theoretical study of aspartic and glutamic acids as
TRANSCRIPT
Moroccan Journal of Chemistry
ISSN: 2351-812X
http://revues.imist.ma/?journal=morjchem&page=login
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:
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
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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
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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.
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