Theoretical study of aspartic and glutamic acids as

Moroccan Journal of Chemistry

ISSN: 2351-812X

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Ayuba & al / Mor. J. Chem. 6 N°1 (2018) 160-172

Mor. J. Chem. x N°x (2016) xxx-xxx

160

Theoretical study of aspartic and glutamic acids as corrosion inhibitors on

aluminium metal surface

Ayuba, A. M. a*, Uzairu, A.b, Abba, H. b, Shallangwa, G. Ab.

(a) Department of Pure and Industrial Chemistry, Bayero University, Kano, Nigeria.

(b) Department of Chemistry, Ahmadu Bello University, Zaria, Kaduna, Nigeria

* Corresponding author:

[email protected]

Received 05 July 2017,

Revised 15 Nov 2017,

Accepted 29 Dec 2017

Abstract

The present study describes the inhibition of aluminium corrosion using amino

acids including aspartic and glutamic acids through computational studies.

Quantum chemical approach was used to calculate some electronic properties of

the molecules to ascertain the correlation between inhibitive effect and

molecular structure of the inhibitors. The corrosion inhibition efficiencies of

these molecules and the global chemical reactivity was established through

some parameters, such as EHOMO, ELUMO, energy gap (∆E), electronegativity (χ),

global hardness (η), and the fraction of electrons transferred from the inhibitor

molecule to the aluminium metallic atom (∆N). In addition, the local reactivity

has been analyzed through the Fukui function and condensed softness indices.

The molecular dynamic method results showed that the more negative the

binding energy of the inhibitor-metal surface is, the better the adsorption of the

inhibitor onto the metal surface and subsequently the higher the inhibition. The

trend could be inferred in terms of inhibition efficiencies of the inhibitors in

respect of their binding energies as glutamic acid greater than aspartic acid.

Keywords: Adsorption; Aluminium; Computation; Corrosion; Inhibitors.

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1. Introduction With the advances in computer hardware and development of related theory, molecular modelling has grown

to be an effective technique to explore complex systems at molecular level. Molecular structure, electron

distribution and detailed adsorption process can be obtained via this approach, which is helpful for

investigation of inhibition mechanism. At the end of the twentieth century, much research based on

molecular dynamics simulation was conducted to investigate the inhibitor mechanism on micro to

mesoscopic scale [1–3]. The effect of corrosive environment factors, such as solvent, temperature and

pressure, etc., on adsorption of inhibitor molecule on metal surfaces were also investigated. These research

results have provided theoretical guidance for molecular design [4]. The adsorption of inhibitor molecules

on surfaces has recently become the subject of intensive investigation in the corrosion field because of the

wealth of information that can be obtained [5–7]. Understanding how an inhibitor molecule behaves near a

metal surface will greatly enhance the ability to control the essential interfacial properties in a wide variety

of corrosion problems. Several computational methods have been used to study the behaviour of inhibitors

for different metals [8–11]. Aluminium is an extremely valuable metal due to its lightweight, high strength,

recyclability, corrosion resistance, durability, ductility, formability, and conductivity. Aluminium and its

alloys find extensive applications in various industries in different capacities [12]. However, aluminium and

its alloys are reactive materials and are prone to corrosion. Corrosion of aluminium and its alloys has been a

subject of numerous studies due to their high technological value and wide range of industrial applications in

aerospace and house hold industries [12]. Though aluminium facilitates the formation of a compact,

adherent passive oxide film for its corrosive immunity in various environments, the surface film is

amphoteric and dissolves substantially when the metal is exposed to high concentrations of acids or bases

[13, 14]. The solubility of the oxide film increases above or below pH 4–9 range and the metal exhibits

uniform attack. The use of corrosion inhibitors is inevitable under these circumstances. Most of the efficient

acid corrosion inhibitors contain heteroatoms such as N, O, S, and multiple bonds in their molecules, which

activate the process of adsorption. This adsorption process gets activated as the electron donating efficiency

of the inhibitor molecule increases [12]. Most of the heteroatoms in organic molecules bear non-bonding

electro pairs in the valence shell and hence possess excellent inhibitory action. The adsorption of molecules

on the metal surface is also influenced by their electronic structure, steric factors, aromaticity, and p-orbital

character of donating electrons [15–17]. The aim of this work is to study the influence of two selected amino

acids, namely aspartic and glutamic acids on the inhibition of aluminium corrosion using molecular

dynamics and quantum chemical calculation to explore the adsorption mechanism of the amino acids on

aluminium (1 1 0). Also, as the electronic structure of amino acids could be involved in determining

interactions with the aluminium surface, correlation between molecular orbital calculations and inhibitor

efficiencies will also be sought.

NH2

O

HO

O

OH

NH2 O

OH

O

HO

a) Glutamic Acid b) Aspartic Acid

Figure 1.1: Chemical structures of the amino acids (a) Glutamic Acid (b) Aspartic Acid


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2. Materials and Methods

2.1 Sketching of the inhibitor molecules and geometry optimization

The inhibitor molecules of interest (aspartic acid and glutamic acid) were sketched using Chemdraw Ultra 7.0

software. The sketched molecules were all subjected to geometry optimization to refine the geometry of their

structures so as to minimize their torsional and conformational energies. This was achieved using the DMol3 geometry

optimization task in Accelrys Material Studio 7.0 software. The optimized structures were saved for further use in

quantum calculations of some structural and electronic properties [18, 19].

2.2 Quantum chemical calculations

The electronic structure of the amino acids, including the distribution of frontier molecular orbitals, EHOMO and ELUMO,

Fukui indices were assessed, with a view to establishing the active sites as well as local and global reactivities of the

molecules. The simulations were performed by means of the Density Functional Theory (DFT) electronic program

DMol3 using the Mulliken population analysis in the Material Studio 7.0 software. DMol3 permits analysis of the

electronic structures and energetics of molecules, solids and surfaces using DFT. Electronic parameters for the

simulations include restricted spin polarization using the DND basis set and the Perdew Wang local correlation density

functional. Local reactivity of the studied compounds was analysed by means of the Fukui indices (FI) to assess

regions of nucleophilic and electrophilic behaviour [11, 12, 20-25].

2.3 Molecular dynamics simulation

The potential energy surface of a small molecule can be very complex, with many local energy minima and

one global energy minimum. There are several methods that can be used to determine the global minimum

including Monte Carlo algorithms and different forms of molecular dynamics. One common molecular

dynamics method, called quench molecular dynamics, performs a standard molecular dynamics calculation

with an additional geometry optimization step, in which a geometry optimization is performed on every

frame in the trajectory file. Effectively, molecular dynamics is used to sample many different low energy

configurations [26, 27]. In order to sample many different low energy configurations and identify the low energy

minima, molecular dynamics (MD) simulation of the interactions between a single inhibitor molecule of interest and

Al surface was performed using Forcite quench molecular dynamics in the Material Studio (MS) modelling 7.0

software. Calculations were carried out using COMPASS forcefield and Smart algorithm in a simulation box 17Å x 12

Å x 28 Å with a periodic boundary condition, to model a representative part of the Al slab and a vacuum layer of 20 Å

height. The Al crystal was cleaved along the (1 1 0) plane with a fractional depth of 3.0 Å. The (110) plane was

chosen because it is more densely packed and has the most stabilisation compared to Al (111) and Al (100) surfaces

with relatively open structures [28]. The geometry of the bottom layers were constrained before optimizing the Al

(110) surface which was subsequently enlarged into a 9 x 7 supercell to avoid edge effects. Temperature was fixed at

350 K which represents a trade off between a system with too much kinetic energy where the molecule desorbs from

the surface and a system with not enough kinetic energy for the molecule to move around the surface. Temperature

was fixed with the NVE (microcanonical) ensemble with a time step of 1 fs and simulation time 5 ps. The system is

quenched every 250 steps. Forcite optimised structures of the amino acid molecules and the Al surfaces were used to

sample the different interactions of the molecule with the surfaces. The slab of aluminium constructed for the docking

was significantly bigger than the amino acid molecules docked in order to avoid edge effects [23, 24, 29-31]. The

binding energy between the Al surface and the inhibitor molecule was calculated using the Equation 3.9;


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Binding Energy = Etotal – (Einhibitor + EAl surface) 1.1

3. Results and Discussion

Figures 1.2: Electronic and Structural Properties of Aspartic Acid: a) Geometry Optimized b) Total

Electron Density c) Highest Occupied Molecular Orbital d) Lowest Unoccupied Molecular Orbital

Figures 1.3: Electronic and Structural Properties of Glutamic Acid: a) Geometry Optimized b) Total

Electron Density c) Highest Occupied Molecular Orbital d) Lowest Unoccupied Molecular Orbital

a b

c

d c

b a

d


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Table 1.1: Computed Quantum Chemical Parameters (Electronic and Structural) of the Studied Inhibitor

Molecules

Properties

Inhibitors

Aspartic Acid Glutamic Acid

HOMO (at orbital number) 35 39

LUMO (at orbital number) 36 40

EHOMO (eV) -5.713 -5.672

ELUMO (eV) -1.600 -1.525

∆E (eV) 4.113 4.147

Dipole Moment (Debye) 1.840 2.120

Molecular Weight (g/mol) 133.103 147.13

Ionization Potential (I) (eV) 5.713 5.672

Electron Affinity (A) (eV) 1.600 1.525

Global Hardness (ƞ) 2.057 2.074

Global Softness (σ) 0.486 0.482

Absolute Electronegativity (χ) 3.657 3.599

Fractions of Electrons Transferred (∆N) 0.473 0.483

Table 1.2: Calculated Fukui Indices for the Studied Inhibitor Molecules

Electrophilic (F-) Nucleophilic (F+)

Mulliken Hirshfeld Mulliken Hirshfeld

Molecule Atom Value Atom Value Atom Value Atom Value

Aspartic Acid N(14) 0.348 N(14) 0.341 C(10) 0.168 O(11) 0.163

Glutamic Acid N(17) 0.38 N(17) 0.366 C(13) 0.190 O(14) 0.174

a b

c d

Figures 1.4: Adsorption of Single a) Aspartic Acid (side view snap shot) b) Aspartic Acid (on top view snap

shot) c) Glutamic Acid (side view snap shot) d) Glutamic Acid (on top view snap shot) Molecules on

Aluminium (110) Surface


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Table 1.3: Calculated Adsorption Parameters for the Interaction of the Studied Molecules with the Al(110)

Surface Using Forcite Quench Dynamics

Properties Aspartic Acid Glutamic Acid

Total Potential Energy (kcal/mol) -49.887+2.416 -39.890+1.151

Energy of Molecule (kcal/mol) -25.625+0.485 -8.624+1.970

Energy of Al(110) Surface

(kcal/mol) 0.000+0.000 0.000+0.000

Binding Energy (kcal/mol) -24.822+5.610 -31.501+1.036

3.1 Discussion

3. 1. 1 Electronic structure properties of the inhibitor molecules using DMol3 methods

The use of quantum chemical calculations has become popular for screening new potential corrosion

inhibitors [32]. In majority of these cases, such screening consists of calculating several electronic structural

parameters of isolated molecules either in gas or in aqueous phase – the solvent is usually treated by some

variant of polarized continuum mode (PCM) [33]. The most popular parameters, which play a prominent

role is the hard and soft acid and base (HSAB) theory of chemical reactivity. These involve the eigenvalues

of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), the

HOMO-LUMO gap (∆E), chemical hardness/softness, electronegativity, and the number of electrons

transferred from inhibitor molecule to the metal surface [26, 34, 35]. Molecular dipole moments and Fukui

functions are also frequently used in corrosion inhibition studies. The local reactivity of the inhibitor

molecules was analyzed through an evaluation of the Fukui indices [18, 36]. Fukui indices are a

measurement of the chemical reactivity, as well as an indicative of the reactive regions and the nucleophilic

and electrophilic behaviour of the molecule. The regions of a molecule where the Fukui function is large are

chemically softer than the regions where the Fukui function is small, and by invoking the HSAB principle in

a local sense, one may establish the behaviour of the different sites with respect to hard or soft reagents [12].

The Fukui function is defined as the derivative of the electronic density with respect to the

number of electrons N at a constant external potential as in Equation 1.2:

1.2

If the effects of relaxation associated with the addition or removal of electronic charges are not considered,

then Equations 1.3 and 1.4 results:

1.3

1.4

where is the density of the lowest unoccupied molecular orbital and is density of the

HOMO [37-39]. The condensed Fukui functions were found by taking the finite difference approximations

from Mulliken population analysis of atoms in the inhibitors, depending on the direction of the electron

transfer using Equations 1.5 and 1.6 respectively:

1.5

1.6


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where qk is the gross charge of atom k in the molecule, i.e. the electron density at a point r in space around

the molecule. The N corresponds to the number of electrons in the neutral molecule, N + 1 corresponds to an

anion, with an electron added to the LUMO of the neutral molecule and N - 1 represents the cation with an

electron removed from the HOMO of the neutral molecule. All calculations are done at the ground-state

geometry. These functions can be condensed to the nuclei by using an atomic charge-partitioning scheme,

such as Mulliken population analysis. An easy graphical display technique was also used based on the Fukui

functions. Instead of calculating the molecular orbitals for the neutral, cation, and anion, we can just add or

subtract electrons from the molecular orbitals of the neutral molecule. Though this procedure is not as good

as the first method, it gives a quick graphical display of the susceptibility of different kinds of attack.

Molecular orbitals are designated with respect either to HOMO or LUMO orbital [40-43]. There are two

different definitions used for the chemical hardness, η that differ by a factor of two [44]. This affects all

other electronic parameters that depend on η. The definition based on the following two Equations 1.7 were

used;

and 1.7

where E is the total energy of the system, N is the number of electrons, and μ is the electronic chemical

potential. The other definition drops the factor 1/2 from the definition of η. The HSAB parameters can be

derived by Equation 1.7 by using finite difference approximation for the first and second eigenvalues of

HOMO and LUMO, -EHOMO and -ELUMO, for the ionization potential and electron affinity [45, 46]. The

electronegativity, χ, is the negative of chemical potential and hence given by Equation 1.8:

χ = -μ ≈ -1/2 (EHOMO + ELUMO) 1.8

while chemical hardness, η is approximated by Equation 1.9:

η ≈ ½(EHOMO – ELUMO) 1.9

The work function ϕ of the metal surface is taken as electronegativity; whereas chemical hardness is

neglected, because η of bulk metal is the inverse of their density state at the Fermi level which is an

exceedingly small number [47].

The number of electrons transferred from the molecule to metal ∆N, will be given by Equation 1.10:

1.10

where Al is considered as Lewis acid according to HSAB concept [48]. The difference in electronegativity

drives the electron transfer, and the sum of the hardness parameters acts as a resistance. In order to calculate

the fraction of electrons transferred, a theoretical value for the electronegativity of bulk aluminium was used

χAl = 5.60 eV [49], and a global hardness of ηAl = 0, by assuming that for a metallic bulk I = A [50, 51]

because they are softer than the neutral metallic atoms. The softness (σ) of the inhibitor molecule is simply

the inverse of the hardness σ = 1/η [52-57].

Figures 1.2 illustrates the geometric optimized structure, the total electron density, highest occupied

molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) of aspartic acid whereas

Figures 1.3 show similar structures for glutamic acids respectively. The electron density is saturated all

around each molecule; which should facilitate flat-lying adsorption orientations [31]. The regions of high

HOMO density are the sites at which electrophiles attack and represent the active centers, with the utmost

ability to bond to the metal surface, whereas the LUMO orbital can accept the electrons in the p- or d-orbital

of the metal using antibonding orbitals to form feedback bonds [29-31]. It is observed that the HOMO

orbital for aspartic and glutamic acids is saturated around the amine functional group, while the LUMO


167

orbital is around the carboxyl functional groups. The trend of HOMO–LUMO locations is actually common

to all the amino acids molecules (aspartic and glutamic acids) which could lead to some similarities in their

adsorption characteristics. The eigenvalues of the HOMO (EHOMO) and LUMO (ELUMO) as well as the

energy gap ∆E = EHOMO - LUMO are presented in Table 1.1 together with some other quantum chemical

parameters related to the molecular electronic structure of the most stable conformation of the molecules.

High values of EHOMO indicate the disposition of the molecule to donate electrons to an appropriate acceptor

with vacant molecular orbitals, whereas low values of ∆E will favour good inhibition efficiencies because

the energy to remove an electron from the last occupied orbital will be minimized [29-31]. The obtained

values presented in Table 1.1 show that the molecules all have comparable EHOMO values, which is not very

surprising because the functional groups that comprise the HOMO are identical. The ∆E values again do not

vary so much, the seemingly low values of ΔE (approximately 5 eV) suggest that interaction of the

molecules with the metal surface would hardly involve electron transfer processes [58]. The low value of

dipole moment of the inhibitor in Table 1.1 has often been associated with good inhibition properties [59-

63]. The dipole moment calculated for all the molecules are quite close, with lowest value in aspartic acid

while the direction of their dipoles is similar and they are projected to the molecular plane. The direction of

dipole can be understood by considering the electrostatic potential, which discerns electron density rich

regions centered on the amine indicating the preferred zone for electrophilic attack. Dipole moments are

substantially enhanced for both inhibitors on going from the gaseous to the aqueous phase, indicating an

increase in the stability of the inhibitors due to the interaction with water [12]. Considering all these factors,

a clear trend was observed for the studied molecules in respect of increase in EHOMO values, decrease in ∆E

values, decrease in dipole moment and increase in molecular weight. The local reactivity of each molecule

was analyzed by means of the Fukui indices (FI) to assess reactive regions in terms of nucleophilic and

electrophilic behaviour to distinguish each part of the molecule on the basis of its distinct chemical

behaviour due to different functional groups or substituents. The F- measures reactivity with respect to

electrophilic attack or the propensity of the molecule to release electrons, whereas F+ is a measure of

reactivity relating to nucleophilic attack or tendency of the molecule attract electrons. The obtained values

were presented in Table 1.2. In the electrophilic (F-), aspartic acid have its highest Mulliken and Hirshfeld

charges on N(14) atom, glutamic acid have it on N(17) atom. While for the nucleophilic (F+), aspartic acid

have its highest Mulliken charge on C(10) and Hirshfeld charge on O(11), glutamic acid on C(13) and

O(14). This further supports the earlier argument that the amino acids uses their lone pair of electrons on

nitrogen atom to adsorb to the surface of aluminium. The similarities in quantum chemical parameters mean

that the adsorption strengths of the molecules would be mostly determined by molecular size parameters

rather than electronic structure parameters alone [12].

Table 1.2 presented results of some other electronic and structural quantum chemical parameters of the

studied inhibitors. These include their; ionization potential, electron affinity absolute (global) hardness,

global softness, absolute electronegativities and fraction of electron transferred respectively. The number of

electrons transferred from the molecule to metal ∆N, was calculated using Equation 1.10, where aluminium

is considered as Lewis acid according to HSAB concept [12]. The difference in electronegativity between

the inhibitor and the aluminium drives the electron transfer, and the sum of the hardness parameters acts as a

resistance. In order to calculate the fraction of electrons transferred, a theoretical value for the

electronegativity of bulk aluminium was used χAl = 5.6 eV, and a global hardness of ηAl = 0, by assuming

that for a metallic bulk I = A [50, 51], because they are softer than the neutral metallic atoms. From Table


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1.2 the fraction of electron transferred was found to be highest in glutamic acid than in aspartic acid. This is

an indication that glutamic acids possess a higher ability to donate electrons or interact to the empty d-

orbitals of the aluminium metal than aspartic acid. Sastri and Perumareddi [52] reported that if ∆N is less

than 3.6, inhibition efficiency increases with increasing values of the electron donating ability of the

molecules, while values of ∆N greater than 3.6 indicate a decrease in inhibition efficiency with increase in

electron donating ability of the inhibitor. The earlier case is found to be applicable to all the studied

molecules since their ∆N values are all less than 3.6.

3.1.2 Molecular dynamics simulations

Adsorption of each inhibitor molecule differently on the aluminium metal surface was analyzed at a molecular level

by molecular simulation dynamics method using Forcite quench molecular dynamics to sample many different low

energy configurations and to identify the low energy minima. Figures 1.4 shows representative snapshots of the top

view (inset) of the lowest energy adsorption configurations for single molecules of aspartic and glutamic acids

respectively on the Al (110) surface from the simulations. Each molecule can be seen to maintain flat lying adsorption

orientation on the Al surface, as expected from the delocalization of the electron density all around the molecules. This

orientation maximizes contact with the metal surface and hence augments the degree of surface coverage. This parallel

adsorption orientation also facilitates interaction of π - electrons of the amino acids on the hetero-atoms (N and O) in

the molecules with the aluminium metal surface. A detailed analysis of the on-top view of the adsorbed molecules on

Al (110) emphasizing the soft epitaxial adsorption mechanism with accommodation of the molecular backbone in

characteristic epitaxial grooves on the aluminium metal surface are presented in Figures 1.4. The on-top view reveal a

very clear trend in the adsorption configuration in which polarizable atoms along the molecular backbone appear to

align with vacant sites on the face-centered cubic lattice atop the aluminium metal surface. Such epitaxial adsorption

configuration, which is associated with a minimum free energy of adsorption, has also been reported for some

compounds and this accounts for the stable adsorption structures [24, 29, 30].

To quantitatively appraise the interaction between each molecule and the aluminium surface, the adsorption

energy (Eads) was calculated using Equation 1.1. A negative value of Eads corresponds to a stable adsorption

structure, whereas Einhibitor, EAl surface and Etotal correspond, respectively to the total energies of the molecule,

Al (110) slab and the adsorbed Molecule/Al (110) couple in the gas phase. The total energies were

calculated by averaging the energies of the three most stable representative adsorption configurations and

the results were presented in Table 1.3. The obtained Eads values; -24.822+5.610 kcal/mol for aspartic acid, -

31.501+1.036 kcal/mol for glutamic acid were all negative and of relatively low magnitude, suggesting

stable adsorption structures (Awe et al., 2015). This low affinity of the inhibitors for the aluminium surface

may account for the low corrosion inhibition efficacy of the molecules. However, the magnitudes of the

calculated binding energies were all less than 100 kcal mol−1 (Table 1.3) this is despite the fact that the

simulations did not take into consideration the specific covalent interactions between the molecules and the

aluminium surface. This value has been reported to be in the range of physisorptive interactions [12, 29, 35].

It has also been reported that the more negative the binding energy of the inhibitor-metal surface is, the

better the adsorption of the inhibitor onto the metal surface and subsequently the higher the inhibition [12,

24, 29, 35]. It can be observed from Table 1.3 that a trend could be inferred in terms of inhibition

efficiencies of the inhibitors in respect of their binding energies as follows: glutamic acid>aspartic acid.

3.1.3 Proposed Mechanism of Inhibition


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It is well-known that terminal oxygen atoms at metal oxide surfaces react with water, forming hydroxylated

sites, or hydroxide layers at the surface (M–OH), that impart a pH dependent surface charge. The polar

hydroxyl (-OH-) groups may cause the surface to attract and physically adsorb a single or several additional

layers of polar water molecules. An oxide or hydroxide surface (Al–OH) becomes charged by reacting with

H+ or OH- ions due to surface amphoteric reactions as presented in Equations 1.11 and 1.12 respectively:

Al - OH + H+ Al - OH2+ 1.11

Al - OH + OH- Al - O- + H2O 1.12

In systems where pH is low, hydroxide surface adsorbs protons to produce positively charged surfaces Al -

OH2+. The number of these sites and the surface charge of the oxide are determined by the pH of the

solution. Surface charge influences adsorption of ions from solution and other interfacial phenomena [47].

The pH of the potential of zero charge (PZC) for aluminum oxides/hydroxides is between 6 and 9, and in

acidic solution, the accumulation of Al - OH2+ species accounts for the surface charge [64, 65]. In acidic

solution, therefore the positively charged surface sites electrostatically attract any anions present in solution,

and repel cations. It is a general assumption that the adsorption of the organic inhibitors at the metal solution

interface is the first step in the mechanism of the inhibitor action. Organic molecules may adsorb on the

metal surface in four types:

(a) electrostatic interaction between a negatively charged surface, which is provided with specifically

adsorbed anions on aluminum and the positive charge of the inhibitor,

(b) interaction of unshared electron pairs in the molecule with the metal,

(c) interaction of p-electron with metal, and

(d) a combination of the (a–c) types.

Efficient adsorption is the result of either p-electron of the amine system or the electronegative N

(heteroatom) atoms [66]. The adsorption of amino acids can be described by two main types of interaction:

physical adsorption and chemisorption. In general, the proceeding of physical adsorption requires the

presence of both electrically charged surface of the metal and charged species in the bulk of the solution.

Chemisorption process involves charge sharing or charge transfer from the inhibitor molecules to the metal

surface to form a coordinate type of a bond. This is possible in the case of positive as well as negative

charge of the surface. However, the inhibitors under investigation are organic compounds which protonize in

an acid medium due to N atom they posses. Thus, the inhibitor molecules become a cation, existing in

equilibrium with the corresponding molecular form. The electrostatic adsorption of these cations could be

explained on the basis that anions (from the corrodent) first adsorbed at the electrode/solution interface at

the corrosion potential through electrostatic attraction force due to the excess positive and charge at the

interface. This process changes the charge of the solution side of the interface from positive to negative, and

thus facilitating physical adsorption of the inhibitors, cations. Thus, cations of these compounds are able to

electrostatically adsorb on the electrode surface covered with primary adsorbed anions. The adsorption of

the studied molecules on the electrode surface makes a barrier for mass and charge transfers. This situation

leads to the protection of the electrode surface from the acid corrosion. In addition to the physical

(electrostatic) adsorption, there may be a chemical adsorption, due to the coordinate type of bonds that may

be formed, between the lone electron pairs of the unprotonated N atoms and the empty p-orbital of Al atoms

which enhance the attraction between the molecules and the electrode surface. The chemical adsorption is

probably the most important type of interaction between the Al2O3 surface and the studied inhibitor

molecules if they occur because the adsorbed species will be in permanent contact with the Al2O3 surface. In


170

this process, a coordinated bond that involves the electron transference from inhibitor system toward the

metallic surface is formed. The electron transference is facilitated when the inhibitor molecule has a lone

pair of electrons without sharing in the donating atom of the functional group, and the availability of p-

electrons due to the presence of double bonds around the carboxyl in thier structure. Moreover, there is a

great possibility that adsorption may also take place via hydrogen bond formation between the N–H linkage

and the oxygen atoms of the oxidized surface species. This type of adsorption should be more prevalent for

protonated N-atoms, because the positive charge on the N-atom is conductive to the formation of hydrogen

bonds. Unprotonated N-atoms may adsorb by direct chemisorption, as mentioned previously, or by hydrogen

bonding to a surface oxidized species. The extent of adsorption by the respective modes depends on the

nature of the metal surface. Adsorption by direct chemisorption, for unprotonated N-atom, is more probable

on an exposed metal atom. In addition, the unprotonated N-atom can also interact with oxidized metal by

hydrogen bonding. Effective inhibition is predominantly provided by the direct coordination of unprotonated

N-atom to metal atoms. As the metal surface is covered by an adherent oxide protective layer, the direct

coordination of nitrogen to an exposed metal atom is a remote event. Protonated and unprotonated N-atoms

are adsorbed onto the metal through hydrogen bond formation. The criteria for inhibitor selection can also be

inferred from above considerations. A good inhibitor must have strong affinity for the bare metal atoms. The

requirement is different in case of aluminum; a compact passive oxide film is always present on the

electrode surface, where hydrogen bond formation accounts for most of the inhibition action. An effective

inhibitor is one that forms hydrogen bonds easily with the oxidized surface [47]. Elucidating the orientation

of organic molecules on the electrode surface different factors need to be considered [67]. In the case of the

studied molecules, the atoms and groups that may interact with the aluminium electrode surface are the N

atoms either in the amino substituent in addition, present in the studied molecules. The delocalization of p-

electrons in the carboxyl may weakly interact with the aluminium oxide surface when molecules are oriented

horizontally [67], but they may also interact with other molecules forming parallel double stacks, with the

molecules oriented vertically. The proposed orientations ranged from horizontal [68], to vertical [69] which

may depend on their concentrations. In the early stages of adsorption (at low surface coverage), i.e., low

concentrations, the orientation of the studied molecules is parallel to the aluminum oxide surface. As the

concentrations of the inhibitor molecules increased more surface coverage occurs and the inhibitor

molecules are oriented vertically. By increasing the inhibitors concentrations the formed barrier becomes

more compact and protective with adsorption of more molecules on the aluminium surface. In this way, the

inhibition efficiency of studied molecules may be found to increase with increase in concentration.

4. Conclusions

The DFT-based quantum chemical computations of parameters associated with the electronic structures of the

inhibitor molecules confirmed their inhibiting potential through ∆N, HOMO, LUMO, electron density, dipole moment

and their energies indicating the point of association of the molecules with the aluminium surface may be through –

NH3, or –COOH respectively. This was further corroborated by molecular dynamics simulation modeling of the

adsorption of the single molecules on the metal surface to ascertain the adsorption/binding energies and sites of the

inhibitor molecules on the aluminium surface. The values obtained were negative and low, signifying low adsorption

and inhibition.


171

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