Quantum chemical analysis of amino acids as anti-corrosion agents

1 Introduction

To accurately evaluate the efficacy of corrosion inhibitors for drugs, metals, and alloys, researchers have developed a variety of experimental techniques and advanced surface characterization technologies. These methods are often financially expensive, requiring a significant amount of effort and a considerable amount of time to yield reliable results. Using these evaluation techniques, researchers can determine the effectiveness of corrosion inhibitors on drugs, metals, and alloys, and measure the corrosion protection they provide (Guo et al. 2020a; Miralrio and Espinoza Vázquez 2020; Obot et al. 2015; Omer et al. 2022a,b,d, 2023). The utilization of computational chemistry methods to assess the effectiveness of a corrosion inhibitor has been proven to be extremely advantageous in understanding the molecular structure of the inhibitor, as well as illuminating its electrical characteristics and reactivity. By utilizing mathematical and computerized formats, it is possible to identify compounds that possess the desired characteristics (Koparir et al. 2022b; Parlak et al. 2022). Corrosion of alloys and metals can be one of the most damaging and costly issues, exacerbated by manufacturing processes that prepare metal surfaces for other applications. An effective way to protect metals and alloys from corrosion is to use corrosion inhibitors (Guo et al. 2020b; Mamand and Qadr 2022; Qadr and Mamand 2021). The high cost of managing and preventing corrosion, as well as the environmental toxicity of some of the used inhibitors, prompted this evaluation. Quantum chemistry approaches have the most profound effect on diminishing the cost of corrosion protection for metals and alloys. This review article begins with a discourse of the most frequently used computational techniques and parameters before summarizing the conclusions of specific research conducted by various authors on the topic of corrosion science and engineering. The essential structural elements that affect inhibition effectiveness in these functional groups are lone pairs of electrons and loosely bound p-electrons (Mamand et al. 2022a,d). Despite the fact that the toxicity of certain chemicals has been confirmed, environmental regulations have encouraged research into non-phosphor and non-toxic corrosion prevention options. Amino acids have become increasingly attractive alternatives as they are not only non-toxic, but also relatively inexpensive and easy to produce with purities higher than 99 %. Furthermore, they are believed to be more efficient and reliable inhibitors, as they are corrosion-resistant on mild steel, copper, and aluminum alloy (Mamand et al. 2022b; Petrunin 2022). The previous study focused on the technique of adsorption as well as the link between the composition of inhibitors, their adsorption on the metal surface, and their morphological inhibition efficiency (Omer et al. 2022a; Qadr and Mamand 2021; Rebaz et al. 2022). Recent studies have revealed that the inhibition efficacy of organic corrosion inhibitors is strongly affected by a variety of physicochemical factors, including steric effects, corrosive environment, functional groups, p orbital character, and electronic density at the donor atom. Among all the available corrosion inhibitors, amino acids have been identified as highly effective yet safe chemicals that can be employed as corrosion inhibitors. Amino acids are organic molecules that are essential for all living organisms, playing a key role in the synthesis of proteins and other important biomolecules such as hormones, neurotransmitters, and nucleic acids (Ahmed et al. 2018; Assad and Kumar 2021; Parlak et al. 2022; Torres et al. 2014).

The present work is the first to combine the advantages of computational chemistry methods with the knowledge of the factors that influence the efficacy of corrosion inhibitors. This approach offers a comprehensive and cost-efficient way of evaluating the effectiveness of corrosion inhibitors, which can be a significant cost savings for manufacturers and other industries. Furthermore, the utilization of computational chemistry methods avoids the need for expensive experimental techniques and advanced surface characterization technologies. The focus on amino acid corrosion inhibitors provides a safe and non-toxic alternative to traditional corrosion inhibitors, with the potential to be more effective and reliable. Additionally, the results of this study can be used to develop strategies for the design of novel inhibitors with improved properties. Thus, this work provides a comprehensive overview of the efficacy of corrosion inhibitors, which can be used to inform and guide future research in this field.

2 Quantum computational details

According to the frontier molecular orbital (FMO) hypothesis, the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) are frequently related to inhibitor compounds’ capacity to give and take electrons, respectively. The term HOMO energy (E_HOMO) refers to an inhibitor molecule’s proclivity to donate electrons to the metal’s empty molecular orbitals (LUMO) (Mamand 2019; Mamand and Qadr 2021). In turn, LUMO energy (E_LUMO) denotes the inhibitor compounds’ capacity to take electrons from the metal’s occupied molecular orbitals (OMO) (Koparir et al. 2022a; Zhuo et al. 2012). High E_LUMO values indicate that the effect of specific takes electrons more readily, which is not regarded as an effective corrosion defender because it does not tend to avoid metal degradation. The underlying idea is that for good corrosion inhibition, a molecule’s E_LUMO must be lower than its E_HOMO.

In quantum chemical investigations, E is an important quantitative parameter for the prediction of corrosion IE. A theoretical measure representing the construction barrier and verification of several molecular systems. E is calculated using Equation (1).

Electron affinity is the energy produced when an electron is bonded to a gas phase atom, whereas ionization potential is the maximum energy required to remove an electron from many-electron atoms in a gas phase (equations (2) and (3)).

Equations (4) and (5) were used to compute the ionization potential (IP) and electron affinity (EA).

The more efficient the inhibitor, the greater the χ value, and conversely. Global hardness (η) considers the evaluation of an atom’s resistance to charge transfer, whereas (σ) defines an atoms or group of atoms’ ability to receive electrons. The following formulae are used to calculate these characteristics.

In general, hard and soft molecules actually require small and large E_s, correspondingly. As a result, soft compounds are more reactive than hard molecules because they may easily supply electrons to an acceptor system. Furthermore, adsorption is most likely to take place at the location of a molecule where softness value is the greatest. The (μ) estimate of polarity in a bond, which incorporates electron distribution in a molecule, is a potent metric that is widely used to predict corrosion inhibition. High (μ) inhibitors create strong dipole-dipole interactions with the metal, resulting in robust adsorption onto its metal surface and greater inhibition efficiencies.

A high electrophilicity index value indicates a good electrophile, whereas a low electrophilicity index value indicates a poor nucleophile. According to equation (9), the link between chemical hardness and electrophilicity yields a global electrophilicity index (ω).

The following expression may be used to calculate N:

where χinh is the inhibitor electronegativity and (w) denotes the work function, ηFe,ηinh and Fe and inh the inhibitor global hardness. For the Fe (110) surface, the work function is usually stated as w = 4.82. When ∆N>0, electron transfer occurs between an inhibitor molecule and the metal surface, and when ∆N>3.6, the electron donating capacity of an inhibitor molecule is boosted.

3 Results and discussion

DFT is a very potent technique in quantum chemistry. It’s a rising star in theoretical modeling. Figure 1 depicts the structures of the selected inhibitors investigated. Figure 1 shows that the chloroquine compounds under consideration include amino groups. Figure 2 depicts the frontier molecular orbital structures of the optimized amino acids compounds using DFT/B3LYP/6-311G++(d,p). E_HOMO, E_LUMO, E_HOMO+1, E_LUMO−1, separation energy ∆E, dipole moment, electron affinity (EA), ionization potential (IP), global electrophilicity, softness, chemical hardness, electronegativity, total energy of electron transfer N, and nucleophilicity are suggested quantum chemical parameters that may be responsible for the inhibition efficiency of the investigated molecules based on the calculations. The adsorption of molecules on metallic surfaces can be explained by the concept of highest occupied molecular orbital energy level (HOMO). It is a measure of the ability of the molecule to donate its electrons. When a molecule is placed in close proximity to the metallic surface, its HOMO energy level becomes very close to the free electron energy level of the metal. This allows for the electrons of the molecule to be transferred to the metal, thus leading to the adsorption of the molecule on the metal surface (Guo et al. 2020a; Omer et al. 2022c; Qadr and Mamand 2021). The electron donating inclination (E_H) of a molecule is a measure of its intrinsic ability to donate electrons to a suitable acceptor. This acceptor must have a lower highest occupied molecular orbital (HOMO) energy and an empty molecular orbital. On the other hand, electron receiving propensity (E_L) measures a molecule’s capability to accept electrons and is determined by the energy of its lowest unfilled molecular orbital (Mamand et al. 2022c). By using computational methods, the energy gap (∆E = E_LUMO-E_HOMO) between the lowest unoccupied molecular orbital (LUMO) and highest occupied molecular orbital (HOMO) of the inhibitor molecule was calculated. Additionally, the dipole moment (l), the electron charge on hetero-atoms such as nitrogen, sulfur, and oxygen, and the overall energy of the inhibitor molecule were also determined. As a result of these calculations, it is possible to estimate the inhibitor molecule’s intrinsic electron-donating capacity and to assess its interaction with the metal substrate (Aktaş et al. 2022; Mamand and Qadr 2022). The frontier molecular orbital hypothesis of chemical reactivity states that electron transitions occur when the reacting species’ highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) come into contact. The HOMO energy is directly related to the ionization potential, which determines how prone the molecule is to attack from electrophiles. Similarly, the LUMO energy is closely connected to the electron affinity and how susceptible the molecule is to attack from nucleophiles. The lower the LUMO energy values, the better the compound’s ability to receive electrons, which will undoubtedly increase the adsorption and inhibition efficacy of the inhibitory molecule on the metal surface (Koparir et al. 2020). The inhibitory efficacy of substances Cys, Lys, Val, S-Met Gly, and Glu, according to a comparison of the experimental and theoretical results in Tables 1–8. The variation in the number of carbon atoms in the chain of radical «R» explains this behavior. The inhibitory effectiveness decreases as the amount of CH₂ groups in the radical «R» of the molecule increases (Aouniti et al. 2013).

Figure 1:

Molecule structures of amino acids.

Figure 2:

HOMO, LUMO, and optimizes structures of selected amino acids based on DFT calculation at 6-311++G(d,p) and B3LYP level in gas and water phases at protonated and non-protonated species.

The energy differential (∆E) between a molecule’s HOMO and LUMO relates inhibitor reactivity with metal surface adsorption. A drop in inhibitor ∆E value improves the reactivity between the inhibiting compound and the metal ion and hence increases the binding properties on the metal surface. Because the energy needed to remove the electron from the final occupied orbital is minimal, this increase in binding ability may lead to an increase in inhibitor inhibition efficiency (%IE). The value of ∆E fell in the following sequence for the six molecules Tables 1–6: L-lysine > S-methyl > L-cysteine > L-glycine > valinin > L-glutamine, indicating that L-glutamine has the smallest energy difference and the highest reactivity, making it the best inhibitor among the six molecules. The energy of HOMO (highest occupied molecular orbital) and LUMO (lowest unoccupied molecular orbital) were found to be essential in determining the molecule’s capacity to attach to the metal’s surface; a higher HOMO energy and lower LUMO energy suggests a better reactivity. According to the study, a bigger energy gap value suggests poor reactivity to a chemical species since the energy gap is connected to the softness or hardness of a molecule. Hard molecules have a larger energy gap, making them less reactive compared to soft molecules.

The orientation of the corrosion inhibition process is predicted by the dipole moment (μ) of inhibitory compounds. It includes details on the polarity of a molecule’s link as well as the distribution of electrons in the molecules. Inhibitors with a large dipole moment tend to adsorb more readily on the surface of a metal, resulting in greater inhibition. The compounds under investigation are detected in the following order: L-glutamine > L-lysine > S-methyl > L-cysteine > L-glycine > valinin. Because the application to predict the direction of a corrosion inhibition response is inconsistent in the literature, it is widely known that the adsorption of polar chemicals high on the surface of the metal should improve inhibition efficacy. The polarizability of the compounds investigated follows the order: L-lysine > S-methyl > L-cysteine > L-glycine > valinin > L-glutamine, showing that L-glutamine may have superior inhibitory efficacy. The inhibitory efficiency of the compounds investigated in terms of polarizability may thus be in the same sequence.

The reactivity and stability of a molecule are determined by its total energy, which is composed of all forms of kinetic motion (translation, vibration, and rotation) as well as all structures of potential energy (electrostatic interaction between charges, magnetic interactions among both spinning charges, and energy stored in bonds). This energy is not only present in the bonds of organic compounds but also in the free-conduction electrons of metals. To determine the total energy, researchers must use a combination of both experimental observations and theoretical results to arrive at an accurate number. Generally, the greater the total energy, the more stable the molecule is, and therefore less likely to donate. This has been proven to be true both experimentally and theoretically, with the results of both showing good agreement. The results show that depending on lowering values of total energy, the tendency for the variability of inhibitory efficiency maintains the following procedure: L-lysine > S-methyl > L-cysteine > L-glycine > valinin > L-glutamine.

The formation of coordination bonds between the unprotonated N and S atoms and the vacant orbitals of Fe atoms is responsible for adsorption, which increases the affinity between the inhibitor molecule and the electrode surface. As a result, cationic species can be adsorbed more effectively on the cathode surface, thus reducing the rate of the hydrogen evolutionary process. In order to assess the inhibitory efficacy of the molecules, several variables must be taken into account, including the number of adsorption active centers in the compound, the charge distribution, the size of the molecule, the mechanism of adsorption, and the formation of the metallic complex. The presence of electron donor groups (N, O, S) in the molecular structure of the amino acid is essential for the inhibition of corrosion, as the presence of free electron pairs in nitrogen, sulfur, and electron on a double bond significantly contributes to the adsorption of the inhibitor. Atoms within molecules are known to have a tendency to attract the shared pair of electrons closer to themselves, and this is referred to as electronegativity. Electronegativity is a measure of the ability of an atom to attract electrons when it is involved in a chemical bond. Electronegativity values can be compared between different atoms to determine the polarity of a molecule, as well as how strongly the atoms within a molecule are bound together. Electronegativity is an important factor in many chemical processes, such as the formation of ionic and covalent bonds. Tables 1–6 provide a comprehensive overview of the electronegativity values of the compounds studied. Sanderson’s theory of electronegativity equalization claims that when the electronegativity difference between two compounds is low, like it is with valinin and L-glutamine (3.92 eV), they reach electronegativity equalization quickly, which indicates minimal reactivity and subsequently a weak inhibitory power. The sequence of electronegativity difference from highest to lowest is as follows: L-lysine (highest), S-methyl, L-cysteine, L-glycine, valinin and L-glutamine (lowest) (Kaya et al. 2016a). The electron transfer is driven by the variation in electronegativity, while the total of the hardness parameters serves as resistance. To compute the proportion of electrons transmitted, a theoretical value for iron absolute electronegativity, and a global hardness of ηFe=0 and χFe=7 eV, were employed, considering that for a metallic bulk I = A because they are softer than neutral metallic atoms.

These conclusions could be described further by the fact that in oxygenated solutions (i.e., with dissolved oxygen), where the metal surface is oxidized, the ability of the amino acid to provide corrosion inhibition is about its proclivity to establish hydrogen bonds with the oxide or hydroxide species on the surface of the metal. The number of N–H connections in amino acid molecules should be proportionate to this capacity.

Back-donation is a chemical process in which electrons move from one atom’s atomic orbital to the adequate symmetrical anti-bonding orbital of a -acceptor ligand. The electrons of the metal are utilized to attach to the ligand, therefore alleviating the metal of excess negative charge. As a consequence, the bonding becomes partially double-bonded. Back bonding shortens bonds while enhancing bond order. Back-bonding is a type of resonance that can be seen. Back-bonding enhances stability in principle. It influences molecular characteristics like hybridization and dipole moment. Depending on the charge transfer theory, which is one of the essential parameters in this study for charge donation and back donation, based on this attribute, the electronic back donation process may also influence the interaction between the inhibitor molecule and the metal surface. According to this theory, if both electron transfer to the compound and return donation from the compound are occurring at the same time. Back donations from molecules to metals have a better and more efficient effect in terms of energy if ΔEb−d>0 or ΔEb−d<0. The results obtained in Tables 1–8 are ΔEb−d>0, which is clear evidence that charge transfer to A molecule and then donating back from the molecule is energetically advantageous. On this basis, we can conclude that the inhibition efficiency increases when there is a better environment. The inhibition efficiency must improve due to the adsorption of molecules on the metal surface when the stabilization energy generated by the contact between the metal surface and the inhibitor increases.

Absolute hardness and softness are critical qualities for determining molecule stability and activity. Chemical hardness clearly denotes the resistance to deformation or polarization of the electron cloud of atoms, ions, or molecules under tiny perturbations of a chemical process. The energy gap between hard and soft molecules is considerable for hard molecules and small for soft molecules. In our current investigation, L-lysine with a low hardness value of 0.058 (eV) has a modest energy gap when compared to other compounds. Typically, the inhibitor with the lowest global hardness (and hence the highest global softness) is predicted to have the best inhibitory effectiveness.

Adsorption might occur in the portion of the molecule where softness (σ), a local attribute, has the largest value for the easiest transport of electrons. L-lysine has the maximum inhibition efficiency, with a softness value of 14.46 eV. The maximum number of transferred electrons (ΔNmax) in amino acid structures was estimated in this study. All results are shown in Tables 1–8. It was noted that a positive number of transferred electrons (ΔNmax) indicates that molecules act as electron acceptors, and molecules act as electron donors if there is a negative number of transferred electrons ΔNmax<3.6 (Kaya et al. 2016b). Consequently, the inhibition efficiency improves as the electron-donating ability of these inhibitors to the metal surface increases. According to Lukovits et al., the corrosion inhibition efficiency is improved if ΔN<3.6, with the increase in electron donating ability of the metal surface. The specified molecules studied in this work have charge transfer properties towards the metal surface see Figure 3.

Figure 3:

Electrostatic map potential in the gas phase and aqueous phase for all study compounds.

Electrophiles take electron pairs whereas nucleophiles provide electron pairs. A base is any chemical that can contribute an electron pair to create a covalent bond, while an acid is any molecule that can take an electron pair (Erdoğan et al. 2017). As a result, acids must be electrophiles, while bases would have to be nucleophiles.

The skeletons of the selected examined amino acids are nearly identical (with the exception of a –SH group in Cys and a meth-related sulphur group in the S-MCys structure). As publicly confirmed by chemical and electrochemical investigations conducted here, the inhibitory performance of these three amino acids declined in the following order: L-glutamine > L-lysine > S-methyl > L-cysteine > L-glycine > valinin. This sequence is explained by the fact that sulphur-containing amino acids may be successfully adsorbed via the S-moiety (Group). Indeed, Cys is a really fascinating amino acid with good acid inhibitor properties. It comprises, in combination with the amino group, the –SH group, which has a high affinity for adsorption and so blocks additional corrosion areas on the surface of the electrode.

4 Fukui function analysis

The Fukui indices were used to assess the local reactivity of the compounds. This index is an indicator of charge transfer and is indicative of the reactive areas as well as the substance’s nucleophilic and electrophilic behavior. The regions of a compound with a high Fukui function are chemically softer than the regions with a small Fukui function. By utilizing the HSAB principle, one can determine the behavior of the various sites in regard to hard or soft chemicals. This method of analysis enables us to determine the reactivity of the different sites of the compounds and examine how they interact with other molecules. The fraction of the electronic density ρ(r→) with regard to the number of electrons N at a steady external potential σ(r→) is described as the Fukui function f(r→).

If the effects of relaxation resulting from the build-up or discharge of electric charges are neglected, then the accuracy of the resulting analysis could be compromised. Such relaxation effects can often be significant and should not be overlooked, as they can have a dramatic influence on the outcome of such an analysis. Furthermore, these effects can vary significantly depending on the type of material being studied and must be taken into account when performing any type of electrical analysis.

Density of the highest and lowest molecular orbitals are ρHOMO(r→) and ρLUMO(r→). The finite difference assumptions using the Mulliken statistical method of atoms in amino acid compounds are used to find the condensing Fukui functions, based on the direction of the electron transfer.

In a neutral atom k the electronic potential in anionic and cationic system denoted by qN,qN+1 and qN−1. where qk denotes the net charge of atom k in the compound, i.e. the electron density at a location r in orbit surrounding the molecule. The number N represents the number of electrons in the molecule. N₊₁ is an anion, with an electron transferred to the neutral molecule’s LUMO. N₋₁ is the cation that has an electron withdrawn from the neutral molecule’s HOMO. The ground-state topology is used for all computations. But use an atomic charge separation technique, such as the Mulliken statistical method, these functions may be compressed to the nuclei. Fukui does his duties. Instead of computing the molecular orbitals for the neutral, cation, and anion, we may simply add or delete electrons from the neutral molecule’s molecular orbitals. This methodology is not as satisfactory as the one explained above, but it does give a quick graphical representation of the susceptibility of various types of attacks. But instead of providing a conclusive computation of a molecular property, freezing the atomic orbitals to those of the neutral molecule offers a valuable graphical methodology that can be decided to apply quickly.

Mulliken atomic charges for the compounds investigated are shown in Figure 4. It is assumed that the more negative the atomic charges of the adsorbed center, the more readily the atom gives its electrons to the metal/metal oxide’s empty orbital, nitrogen and sulfur atoms have negative charge centers that might give electrons to the iron surface to establish a coordinate-type connection.

Figure 4:

Mulliken charge distribution.

5 Molecular dynamic simulation (MDS)

The analysis of this figure demonstrates that the inhibitor molecule investigated has significant interactions with the Fe atoms. Figure 5 shows that the inhibitor was capable of adsorption on the surface. The close interaction between the aromatic rings and the heteroatoms (N and O) of this restriction and the transition metal can be due to this mechanism of adsorption. The total energy of the substrate-adsorbate composition, in kJ/mol, is one of the values shown in Tables 7–9. The total energy is described as the sum of the adsorbate component energies, the stiff adsorption energy, and the deformation energy, and adsorption energy reflects the energy produced (or needed) when the relaxed adsorbate element was adsorbed on the substrate. The adsorption energy is defined as the sum of the stiff adsorption energy and the adsorbate component’s deformation energy. The stiff adsorption energy represents the energy generated (or required) when the unrelaxed adsorbate component was adsorbed on the substrate prior to the iterative refinement stage. The energy produced when the deposited adsorbate constituent was loosened on the substrate surface is reported as the deformation energy. Finally, (dE_ad/dN_i) gives the energy of substrate-adsorbate combinations in which one of the adsorbate components is missing (Erdoğan et al. 2017). Furthermore, the results reveal that the researched compound’s negative adsorption energy value supports its inhibitive function and is consistent with the experimental results. Amino acids have already been found to be effective corrosion inhibitors for Cu, Al, Sn, and iron, with inhibitory activity varying depending on the metal and the corrosive media (Awad et al. 2017; Tkalenko et al. 2010). It has been shown that amino acids with sulphur and longer hydrocarbon chains block the enzyme significantly (Ashassi-Sorkhabi and Asghari 2010; Zhang et al. 2008). The bulk of amino acid corrosion inhibition research is focused on copper, aluminum, and iron.

Figure 5:

Top and side views of the most stable low energy configuration for the adsorption for all selected amino acids in this study.

Copper is a commonly utilized material in many engineering settings because of its high electrical and thermal conductivity and high electrical and thermal conductivity; nevertheless, its corrosion resistance decreases as the aggressive solvent concentration increases (Elmorsi and Hassanein 1999; Zucchi et al. 2004). The most practical way for preventing corrosion in acidic situations is to utilize chemical inhibitors (Mihit et al. 2006). Studies have been carried out to investigate the effectiveness of organic compounds in shielding metals from corroding in harsh acidic environments. Much research has been conducted to investigate the behavior of copper and copper alloys in various corrosive conditions (Dafali et al. 2003; Salghi et al. 2000). As depicted in Figure 5, this study examined the top and side surfaces of all the molecules utilized, encompassing iron, copper, and aluminum. For further research and understanding of the properties of these materials and changes in adsorption energy. That the best antibody has the most negative value of adsorption energy, which is in full agreement with the practical results as well as the previous results obtained by DFT, as shown in Tables 7–9.

This study found that Cys had a higher inhibitory efficacy than the other amino acids evaluated. It is well understood that the majority of organic substances used as corrosion inhibitors may adsorb on the metal surface via heteroatoms such as nitrogen, oxygen, sulfur, and phosphorus. Its inhibition efficiency might be following the L-lysine > S-methyl > L-cysteine > L-glycine > valinin > L-glutamine order. The inclusion of S–H in the molecular structure of Cys increases the efficacy of inhibition. The group SH is more of an electron donor, and it provides the option of being an adsorption centre with the nitrogen atom. The nitrogen atom in the aliphatic chain improves the contact of molecules with the metal surface in the instance of Lys.

6 Conclusions

DFT is a powerful technique in quantum chemistry which provides a detailed understanding of the inhibition efficiency of amino acid molecules. By analyzing the different quantum chemical parameters, such as the energy gap (∆E = E_LUMO-E_HOMO), dipole moment (μ), electron charge on hetero-atoms, total energy, electronegativity, and back-donation, it is possible to determine the adsorption and inhibition efficacy of the molecules on the metal surface. The inhibitory efficacy of the molecules, according to the analysis, is in the sequence of L-glutamine > L-lysine > S-methyl > L-cysteine > L-glycine > valinin. The polarizability of the compounds follows the same sequence, indicating that L-glutamine may have superior inhibitory efficacy. Additionally, the total energy of the compounds follows the sequence of L-lysine > S-methyl > L-cysteine > L-glycine > valinin > L-glutamine, suggesting that L-glutamine has the highest reactivity and hence the best inhibitor among the six molecules. The ability of an amino acid inhibitor to protect a metal surface from corrosion depends on the hardness and softness of the molecule. The inhibitor with the lowest global hardness (and highest global softness) is predicted to have the best inhibitory effectiveness. Sulphur-containing amino acids, such as L-cysteine and S-methyl, are particularly effective because of their high affinity for adsorption. The inhibitory performance of the selected amino acids was determined to be in the following order: L-glutamine > L-lysine > S-methyl > L-cysteine > L-glycine > valinin. Fukui index is an important tool for analyzing the local reactivity of a compound, and provides insight into the chemical hardness or softness of different sites. By taking into account the relaxation effects, which can vary depending on the type of material, the accuracy of the analysis can be improved and more reliable results can be obtained. Amino acids have been found to be effective corrosion inhibitors for Cu, Al, Sn, and iron, and this research further expands our understanding of how these molecules can be used to inhibit corrosion.