Computational simulation and inhibitive properties of

Oguike et al. Int. J. Res. Chem. Environ. Vol. 4 Issue 3 (177-186) July 2014

International Journal of

Research in Chemistry and Environment Available online at: www.ijrce.org

ISSN 2248-9649

Research Paper

Computational Simulation and Inhibitive Properties of Amino acids for Mild Steel Corrosion: Adsorption in Gas Phase onto Fe (110) *Oguike R.S. and Oni O. Corrosion Protection and Materials Science Laboratory, Department of Chemistry, Abubakar Tafawa Balewa University Bauchi, PMB 0248, Bauchi, NIGERIA (Received 17th June 2014, Accepted 25th June 2014)

Abstract: A theoretical study has been performed on five selected amino acid molecules, arginine, asparaginine, aspartic acid, glutaminine and Tryptophan on mild steel surface from gas phase. The study is computed using Density Functional Theory (DFT) by quantum chemical calculation and molecular dynamics simulation. The properties of these molecules relevant to their potential action as corrosion inhibitor were calculated such as EHOMO, ELUMO, energy gap (∆E), electronegativity (χ), global hardness (η), softness (σ) and the fractional number of electrons transferred (∆N) using the Dmol3 code. The theoretical order of inhibition efficiency was found to be comparable with experimental result reported. The quench molecular dynamics simulations were applied to discover the equilibrium adsorption configurations between single inhibitor molecule and mild steel surface using supermolecule approach. Keywords: Density Functional Theory, Corrosion inhibition, Molecular dynamics, Mild steel, Amino acid © 2014 IJRCE. All rights reserved

the overall process is a function of the metal type, corrodent molecular and electronic structure as well as concentration of the inhibitor molecules while temperature and other environmental conditions have their contributions to the overall process [9-16, 22].

Introduction Material corrosion has been one of the factors that undermine our modern development, more especially in the industrial sector. Researches have shown that corrosion inhibitors when applied are an economic and effective technique that retards metals and alloys from deteriorating. Several studies have been carried out on amino acids as corrosion inhibitors for metals and its alloys and they have been found to inhibit its corrosion in aggressive media. Predictions by several authors have been made that amino acids as an organic inhibitor which adsorbs on the metals surface to mitigate corrosion rate either by the blocking effect of adsorbed inhibitor molecules on the metal surface and/or by the effects attributed to the change in the activation barriers of the anodic and cathodic reactions of the corrosion process [18] . Despite the widespread increasing interests in the application of these organic inhibitors, experimental results (as of now) reveal that the inhibition process is neither uniform with respect to all the classes of compounds studied nor are they consistent in a given environment. The main objective of theoretical research is to gain insight into the mechanisms by which inhibitor molecules added to aqueous environment retard the metal/corrodent interaction. Indeed, the effectiveness of

Density functional theory (DFT) has become a useful theoretical method that is applied to successfully describe the chemical reactivity of inhibitors and their adsorption efficiency on metal surface. A DFT-based quantum-chemical computational simulation of suitable models is now a prevailing tool readily available to corrosion scientists for theoretical investigation of corrosion-inhibition mechanism. Such computations have been widely used to analyze the molecular electronic structures of adsorption-type inhibitors using a number of quantum chemical descriptors which gives important insights on corrosion inhibition mechanisms [17-19]. The effectiveness of an inhibitor to provide corrosion protection depends to a large extent on the interaction between the inhibitor and the metal surface. The adsorbed inhibitors can affect the corrosion reaction, either by the blocking effect of the adsorbed inhibitor on the metal surface or by the effects attributed to the change in the activation barriers of the anodic and cathodic reactions of the corrosion process. Organic compounds, which can 177

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donate electrons to unoccupied d orbitals of metal surface to form coordinate covalent bonds and can also accept free electrons from the metal surface by using their antibonding orbitals to form feedback bonds, constitute excellent corrosion inhibitors. The most effective inhibitors are those compounds containing heteroatoms like nitrogen, oxygen, sulfur and phosphorus, as well as aromatic rings. The inhibitory activity of these molecules is accompanied by their adsorption to the metal surface. Free electron pairs on heteroatoms or π electrons are readily available for sharing to form a bond and act as nucleophile centers of inhibitor molecules and greatly facilitate the adsorption process over the metal surface, whose atoms act as electrophiles [20-21].

Accordingly, inhibition efficiency is correlated to the molecular and structural properties of inhibitor compounds. These parameters which could be obtained through theoretical calculations which includes, chemical reactivity, charge distribution and the frontier molecular orbit theory, HOMO (higher occupied molecular orbital) energy, the LUMO (lower unoccupied molecular orbital) energy, the energy of the gap, (∆E), chemical hardness (η) and softness (σ), electronegativity and electron transfer number (∆N). Lesar and Milošev[23] studied corrosion inhibition properties of 1,2,4-triazole and its amino derivatives while Gece and Bilgic[24] studied inhibition efficiencies of some amino acids as corrosion inhibitors of nickel. Khaled studied molecular simulation of trizaoles as corrosion inhibitor for mild steel[7].

Asparaginine (Asn)

Arginine (Arg)

Glutaminine (Gln)

Aspartic acid (Asp)

Tryptophan (Trp)

Figure 1: (a) Lewis structures of the investigated amino acids, (b) Name, (c) Abbreviation 178

Oguike et al. Int. J. Res. Chem. Environ. Vol. 4 Issue 3 (177-186) July 2014

herein, χFe and χinh represent the absolute electronegativity of iron and the inhibitor molecule, respectively, ηFe and ηinh represent the absolute hardness of iron and the inhibitor molecule. These quantities are associated with electron affinity (A) and ionization potential (I) which are useful in their ability to help evaluate chemical behavior.

In this present study, we are investigating on theoretical methods to elucidate the inhibition action of arginine (Arg), asparaginine (Asn), aspartic acid (Asp), glutaminine (Gln) and tryptophan (Trp) as corrosion inhibitor for mild steel cleaved along Fe (110) plane from gas phase using molecular and structural properties. This was done by discussing quantum chemical parameters, local reactivity indices such as Fukui Function and the binding characteristics of these amino acid compounds on the mild steel surface using quench molecular dynamics simulations.

(5)

(6)

Computation The geometry optimization process is carried for the studied amino acids, Arg, Asn, Asp, Gln, Trp and the Fe surface using an iterative process, in which the atomic coordinates are adjusted until the total energy of the structure corresponds to a local minimum at surface potential energy. These were modeled by Materials Studio Modeling 4.0 [25], a high quality quantum mechanics computer program (available from Accelrys, San Diego, CA). The electronic structures of inhibitor molecules and the Fe surface were modeled by means of the DFT electronic structure program DMol3 using a Mulliken population analysis as well as a Hirshfeld numerical integration procedure. Electronic parameter for the simulation includes restricted spin polarization using the DNP basis set and the Perdew Wang (PW) local correlation density functional. [22] DFT has also been found to be successful in providing insights into the chemical reactivity and selectivity, in terms of global parameters as electronegativity (χ), hardness (η) and local ones as the Fukui function f(r). The local reactivity of the molecules was studied through an evaluation of the Fukui indices using Dmol3 code which computes the measure of the molecules’ chemical reactivity indicating the possible reactive sites on the molecule. The condensed Fukui function calculations are based on the finite difference approximations and partitioning of the electron density ρ(r) between atoms in a molecular system.[26] f + = ʠk(N + 1) – ʠk(N) f – = ʠk(N) – ʠk(N – 1)

the global softness σ as the inverse of chemical hardness (7) According to DFT- Koopmans’ theorem, I can be approximated as the negative of EHOMO and A is also related to the negative ELUMO. Molecular dynamics (MD) simulation of the interaction between a single inhibitor molecules and the Fe surface was performed using Forcite quench molecular dynamics[22] to sample different low energy configurations and identify the low energy minima. Calculations were carried out, using the COMPASS (Condensed phase Optimized Molecular Potentials for Atomistic Simulation Studies) force field and the Smart algorithm, in a simulation box 24.79 Å × 24.05 Å × 29.79 Å with periodic boundary conditions to model a representative part of the interface, devoid of arbitrary boundary effects. The box was comprised of the Fe slab and a vacuum layer of 20 Å height. The Fe crystal was cleaved along the 110 plane and relaxed by minimizing its energy using molecular mechanics, while its periodicity was changed by constructing a supercell 12 x 10. The temperature was fixed at 298.15 K, with NVE ensemble. The system was quenched every 250 steps with convergence tolerance energy at 1.0-3kcal/mol. Optimized structures of inhibitor molecules and the Fe surface were used for all simulations. Results and Discussion The Lewis structures of the amino acid molecules studied are given in Figure 1. The optimized mild steel surface cleaved along 110 plane is shown in Fig. 2 while optimized molecular structures of the studied molecules using Dmol3 code by high convergence criteria are shown in Fig. 3. The computed quantum chemical parameters, EHOMO, ELUMO, ∆E, electronegativity (χ), global chemical hardness (η), global softness (σ) and number of electrons transferred (∆N) are given in Table 1. A practical route to the complex processes occurring between adsorbed inhibiting species and metal surfaces at the molecular level involves computer simulations of suitable models that calculate the molecular reactivity. According to Yan et al [27], the frontier molecular orbital theory, the formation of a transition state of chemical specie is due to an interaction between EHOMO and ELUMO of the reacting species.

(1) (2)

herein, ʠk is the gross charge of atom k in the molecule and N is the number of electrons. The condensed Fukui function is local reactivity descriptor and can be used only for comparing reactive atomic centres within the same molecule. The binding energy (–Ecomplex) of iron surface with inhibitor molecules was calculated according to the following equation:[13] EBind = EFe–inh – (EFe + EInh)

(3)

herein, EFe–inh is the total energy of the Fe crystal together with the adsorbed inhibitor molecule, EFe and EInh is the total energy of the iron crystal and free inhibitor molecule, respectively. The number of electrons transferred (∆N) from the inhibitor molecule to the metallic atom was also calculated using the following equation:[23]

The energy of HOMO characterizes the susceptibility of the molecule towards attack by electrophiles. High value of EHOMO indicates a tendency of the molecule to donate electrons to appropriate

(4) 179

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acceptor molecules with low energy MO or empty electron orbital. Increasing values of EHOMO is likely to indicate adsorption and therefore enhanced inhibition efficiency by an influence at the adsorbed layer through transport process. The energy of LUMO characterizes the propensity of the molecule towards attack by nucleophiles. Low value of ELUMO indicates an electron accepting ability of an inhibitor molecule. The binding ability of an inhibitor to a metal surface increases with increasing EHOMO and decreasing ELUMO values. This suggests that the EHOMO facilitate electron donation through the adsorbed layer while low E LUMO induces a back-donation of electron from the metal to inhibitor molecules[28]. The mild steel surface optimized along Fe(110) plane acts as an electrophile centers which might be due to the Fe atoms exhibiting an electron deficiency in the corner atoms while rich electron density in the center atom (Figure 2). This suggests that adsorption behaviour of the corner atoms would be different to that of the center atom, a phenomenon that could yield marked effect on nanocrystalline structures.

molecular orbital theory indicate the following order of inhibition efficiencies for the molecules: Trp > Arg > Asn > Gln > Asp which is comparable to the studies of Obiukwu et al. The HOMO densities of all the studied molecules were virtually found to be around the whole molecule. According to Yan [27], this kind of structure is difficult to form chemical bond active sites which suggest a physisorption for all studied molecules. This conforms to the findings of Obiukwu et al[32]. The energy band gap (∆E), the difference of ELUMO and EHOMO is another important factor that describes the reactivity of inhibitor molecules towards adsorption on metallic surfaces. It has been reported [33] that the low values of ∆E will provide a good inhibition efficiency, because the energy for removing an electron from the last occupied orbital will be low. As ∆E decreases, the reactivity of the molecule increases leading to increase in inhibition efficiency of the molecule [34]. For example, molecules with large HOMO-LUMO gap are generally stable and unreactive while those with small are ∆E reactive[35]. Table 1 show that Trp has a high energy band gap (70.85kcal/mol).

The nucleophile centers of the inhibitor molecules are normally heteroatoms with free π-electrons that are readily available for sharing in bond formation [29-31] . The computed results of EHOMO and ELUMO are shown in Fig. 3. The results in table 1 indicates that Trp has the highest EHOMO, while inspection of Fig. 3 reveals that the HOMO orbital is chiefly located around the indole ring while the LUMO orbital is predominant at the aldehyde function. This suggests that Trp can interact with the vacant orbital of Fe using these sites to form feedback bonds via adsorption. The total electron density (charge distribution) shown in Figure 3 reveals that the electron density is saturated all around the molecule, hence a flat-lying adsorption configuration was used for the computation. The HOMO orbital for Asp is found to saturate around carboxylate function and the LUMO orbital is localized around the aldehyde function. Similarly, the HOMO orbital of Arg is principally found around the amines, N3 and N10 while the LUMO orbital is localized around the aldehyde function.

For the purpose of investigating the active site of the inhibitor molecules, the Fukui indices are considered in table 2 and their computations shown in Fig. 4. Among the theoretical models proposed to compute local reactivity indices, Fukui functions make it possible to rationalize the reactivity of individual molecular orbital contributions which accounts for the response of the whole molecular spectrum. The f – measures reactivity with respect to the ability of the inhibitor molecule to donate electrons, while the f + is a measure of reactivity relating to the propensity of the molecule to accept electrons.[36] The optimized geometries obtained from the calculations of condense Fukui functions are shown in Fig. 4, the result for Fukui (Mulliken analyses) function support the trend of the frontier molecular orbital theory observed for the studied inhibitor molecules indicating the sites through which these molecules will be adsorbed onto the Fe(110) surface.

The HOMO orbital of Asn and Gln is found mostly around N7, O8 and C5, O7 respectively while their LUMO orbital density is largely around O1, C2 and C6, O7 respectively. It is interesting that we observed that all of the molecules studied used the aldehyde function to interact with the vacant molecular orbital of Fe using antibonding orbitals to form feedback bonds. This suggests that these inhibitor molecules can retard the corrosion process of mild steel. Obiukwu et al[32] studied some amino acids as corrosion inhibitor for mild steel corrosion in 1M H2SO4. The results from frontier Figure 2: Optimized structure of mild steel cleaved along Fe(110) plane

180

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Table 1 Electronic parameters (EHOMO, ELUMO, ∆E, electronegativity (χ),global chemical hardness (η), global softness (σ) and number of electrons transferred (∆N) of Arg, Asn, Asp, Gln, Trp in gas phase Molecule Arg Asn Asp Gln Trp

EHOMO (kcal/mol) -122.93 -129.33 -136.54 -131.21 -116.78

ELUMO (kcal/mol) -43.55 -47.38 -67.46 -48.57 -45.93

∆E (kcal/mol) 79.38 81.95 69.08 82.64 70.85

∆N (kcal/mol) 0.9849 0.8915 0.8602 0.8656 1.1299

χ (kcal/mol) 83.24 88.36 102.0 89.89 81.36

η (kcal/mol) 39.69 40.98 34.54 41.32 35.43

σ (10–2) (kcal/mol) 2.52 2.44 2.90 2.42 2.82

Arg

Asn

Asp

Gln

Trp (a) Optimized structure

(b) HOMO orbital

(c) LUMO orbital

Figure 3: Electronic properties of Arg, Asn, Asp, Gln, Trp: [C, gray, H, white, N, blue, O, red], structures , (b) HOMO orbital , (c) LUMO orbital

181

(a) optimized

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Table 2 Condensed Fukui function of active sites for Arg, Asn, Asp, Gln, Trp in gas phase f–

f+

Arg

N(10) 0.127 N(3) 0.103

C(8) O(9)

0.285 0.234

Asn

N(7) O(1)

0.232 0.155

C(2) O(1)

0.284 0.231

Asp

O(1) C(2)

0.363 0.101

C(6) O(7)

0.278 0.236

Gln

O(7) O(8)

0.165 0.133

C(6) O(7)

0.283 0.237

Trp

C(8) N(9)

0.065 0.058

C(12) 0.279 O(13) 0.224

Mulliken atomic charges N( 3) -0.409 C( 8) 0.243 O( 9) -0.329 N(10) -0.485 O( 1) -0.339 C( 2) 0.243 N( 7) -0.454 O( 1) -0.393 C( 2) 0.491 C( 6) 0.244 O( 7) -0.301 C( 6) 0.256 O( 7) -0.315 O( 8) -0.438 C( 8) -0.010 N( 9) -0.344 C(12) 0.241 O(13) -0.331

Figure 4: Chemical reactivity properties of Arg, Asn, Asp, Gln, Trp: [C, gray, H, white, N, blue, O, red], (b) f +, (c) Electron density 182

(a) f – ,

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The highest f – value associated with the indole ring C8 atom for Trp indicates the site most prone to nucleophilic attack and through which the molecules will interact with the Fe(110) surface. This indicates the propensity to donate electrons to vacant molecular orbital on the Fe surface to form coordinate bond. This agrees with the results of the computed HOMO density. Likewise, the highest f – values found for Arg and Asn are related to amine N10 atom and amine N7 atom respectively which also agrees with the computed HOMO density. Gln and Asp were found to be at aldehyl O7 atom and carboxyl O1 atom respectively with small densities, which could be attributed to their low reactivities (inhibition efficiency). The high f + value for Trp is linked with the aldehyl C12 atom signify the site most susceptible for an electrophilic attack that is through which the molecule accepts electrons to form feedback bonds with Fe surface. This also conforms to the computed LUMO orbital density. The values got for Arg

(a) Arg

and Asn where found to be around their aldehyl C atoms, C8 atom and C2 respectively while that of Gln and Asp had their f + values to be found around aldehyl C atoms C6 and C6 atom respectively. A close inspection would reveal that all studied molecules had the back-donation process at their aldehyl C atoms in agreement with the frontier orbital results obtained. Table 1 provides some important calculated quantum-chemical parameters using Eqn. (4), number of electrons transferred (∆N). Values of χ and η were calculated by using the values of I (-EHOMO) and A (-ELUMO) obtained from quantum chemical calculations. In order to calculate ∆N, a theoretical value for the electronegativity of bulk iron according to Zarrouk et al[37] was used, that is χFe ≈ 161.42 kcal/mol, and a global hardness of ηFe ≈ 0, by assuming that for a metallic bulk I = A, because they are softer than the neutral metallic atoms [5].

(b) Asn

(c) Asp

(d) Gln

(e) Gln

Figure 5: Representative snapshots of (a) Arg, (b) Asn, (c) Asp, (d) Gln and (e) Trp adsorbed on Fe(110). Inset images show the on-top views, emphasizing the molecular backbone aligning with vacant sites on the fcc lattice atop the metal surface 183

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According to Lukovits, if ∆N < 3.6, the inhibition efficiency increased with increasing electron donating ability at the metal surface[33].

inhibition efficiency results got showed that the length of alkyl chain had influence on molecular reactivity and the presence of indole ring further advanced this reactivity. This verity shows Trp to have higher inhibition efficiency than all studied amino acid molecules. The quench molecular dynamics demonstrated that the inhibitor molecules conform to physisorption type of corrosion inhibition. Also, our simulations showed that the adsorption energy increased with the presence of the indole ring and with elongation of alkyl chain. The values of number of transferred electrons also agree with the order of inhibition efficiency. References 1. Costa J.M., and Lluch J.M., The use of quantum mechanics calculations for the study of corrosion inhibitors, Corros. Sci. 24,929–933 (1984)

It can be inferred from the calculated results that inhibitors investigated in this study were donors of electrons, and the iron surface was the acceptor. Order of ∆N is as follow: Trp > Arg > Asn > Gln > Asp, which is in accordance with the change trends of EHOMO and Fukui functions. The highest inhibition efficiency of Trp can be attributed to the strongest coordinate bonds formed between the lone electron pairs of heterocyclic atom/π electrons of indole ring and the vacant d-orbitals of the metal surface. The absolute softness signifies the low resistance of an inhibitor molecule towards the deformation or polarization of the electron cloud of the atoms or molecules under a small perturbation of chemical reaction. In our present study, Trp has a high value of 2.82 x 10-2 kcal/mol and electron transfer value of 1.1299 kcal/mol. To quantitatively evaluate the most suitable adsorption modes between each inhibitor molecule and mild steel surface, the adsorption energy (EBind) was calculated using the relationship in Eqn. (3). In each case the potential energies were calculated by averaging the energies of the five computed structures of lowest energy. We discovered that Trg exhibited highest binding energy (89.28 kcal/mol) during our simulation process. This could be attributed to the number of lone pair of electrons on N atoms as well as the π-electron clouds on the indole ring can provide electrons to the unfilled 3d-orbitals of iron surface to form protective layer on the metal surface. Such protective film may act as a steric barrier that hinders the reactive ions/species in the aggressive environment from coming into contact with the metal surface, thereby mitigating corrosion process.

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