded that, the mode of adsorption depends on the affinity of the iron metal towards the π -electron clouds of the ring system [66]. From experimental measurements, the order of increasing the corrosion inhibition efficiency IE (%) of (MAD_1–6) inhibitors on iron in acidic and alkaline solutions was follows the arrangement: MAD_ 1> MAD_ 2> MAD_ 3> MAD_ 4> MAD_ 5> MAD_ 6. (MAD_ 1) is the most efficient inhibitors of the investigated (MAD_1-6). This seems to be adsorbed on the iron surface through each of adsorption oxygen centers and π -electron system of the benzene rings. It was found that, substituted phenyl rings in the α position of mono-azo derivative increases longitudinal polarization of the π -electron clouds. Thus, the adsorbed species lie flat on the iron surface causing a higher inhibitive effect value than the others derivatives. When the phenyl rings lies in the β -position for compound (MAD_ 2) this is because transverse polarization and consequently their adsorption are relatively decreased on the metal surface. The adsorption of (MAD_ 3) inhibitor depends on the three oxygen adsorption sites. Methyl (CH3 -) group is more basic than the H-atom, so its presence within the azo dyes molecule causing increasing the localization of the π -electron clouds on the Fe metal surface depending on its position as follows: p > o > m-position. Thus, compound (MAD_ 4) lie before (MAD_ 5) and the compound (MAD_ 6) comes at the end of the investigated (MAD_1-6) derivatives. 5. Conclusions The six mono-azo dyes are effective inhibitors of corrosion of iron exposed to 2.0 M HNO3 and 2.0 M NaOH solutions, respectively, at 303 K. The polarization curves showed that the compounds were mixed-type inhibitors in acidic and only cathodic in alkaline solutions. Correlation between kinetic-thermodynamic

478


Fig. 12. Skeletal representation of the proposed mode of adsorption of six mono-azo dye (MAD_1–6) derivatives on the iron surface.

Acknowledgments I gratefully acknowledge Faculties of Science, Departments of Chemistry at Baljarashi, Al-Baha University, (Saudi Arabia), Cumhuriyet University (Turkey), and Tongren University (China), for the financial assistance and facilitation of our research.

References

Fig. 13. Skeletal representation of the proposed mode of adsorption of mono-panisidine (MAD_3) on the iron surface.

model and Frumkin adsorption isotherm of the corrosion inhibition is described. Data obtained from quantum chemical calculations using DFT at HF/SDD, HF/6-311 G, HF/6-31++G, B3LYP/SDD, B3LYP/6-311 G and B3LYP/6-31++G methods were correlated to the inhibitive effect of the compounds. Molecular dynamic simulations (MDS) employing Monte Carlo sampling approach were performed using Material Studio software program to search for the most stable configuration and adsorption energies for the interaction of the (MAD_1–6) corrosion inhibitors on Fe (110) interface. Experimental and theoretical calculations are in good agreement. Our approach will be help full for quick prediction of a potential inhibitor from a lot of similar inhibitors and subsequently in their rational design and synthesis for corrosion inhibition application.

[1] Prabhu RA, Venkatesha TV, Shanbhag AV, Praveen BM, Kulkarni GM, Kalkhambkar RG. Quinol-2-thione compounds as corrosion inhibitors for mild steel in acid solution. Mater Chem Phys 2008;108(2):283–9. [2] Madkour LH, Elroby SK. Inhibitive properties, thermodynamic, kinetics and quantum chemical calculations of polydentate Schiff base compounds as corrosion inhibitors for iron in acidic and alkaline media. Int J Ind Chem 2015;6(3):165–84. [3] Madkour LH, Elroby SK. J Corr Sci Eng (JCSE) 2014:17. [4] Madkour LH, Zinhome UA. J Corr Sci Eng (JCSE) 2010:13. [5] Madkour LH, Elroby SK. Stand Sci Res Essays 2014;2(13):680–704. [6] Doner A, Solmaz R, Ozcan M, Kardas G. Corros Sci 2011;53:2902–13. [7] Solmaz R, Kardas GC, Ulha M, Yazici B, Erbil M. Investigation of adsorption and inhibitive effect of 2-mercaptothiazoline on corrosion of mild steel in hydrochloric acid media. Electrochim Acta 2008;53(20):5941–52. [8] Madkour LH, Hassanein AM, Ghoneim MM, Eid SA. Inhibition Effect of hydantoin compounds on the corrosion of iron in nitric and sulfuric acid solutions. Monatshefte fiir Chemie 2001;132:245–58. [9] Madkour LH, Elmorsi MA, Ghoneim MM. Monatshefte fiir Chemie 1995;126:1087–95. [10] Madkour LH, Ghoneim MM. Inhibition of the corrosion of 16/14 austenitic stainless steel by oxygen and nitrogen containing compounds. Bull Electrochem 1997;13(1):1–7. [11] Solmaz R, Mert ME, Kardas G, Yazici B, Erbil M. Adsorption and corrosion inhibition Effect of 1,10-Thiocarbonyldiimidazole on mild steel in H2 SO4 solution and synergistic effect of iodide ion. Acta Phys Chim Sinica 2008;24(7):1185–91. [12] Altunbas¸ E, Solmaz R, Kardas¸ G. Mater Chem Phys 2010;121:354–8. [13] Kaya S, Kaya C, Guob L, Kandemirli F, Tüzün B, Ug˘ urlu I˙ , et al. Quantum chemical and molecular dynamics simulation studies on inhibition performances of some thiazole and thiadiazole derivatives against corrosion of iron. J Mol Liq 2016;219:497–504. [14] Solmaz R, S¸ ahin EA, Doner A, Kardas¸ G. Corros Sci 2011;53:3231–40. [15] Al-Doori1 HH, Shihab MS. J Al-Nahrain Univ 2014;17(3):59–68.

L.H. Madkour et al. / Journal of the Taiwan Institute of Chemical Engineers 68 (2016) 461–480 [16] Hamani H, Douadi T, Al-Noaimi M, Issaadi S, Daoud D, Chafaa S. Corros Sci 2014;88:234–45. [17] Abdul-Nabi AS, Jasim EQ. J Basrah Res (Sci) 2013;3(3):82–106 9. [18] H. Shokry, R. Shaha, E.M. Mabrouk, J Adv Chem (2013) 5 (2) 701–718 [19] Nagiub AM, Mahross MH, Khalil HFY, Mahran BNA, Yehia MM, El-Sabbah MMB. Portugaliae Electrochimica Acta 2013;31(2):119–39. [20] Abdallah M, Moustafa E. Inhibition of acidic corrosion of carbon steel by some mono and bis azo dyes based on 1,5 dihydroxynaphihalene. Anal Chim 2004;94(601). [21] Touhami F, Aouniti A, Abed Y, Hammouti B, Kertit S, Ramdani A, Elkacemi K. Corrosion inhibition of armco iron in 1 M HCl media by new bipyrazolic derivatives. Corros Sci 20 0 0;42:929–40. [22] E. Kraka, D. Cremer, Computer design of anticancer drugs, J Am Chem Soc 122 (20 0 0) 8245–8264. [23] Kraka E, Cremer D. Structure and stability of enediynes containing hetero atoms – A quantum chemical investigation. J Mol Struc-Theochem 20 0 0;506:19–211. [24] Madkour LH, Elshamy IH. Experimental and computational studies on the inhibition performances of benzimidazole and its derivatives for the corrosion of copper in nitric acid. Int J Ind Chem 2016;7(2):195–221. [25] Parac M, Grimme S. J Phys Chem A 2003;106:6844–50. [26] Madkour LH, Issa RM, El-Ghrabawy IM. J Chem Res (S) 1999;408-409:1701–26 & (M). [27] ASTM G 31-72. Standard Guide Practice for Laboratory Immersion Corrosion Testing of Metals. Immersion corrosion evaluations using G31-72 provide a straightforward and simple method of determining the rate of corrosion in aqueous solutions. It is most appropriate for determine the corrosivity of liquids in static applications. [28] Li XH, Deng SD, Mu GN, Fu H, Yang FZ. Corros Sci 2008;50:420–30. [29] Li XH, Deng SD, Fu H, Mu GN. Corros Sci 2008;50:2635–45. [30] Vracar LM, Drazic DM. Corros Sci 2002;44:1669–80. [31] Mylius FZ. Metallkunde 1922;14:233. [32] Aziz K, Shams El Din AM. A simple method for thedetermination of the inhibition efficiency of surfactants. Corros Sci 1965;5(7):489–501. [33] Mylius FZ. Eine kritische Zusammenfassung Metallkunde 1924;16:81. [34] Fouda AS, Elasmy AA. Efficiency of some phenylthiosemicarbazide derivatives in retarding the dissolution of Al in NaOH solution. Monatshefte fu¨r Chemie Chem Mon 1987;118(6–7):709–16. [35] Fouda AS, Madkour LH, Elshafei AA, Elasklany AH. Mat.-wiss. u. Werkstofftech 1995;26:342–6. [36] Adamo C, Jacquemin D. The calculations of excited-state properties with time dependent density functional theory. Chem Soc Rev 2013;42:845–56. [37] M.J. Frisch, G.W. Trucks, H.B. Schlegel, G.E. Scuseria, M.A. Robb, J.R. Cheeseman Jr., et al., Gaussian 03 W, Gaussian Inc., Wallingford, CT, 2004. [38] R.D. Dennington, T.A. Keith, C.M. Millam GaussView 5.0 Wallingford, CT; (2009). [39] Chermette H. Chemical reactivity indexes in density functional theory. J Comp Chem 1999;20:129–54. [40] Parr RG, Chattaraj PK. Principle of maximum hardness. J Am Chem Soc 1991;113:1854–5. [41] Iczkowski RP, Margrave JL. Electronegativity. J Am Chem Soc 1961;83:3547–51. [42] Yang W, Lee C, Ghosh SK. Molecular softness as the average of atomic softnesses: companion principle to the geometric mean principle for electronegativity equalization. J Phys Chem 1985;89:5412–14. [43] Yang W, Parr RG. Hardness, softness and the Fukui function in the electronic theory of metals and catalysis. Proc Natl Acad Sci 1985;82:6723–6. [44] Koopmans T. Ordering of wave functions and eigen-energies to the individual electrons of an atom. Physica 1933;1:104–13. [45] Islam N, Ghosh DC. A new algorithm for the evaluation of the global hardness of polyatomic molecules. Int J Quant Chem 2011;109:917–31. [46] Kaya C. Inorganic Chemisry 1 and 2. Ankara: Palme Publishing; 2011. [47] Parr RG, Sventpaly L, Liu S. Electrophilicity index. J Am Chem Soc 1999;121:1922–4. [48] Chattaraj PK, Sarkar U, Roy DR. Electrophilicity index. Chem Rev 2006;106:2065–91. [49] Frenkel D, Smit B. Understanding molecular simulation: From algorithms to applications. 2nd ed. San Diego: Academic Press; 2002. [50] Kirkpatrick S, Gelatt CD, Vecchi MP. Optimization by simulated annealing. Science 1983;220:671–80. [51] Guo L, Zhang ST, Lv TM, Feng WJ. Comparative theoretical study on the corrosion inhibition properties of benzoxazole and benzothiazole. Res Chem Intermed 2015;41:3729–42. [52] Sun H. COMPASS: an ab initio force-field optimized for condensed-phase applications overview with details on alkane and benzene compounds. J Phys Chem B 1998;102:7338–64. [53] Kaya S, Tüzüna B, Kaya C, Obot IB. J Taiwan Inst Chem Eng 2015;0 0 0:1–8. [54] Behpour M, Ghoreishi SM, Mohammadi N, Soltani N, Salavati-Niasari M. Corros Sci 2010;52:4046–57. [55] Obi-Egbedi NO, Obot IB. Corros Sci 2011;53:263–75. [56] Musa AY, Khadom AA, Kadhum AH, Mohamad AB, Takriff MS, Taiwan J. Inst Chem Eng 2010;41:126–8. [57] Khadom AA, Yaro AS, Kadum AH, Taiwan J. Inst Chem Eng 2010;41:122–5. [58] Bouklah M, Hammouti B, Lagrenee M, Bentiss F. Corros Sci 2006;48:2831–42. [59] Chitra S, Parameswari K, Sivakami C, Selvaraj A. Chem Eng Res Bull 2010;14:1–6.

[60] [61] [62] [63] [64] [65] [66] [67] [68]

[69] [70] [71] [72] [73] [74] [75] [76] [77] [78] [79] [80]

[81] [82] [83] [84]

[85] [86] [87] [88] [89] [90] [91] [92] [93]

[94] [95] [96] [97]

[98]

[99]

[100] [101] [102] [103] [104] [105] [106] [107] [108] [109] [110] [111] [112]

479

Zou Y, Wang J, Zheng YY. Corros Sci 2011;53:208–16. El-Naggar MM. Corros Sci 2007;49:2226–36. Umoren SA, Ebenso EE. Mater Chem Phys 2007;106:387–93. Emregul KC, Hayvalı M. Corros Sci 2006;48:797–812. Frumkin AN. Z Phys Chem 1925;116:466–84. Babic- Samardzija K, Khalid KF, Heckerman. J App Surf Sci 2005;240(I-4):327. Sankarapapavinasam S, Ahmed MF. J Appl Electrochem 1992;22:390. A. El-Sayed, D Kagaku, 66(2) (1998) 176. Ahamad I, Prasad R, Quraishi MA. Thermodynamic, electrochemical and quantum chemical investigation of some Schiff bases as corrosion inhibitors for mild steel in hydrochloric acid solutions. Corros Sci 2010;52(3):933–42. Avci G. Colloid Surf. A: Physicochem Eng Aspec 2008;317:730–6. Khaled KF, Hackenman N. Electrochim Acta 2004;49:485–95. Abd El-Maksoud SA, Fouda AS. Mater Chem Phys 2005;93:84–90. Abdel-Rehim SS, Ibrahim MAM, Khaled KF. Mater Chem Phys 2001;70:268–73. Ferreira ES, Giancomelli C, Giacomelli FC, Spinelli A. Mater Chem Phys 2004;83:129–34. Li WH, He Q, Pei CL, Hou BR. J Appl Electrochem 2008;38:289–95. Quartarone G, Bonaldo L, Tortato C. Appl Surf Sci 2006;252:8251–7. Chauhan LR, Gunasekaran G. Corros Sci 2007;49:1143–61. Hegazy MA. Corros Sci 2009;51:2610–18. da Silva AB, D’Elia E, da Cunha Ponciano Gomes JA. Corros Sci 2010;52:788–93. Bayol E, Kayakirilmaz K, Erbil M. Mater Chem Phys 2007;104:74–9. Li X, Deng S, Fu H, Li T. Adsorption and inhibition effect of 6-benzylaminopurine on cold rolled steel in 1.0 M HCl. Electrochim Acta 2009;54(16):4089–98. Becke AD. Phys Rev 1988;38:3098–100. Lee C, Yang W, Parr RG. Phys Rev 1988;37:785–9. Hehre WJ, Radom L, Schleye PvR, Pople JA. Ab initio molecular orbital theory. New York: Wiley; 1989. Obot IB, Macdonald DD, Gasem ZM. Density functional theory (DFT) as a powerful tool for designing new organic corrosion inhibitors. Part 1: An overview. Corros Sci 2015. Pearson RG. Hard and soft acids and bases. J Am Chem Soc 1963;85(22):3533–9. Pearson GR. The principle of maximum hardness. Acc Chem Res 1993;26(5):250–5. Parr RG, Chattaraj PK. Principle of maximum hardness. J Am Chem Soc 1991;113(5):1854–5. Martinez S. Mater Chem Phys 2002;77:97–102. Sanderson RT. Chemical bond and bond energy. New York: Academic Press; 1976. Sanderson RT. Electronegativities in inorganic chemistry. J Chem Edu 1954;31:2–7. Awad MK, Mustafa MR, Elnga MMA. J Mol Struct (Theochem) 2010;959:66–74. Fukui K. Role of frontier orbitals in chemical reactions. Science 1982;218:747–54. Rodriguez-Valdez LM, Martínez-Villafañe A, Glossman-Mitnik D. Computational simulation of the molecular structure and properties of heterocyclic organic compounds with possible corrosion inhibition properties.. J Mol Struct THEOCHEM 2005;713(1):65–70. Li X, Deng S, Fu H. Prog Org Coat 2010;67:420–6. Khaled KF, Babíc-Samard_zija K, Hackerman N. Electrochim Acta 2005;50:2515–20. Bereket G, Hür E, Ögretir C. Theochem. J Mol Struct 2002;79:578. Musa YAhmed, Ramzi Jalgham TT, Abu Bakar Mohamad M. Molecular dynamic and quantum chemical calculations for phthalazine derivatives as corrosion inhibitors of mild steel in 1 M HCl.. Corros Sci 2012;56:176–83. BObot I, Obi-Egbedi NO, Ebenso EE, Afolabi AS, Oguzie EE. Experimental, quantum chemical calculations, and molecular dynamic simulations insight into the corrosion inhibition properties of 2-(6-methylpyridin-2-yl) oxazolo [5, 4-f][1, 10] phenanthroline on mild steel. Res Chem Intermed 2013;39(5):1927–48. John S, Joy J, Prajila M, Joseph A. Electrochemical, quantum chemical and molecular dynamics studies on the interaction of 4-amino-4H,3,5di(methoxy)-1,2,4-triazole (ATD), BATD, and DBATD on copper metal in 1 N H2 SO4 . Mater Corros 2011;62:1031–41. Noor EA, Al-Moubaraki AH. Mater Chem Phys 2008;110:145–54. Bentiss F, Jama C, Mernari B, El Attari H, El Kadi L, Lebrini M, et al. Corros Sci 2009;51:1628–35. Valcarce MB, Vazquez M. Mater Chem Phys 2009;115:313–21. Sahin M, Bilgic S, Yilmaz H. Appl Surf Sci 2002;195:1–7. Umoren SA, Ogbobe O, Igwe IO, Ebenso EE. Corros Sci 2008;50:1998–2006. Khaled KF. Appl Surf Sci 2004;230:307. Solomon MM, Umoren SA, Udosoro II, Udoh AP. Corros Sci 2010;52(4):1317–25. Badawy WA, Ismail KM, Fathi AM. Electrochim Acta 2006;51:4182–9. Abdallah M. Corros Sci 2002;44:717–28. El-Awady AA, Abd-El-Nabey BA, Aziz SG, Khalifa M, Al-Ghamedy HA. International J Chem 1990;1(4):169–79. El-Awady AA, Abd-El-Nabey BA, Aziz SG. J Electrochem Soc 1992;139:2149. Fouda AS, Mousa MNH, Taha FI, El-Neanaa AI. J Corrosion Sci 1986;26:719. Langmuir I. J Am Chem Soc 1947;39.

480 [113] [114] [115] [116] [117] [118] [119] [120] [121] [122] [123] [124]

[125] [126]

[127] [128]

[129]

[130]

L.H. Madkour et al. / Journal of the Taiwan Institute of Chemical Engineers 68 (2016) 461–480 Smialowska Szkarska-, Dus B. Corrosion 1967;23:130. Tang L, Li X, Si Y, Mu G, Liu G. Mater Chem Phys 2006;95:29–38. Sibel Z, Dogan P, Yazici B. Corros Rev 2005;23:217. Singh AK, Quraishi MA. Corros Sci 2010;52:1373–85. Soltani N, Behpour M, Ghoreishi SM, Naeimi H. Corros Sci 2010;52:1351–61. Ramesh SV, Adhikari AV. Corros Sci 2008;50:55. Musa AY, Kadhum AAH, Mohamad AB, Daud AR, Takriff MS, Kamarudin SK. Corros Sci 2009;51:2393–9. Behpour M, Ghoreishi SM, Soltani N, Salavati-Niasari M, Hamadanian M, Gandomi A. Corros Sci 2008;50:2172–81. Benali O, Larabi L, Traisnel M, Gengembra L, Harek Y. Appl Surf Sci 2007;253:6130–7. Shokry H, Sekine I, Yuasa M, El-Baradie HY, Comma GK, Issa RM. Zairyo to Kankyo 1997;47(7):447. Zhang QB, Hua YX. Corrosion inhibition of mild steel by alkylimidazolium ionic liquids in hydrochloric acid. Electrochim Acta 2009;54(6):1881–7. Kales H, Keles M, Dehri I, Serindag O. The inhibitive effect of 6-amino-m-cresol and its Schiff base on the corrosion of mild steel in 0.5 M HCI medium. Mater Chem Phys 2008;112(1):173–9. Aytac A, O¨zmen U, Kabasakalogˇlu M. Investigation of some Schiff bases as acidic corrosion of alloy AA3102. Mater Chem Phys 2005;89(1):176–81. Solmaz R, Kardas G, Yazici B, Erbil M. Adsorption and corrosion inhibitive properties of 2-amino-5-mercapto-1,3,4-thiadiazole on mild steel in hydrochloric acid media. Colloids Surf A Physicochem Eng Asp 2008;312(1):7–17. Li Y, Zhao P, Liang Q, Hou B. Berberine as a natural source inhibitor for mild steel in 1 M H2 SO4 . Appl Surf Sci 2005;252(5):1245–53. Kaim W, Schwederski B, Heilmann O, Hornung FM. Coordination compounds of pteridine, alloxazine and flavin ligands: Structures and properties. Coord Chem Rev 1999;182(1):323–42. Behpour M, Ghoreishi SM, Salavati-Niasari M, Ebrahimi B. Evaluating two new synthesized S-N Schiff bases on the corrosion of copper in 15% HCl acid. Mater Chem Phys 2008;107(1):153–7. Leçe HD, Emregül KC, Atakol O. Corros Sci 2008;50:1460–8.

Loutfy H. Madkour Scopus Author Identifier: 7003686193 and ORCID 0 0 0 0-0 0 02-3101-8356. Received his B.Sc., M.Sc. and Ph.D. from the Cairo, Minia and Tanta Universities of the AR Egypt, respectively. He worked as a lecturer chemistry at the Tanta University since 1982 and as a professor of physical chemistry in 1999. He is serving in different positions in Egypt, Kuwait, Republic of Yemen, and Kingdom of Saudi Arabia. He is a professor of physical chemistry at Al Baha University (KSA) since 2012. His research field is the physical chemistry, electrochemistry, corrosion, electrometallurgy, electro analytical chemistry, analytical chemistry, polarography, electrolytic extraction of heavy metals from natural ores and deposits, electrochemical thermodynamics, and environmental chemistry. He is occupy as Editorial Board member of International Journal of Industrial Chemistry (IJIC); ECronicon Chemistry (EC Chemistry); BAO Journal Chemistry and International Journal of Ground Sediment & Water. He is a corresponding author in this paper.

Savas¸ Kaya is a lecturer in Imranlı Vocational School, Cumhuriyet University. He completed his M.Sc. degree in the year 2013 in the field of theoretical inorganic chemistry in Cumhuriyet University Science Institute. Then, he started to PhD education under the guidance of Dr. Professor Dr. Cemal Kaya. His research is mainly focused on Density Functional Theory, theoretical chemistry, physical inorganic chemistry. He has authored many theoretical papers related to quantum chemical parameters, corrosion science, and chemical equalization principles.

Dr. Cemal Kaya is a full Professor in Department, Chemistry of Cumhuriyet University. He has received his Ph.D. degree in 1982 from Hacettepe University. His expertise areas are inorganic chemistry, quantum chemistry, molecular symmetry. His current research focus is Density Functional Theory based quantum chemical parameters like hardness, chemical potential, electronegativity and electrophilicity. Professor Cemal Kaya has authored two inorganic chemistry books, one molecular symmetry book and many publications in theoretical chemistry.

Lei Guo received his Ph.D. in 2015 from the Chongqing University in Chongqing of the PR China and in the same year worked in the School of Materials Science and Chemical Engineering at Tongren University. His research centers on designing novel green corrosion inhibitors for the protection of metals and alloys from corrosion.