A comparative DFT investigation of the corrosion inhibition performance of carbohydrate-based mono- and disaccharide derivatives on Al(111)

Abstract

Carbohydrate derivatives representing different structural categories such as open-chain monosaccharides (glucose and fructose), cyclic monosaccharides (D-glucose, D-β-fructofuranose, and D-galactose), and disaccharides (sucrose, maltose, and β-lactose) were examined as potential eco-friendly corrosion inhibitors on the Al(111) surface, using Density Functional Theory (DFT) to identify and compare their inhibition efficiency and adsorption behavior. A combination of quantum chemical descriptors derived from DFT and periodic DFT calculations (PBC-DFT), aimed at elucidating the corrosion inhibition mechanism on the Al(111) surface. The results demonstrate that sucrose and β-lactose exhibit the highest adsorption energies, at −46.197 and −44.561 kcal/mol, respectively, compared to their analogues. In addition, glucose (OC), fructose (OC), sucrose, maltose, and β-lactose adsorb onto the Al(111) surface via coordinate covalent O–Al bond formation, indicating chemisorption as the predominant adsorption mechanism. In contrast, the cyclic monosaccharides D-glucose, D-β-fructofuranose, and D-galactose adsorb onto the Al(111) surface without forming covalent bonds, suggesting that the adsorption process is governed by physisorption rather than chemisorption.

Keywords

DFT corrosion inhibitors carbohydrate derivatives reactivity descriptors inhibition mechanism Al(111) surface

Introduction

Aluminum and its alloys naturally possess corrosion resistance.^1–3 However, aluminum can still be vulnerable to corrosion in specific conditions, a process that may degrade metal surfaces under the influence of environmental factors, particularly moisture, which saturated with oxygen that serving as a critical factor in the development of corrosion cells.^4,5 Over the past two decades, researchers have increasingly focused on natural organic inhibitors due to their eco-friendly and sustainable nature. In addition, these compounds have demonstrated remarkable potential owing to their rich structural diversity and functional adaptability.^6,7 Organic molecules containing heteroatoms such as oxygen, nitrogen, and sulfur, along with conjugated π-systems, are particularly effective in interacting with metallic surfaces through adsorption.^8–10

Carbohydrate-based (saccharide) inhibitors^11–14 have gained increasing attention as environmentally friendly alternatives due to their non-toxic, biodegradable nature, wide availability, and distinctive molecular architectures. These structures are particularly rich in oxygen-containing functional groups and, in some derivatives, aromatic rings, which collectively enhance their ability to interact with metal surfaces through adsorption processes.

B. Müller¹⁵ studied the corrosion inhibition of aluminum and zinc pigments using various saccharides, including the reducing sugars fructose and mannose, the non-reducing sugar saccharose, and ascorbic acid (vitamin C). The results showed that hydrogen-induced corrosion of aluminum pigments in aqueous alkaline media was effectively inhibited by fructose, mannose, and ascorbic acid. In contrast, saccharose, as a non-reducing sugar, exhibited no inhibitory effect.

Araceli Espinoza Vázquez et al.¹⁶ investigated the effectiveness of various carbohydrates as corrosion inhibitors for API 5L X70 steel in a 1 M HCl acidic medium, evaluating both commercially available carbohydrates, such as glucose, galactose, and lactose and synthesized derivatives. The study revealed that glucose exhibited superior inhibitory performance compared to galactose, with all investigated carbohydrates following a mixed chemical and physical adsorption mechanism.

Linrui Ma et al.¹⁷ investigated a novel eco-friendly corrosion inhibitor, dithiocarbamate-modified glucose (DTCG), synthesized from glucose via amination and nucleophilic addition reactions. Their study focused on evaluating the anti-corrosion performance of DTCG on copper in a 3 wt% NaCl solution, utilizing both experimental and theoretical approaches. The results demonstrated that DTCG achieved a maximum inhibition efficiency exceeding 96%, as confirmed by multiple analytical techniques. Acting as a mixed-type inhibitor, the effectiveness of DTCG was further validated by Density Functional Theory (DFT) calculations, which were in strong agreement with the experimental results.

Dheeraj S. C. and co-workers,¹⁸ investigated hexamethylenediamine-functionalized glucose as a novel eco-friendly corrosion inhibitor for copper in a 3.5% NaCl solution. Electrochemical techniques (EIS, polarization, SECM) along with surface analyses (SEM, ATR-IR) confirmed the effective corrosion inhibition by DHA, attributed to its adsorption on the copper surface.

Over the past decades, quantum chemical methods and molecular dynamics simulations^19–22 have emerged as powerful and efficient tools for accurately predicting chemical reactivity and evaluating the corrosion inhibition performance of organic molecules. Numerous computational chemistry studies^23–27 have been carried out to rationalize the observed anti-corrosion mechanisms and molecular reactivity by analyzing electronic properties and clarifying the nature of interactions, whether through chemical adsorption (chemisorption) or physical adsorption (physisorption) on metal surfaces.

To the best of our knowledge, no comprehensive review in the available literature has systematically compiled, analyzed, and compared the structural diversity of monosaccharides and disaccharides, together with their corresponding tautomers, within a unified framework. Furthermore, no study has applied consistent computational methodologies using conceptual DFT and periodic boundary condition (PBC) calculations to quantitatively assess their inhibition efficiency and adsorption mechanisms.

This study primarily aims to unveil and investigate the corrosion inhibition mechanisms of eight saccharide derivatives (Figure 1) on the aluminum Al(111) surface, employing computational chemistry approaches. The selected compounds include open-chain monosaccharides (glucose and fructose), cyclic monosaccharides (D-glucose, D-β-fructofuranose, and D-galactose), and disaccharides (sucrose, maltose, and β-lactose). We first investigated and compared the relationship between the inhibition efficiency and the molecular structures of the eight inhibitors. Subsequently, we identified their most reactive sites using global and local reactivity descriptors derived from density functional theory (DFT). Finally, we elucidated and compared the adsorption behavior of these inhibitors on the Al(111) surface. Subsequently, we complemented our investigation with adsorption modeling employing first-principles methods, providing a comprehensive understanding of the inhibition mechanisms. This research is expected to contribute to developing sustainable, high-performance corrosion inhibitors for various industrial applications.

Figure 1.

2D representations of the molecular structures of the analyzed saccharide derivatives.

Despite the growing interest in carbohydrate-based corrosion inhibitors, previous studies have mainly focused on individual or chemically modified saccharides and were largely conducted on copper or steel surfaces. For example, Müller¹⁵ and Espinoza-Vázquez et al.,¹⁶ as well as Ma et al.¹⁷ and Dheeraj et al.,¹⁸ investigated carbohydrate inhibitors using experimental and DFT approaches but without a systematic structural comparison and rarely addressing aluminum surfaces.

Consequently, a comparative understanding of how molecular structure influences corrosion inhibition on aluminum remains limited.^11–14 In contrast, the present work systematically examines eight structurally diverse saccharides using a unified approach that combines conceptual DFT descriptors with periodic boundary condition adsorption calculations on the Al(111) surface, thereby clearly establishing the novelty and significance of this study.

Computational details

Quantum chemical calculations

The molecular electronic structures of the eight investigated carbohydrate-based mono- and disaccharide derivatives, including glucose (OC), fructose (OC), D-glucose, D-β-fructofuranose, D-galactose, sucrose, maltose, and β-lactose, illustrated in Figure 1, were optimized using Density Functional Theory (DFT) with the B3LYP functional²⁸ and the def2-TZVPP triple-ζ basis set,²⁹ as implemented in the ORCA software (version 5.0.4).³⁰ The solvent effect was accounted for using the SMD model (Solvation Model based on Density).³¹

Optimized molecular geometries and their associated frontier molecular orbital distributions (HOMO and LUMO) of the investigated carbohydrate were visualized using IboView software.³² All Fukui isosurface maps were calculated using the VMD program,³³ based on the cube files (.cub) generated by Multiwfn software.³⁴ Partial atomic charges were determined through natural population analysis (NPA) using the JANPA software package.³⁵ The molecular electrostatic potential (MEP) was generated with the ORCA package (orca_plot) and visualized using the UCSF Chimera program (version 1.10.2).³⁶

Global reactivity descriptors (global quantities) based on conceptual DFT^37,38 were employed to analyze and compare the chemical reactivity of the eight studied saccharides and to investigate correlations between their molecular electronic structures and reactivity profiles. In addition, the local reactivity of the eight studied saccharides was predicted using the condensed Fukui index.^39,40

f_{k}^{+} = q_{K} (N + 1) - q_{K} (N) (N u c l e o p h i l i c a t t a c k)

(1)

f_{k}^{-} = q_{K} (N) - q_{K} (N - 1) (E l e c t r o p h i l i c a t t a c k)

(2)

where,

q_{K}

represents the gross charge of atom k within the molecule, and N denotes the number of electrons in the molecule in its neutral state. N + 1 and N−1 correspond, respectively, to the anionic and cationic species.

Solid state DFT calculations

First-principles calculations based on Density Functional Theory (DFT) with periodic boundary conditions (PBC), as implemented in the Quantum ESPRESSO software package (version 6.4.1),⁴¹ were employed to examine the adsorption behavior and corrosion inhibition mechanism of our optimized mono- and disaccharide derivatives (B3LYP/def2-TZVPP) on the aluminum Al(111) surface.

A 5 × 5 periodic slab supercell of the Al(111) surface was constructed with a vacuum gap of 20 Å along the z-direction. The supercell comprised 75 atoms distributed across three atomic layers, each containing 25 atoms, with only the bottom layer fixed during the calculations to mimic bulk constraints, as shown in Figure 7.

For the geometry relaxation calculations, a 2 × 2 × 1 Monkhorst–Pack k-point mesh was employed for Brillouin zone (BZ) sampling.⁴² The Kohn–Sham orbitals were expanded in a plane-wave basis set, with an energy cutoff of 30 Ry and a charge-density cutoff of 250 Ry. To avoid interactions between periodic images, a dipole correction following Bengtsson was applied,⁴³ and van der Waals interactions were accounted for using the Grimme DFT-D2 correction parameter.⁴⁴

The adsorption energy between the studied saccharide inhibitors and Al(111) surface can be calculated using the following equation.^45,46:

Δ E_{a d s} = Δ E_{(A l (111) - i n h)} - (Δ E_{A l (111)} + Δ E_{i n h})

(3)

where

Δ E_{A l (111) - i n h}

Δ E_{A l (111)}

and

Δ E_{i n h}

represent the energies of the Al(111)inhibitor complex, Al(111) surface, and isolated inhibitor molecule, respectively. However, the maximum adsorption energy is identified as the most negative value obtained during the simulation process.

Results and discussion

Quantum DFT calculations

Recently,^47–49several researchers have used conceptual DFT based modeling approaches to better understand the chemical behavior of various systems and to identify the relevant descriptors used for comparing different chemical substances, as well as to explore phenomena such as adsorption.^50,51

It is well established in the literature that the highest occupied molecular orbital energy and lowest unoccupied molecular orbital energy (HOMO and LUMO) are associated with a molecule's ability to donate and accept electrons, respectively. Additionally, the stability of a molecule is related to the significant energy gap (ΔE_gap) between the HOMO and LUMO. A small ΔE_gap indicates high reactivity, thereby denoting a highly efficient inhibitor.^23–25

The data presented in Table 1 clearly indicate that glucose and fructose in their open-chainforms (open conformation) exhibit markedly higher chemical reactivity, as evidenced by their relatively low ΔE_gap values (5.844 eV and 6.042 eV, respectively). This heightened reactivity contrasts with the values observed for the other compound classes examined, namely the cyclic monosaccharides (D-glucose, D-β-fructofuranose, and D-galactose) and the disaccharides (sucrose, maltose, and β-lactose), which display comparatively larger ΔE_gap values that reflect lower reactivity.

Table 1.

Calculated reactivity descriptors^(a) of studied carbohydrate derivatives.

Descriptors		E_HOMO (eV)	E_LUMO (eV)	ΔE_gap (eV)	μ (Debye)	< α > (a.u.)	TE (a.u.)
Monosaccharides Open-Chain (OC)	Glucose	−7.099	−1.255	5.844	1.290	132.711	−687.14
Monosaccharides Open-Chain (OC)	Fructose	−7.139	−1.097	6.042	3.540	133.544	−687.15
Monosaccharides Cyclic	D-Glucose	−7.095	0.962	8.057	3.145	132.270	−687.16
	D-β-fructofuranose	−7.134	0.857	7.991	5.098	130.643	−687.15
	D-Galactose	−7.144	0.975	8.118	4.854	131.516	−687.16
Disaccharides	Sucrose	−6.921	0.811	7.732	3.398	254.244	−1297.85
	Maltose	−7.193	0.812	8.005	3.543	256.888	−1297.87
	β-Lactose	−7.118	0.936	8.054	5.438	257.583	−1297.87

^(a): E_HOMO: Energies of highest occupied molecular orbital; E_LUMO: Energies of lowest unoccupied molecular orbital; ΔE_gap: LUMO-HOMO energy gap; μ: Dipole moment; <α>: Polarizability and TE: Total energy.

Since organic corrosion inhibitors typically function in aqueous environments, the pH value may vary, causing however a shift in the balance between protonated and deprotonated species. Under acidic conditions, ring-opening reactions cause the open-chain form to become more prevalent. In neutral or basic environments, however, the cyclic form remains thermodynamically favored. Therefore, in this raison both structural configurations of open-chain (linear) and ring-closed (cyclic) forms were investigated, to account for all possible molecular changes under varying pH conditions.

According to the results presented in Table 1, the other two studied classes of carbohydrates, comprising monosaccharides in closed conformations (D-glucose and D-β-fructofuranose) and disaccharides with two cyclic units (sucrose, maltose, and β-lactose), exhibit relatively similar ΔE_gap values. These values increase in the following order: sucrose (7.732 eV) < D-β-fructofuranose (7.991 eV) < maltose (8.005 eV) < β-lactose (8.054 eV), D-glucose (8.057 eV) < and D-galactose (8.118 eV).

Nevertheless, certain experimental and computational studies available in the literature^52,53 indicate that disaccharide derivatives, including sucrose, maltose, and lactose, are generally more effective as metal corrosion inhibitors than monosaccharides like glucose and fructose.

It is important to note that the high chemical reactivity of glucose and fructose, compared to their analogues (disaccharides), as validated by the conceptual DFT descriptor (ΔE_gap) and summarized in Table 1, does not carefully reflect their adsorption capability on the metallic surface. Indeed, adsorption depends on the adsorbate–adsorbent affinity, particularly on the molecular geometry and the spatial orientation of heteroatom-rich functional groups relative to the specific metal surface.

Based on the data presented in Table 1, it can be observed that the polarizability tends to increase with molecular volume, as indicated by the van der Waals volume (V^vdw) and surface area (SA), calculated using the GEPOL algorithm. The trend follows the order: Glucose “OC” (132.711) < Fructose “OC” (133.544) < D-Glucose (132.270) < D-β-fructofuranose (130.643) < D-Galactose (131.516) < Sucrose (254.244) < Maltose (256.888) < β-Lactose (257.583).

The results in Table 1 show that disaccharides with two-ring structures, such as sucrose, maltose, and β-lactose, exhibit the highest polarizability values due to their larger molecular volumes, compared to the monosaccharides in either open-chain or cyclic forms. This correlation between molecular size and polarizability is well established and has been consistently validated in previous studies.^54,55 This property is of notable importance, as it is widely recognized that the efficiency of inhibition increases with the extent of surface coverage provided by the inhibitor molecule on the metal substrate.

On the other hand, the inspection of the frontier molecular orbitals (FMO; HOMO and LUMO) density distributions for the optimized studied carbohydrates (Figure 2), reveals that the HOMO density for the Glucose and Fructose in their open-chain are delocalized on oxygen atom of carbonyl group. The HOMO densities for the studied monosaccharides (D-Glucose, D-β-fructofuranose, and D-Galactose) and disaccharides (Sucrose, Maltose, and β-Lactose) are strongly localized on the over molecule due obviously to the presence of several oxygen atoms, whether on the ring or on the various hydroxyl groups (see Figure 2).

Figure 2.

Frontier molecule orbital density distribution (HOMO and LUMO) of studied saccharides derivatives.

This observation thus suggests that for the Glucose and Fructose (open-chain) inhibitors would be preferentially adsorbed onto the metal surface by donating electrons via the unshared electron pairs on oxygen atome of carbonyl groupe to the d-orbitals of the metal surface, while for the monosaccharides (D-Glucose, D-β-fructofuranose, and D-Galactose) and disaccharides (Sucrose, Maltose, and β-Lactose) inhibitors, all the atoms in the structure are involved in the possible donation of electrons to the empty d-orbitals of the metal surface atoms.

Furthermore, based on the results of the FMO shown in Figure 2, the LUMO density distributions for Glucose and Fructose (open-chain) and for the monosaccharides (D-Glucose, D-β-fructofuranose, and D-Galactose) are mostly localized over the inhibitor molecules. In contrast, for the disaccharide inhibitors (Sucrose, Maltose, and β-Lactose), the LUMO is delocalized on a single side of the molecule, indicating that more susceptible reactive centers can accept electrons from the occupied d-orbitals of the metal surface.

Additionally, the local reactivity and site selectivity of the eight studied saccharide inhibitors were evaluated through Natural Population Analysis (NPA), Molecular Electrostatic Potential (MEP) surface analysis, and Fukui functions ( $f_{k}^{-}$ and $f_{k}^{+}$ ) calculations, highlighting the most reactive centers prone to nucleophilic and electrophilic attacks.

The MEP and NPA results are shown in Figures 3 and 4, respectively. Subsequently, the Fukui function maps are depicted in Figure 5 for monosaccharides and in Figure 6 for disaccharides.

Figure 3.

Molecular electrostatic potential (MEP) of studied saccharides derivatives.

Figure 4.

Natural population analysis (NPA) of studied saccharides derivatives.

Figure 5.

Isosurface Fukui maps of nucleophilic attack $f_{k}^{+}$ (right), electrophilic attack and electrophilicattack $f_{k}^{-}$ (left) for the studied monosaccharides.

Figure 6.

Isosurface Fukui maps of nucleophilic attack $f_{k}^{+}$ (right), electrophilic attack and electrophilicattack $f_{k}^{-}$ (left) for the studied dinosaccharides.

According to the analysis of the MEP surfaces (Figure 3), a similar behavior was observed across all eight studied saccharides, where regions of positive electrostatic potential (red zones), indicative of donor sites, are predominantly localized on the substituent groups associated with the oxygen atoms of the hydroxyl groups and carbonyl functionalities. In contrast, regions of negative electrostatic potential (blue areas) are primarily localized on the aromatic rings of both cyclic monosaccharides and disaccharides, whereas in open-chain monosaccharides, these regions are predominantly distributed along the main carbon backbone. These results indicate that the eight studied saccharides not only have the potential to adsorb onto the metal surface by donating electrons through their oxygen atoms, but can also accept electrons from the metal surface, thereby facilitating inhibition through a charge transfer process.

In addition, the results of the atomic charge distributions obtained from natural population analysis (NPA) reveal and confirm that the oxygen atoms in the hydroxyl groups and carbonyl functionalities of the eight inhibitors carry highly negative charges, identifying them as the most reactive sites capable of donating electrons (nucleophilic centers) to the unoccupied d-orbitals of the aluminum surface (see Figure 4).

Local reactivity was further examined using Fukui indices to identify and evaluate the most reactive sites susceptible to nucleophilic and/or electrophilic attacks. Fukui function maps corresponding to nucleophilic $(f_{k}^{+})$ and electrophilic $(f_{k}^{-})$ attack sites are presented in Figure 5 for monosaccharides and in Figure 6 for disaccharides.

The findings indicate that, for all monosaccharides examined (glucose, fructose, D-glucose, D-β-fructofuranose, and D-galactose), the primary reactive sites vulnerable to nucleophilic attacks $(f_{k}^{+})$ are predominantly located at all the hydroxyl groups, as evidenced by their relatively higher density distribution, depicted on the right side of Figure 5. In contrast, for electrophilic attacks $(f_{k}^{-})$ , the most reactive centers are situated on one side of each monosaccharide (either open-chain or cyclic forms), specifically at certain hydroxyl groups, as demonstrated by the large density distributions in verdun green color shown on the left side of Figure 5.

However, a similar pattern is observed for the disaccharides (sucrose, maltose, and β-lactose), where the most reactive sites for electrophilic attacks $(f_{k}^{-})$ are located at certain hydroxyl groups, particularly at the ends of the molecular structures of sucrose, maltose, and β-lactose, as shown on the left side of Figure 6. Meanwhile, nucleophilic attacks $(f_{k}^{+})$ on the studied disaccharides sucrose, maltose, and β-lactose are distributed across nearly all atoms, including the π orbitals of the heterocyclic pyrazine ring and the oxygen atoms of the hydroxyl groups.

Adsorption results

All eight studied saccharides, which were first optimized at the B3LYP/def2-TZVPP level of theory in the first part of this study, were subsequently examined to investigate their adsorption behavior and corrosion inhibition mechanism on the aluminum Al(111) surface. Figure 7 shows the slab model constructed using the Atomistix Toolkit package (QuantumWise A/S, academic version 2015.1),⁵⁶ where the inhibitors were initially placed in a perpendicular orientation to the Al(111) surface at a distance of 3 Å.

Figure 7.

Side and top views of Al(111) supercell.

The adsorption results, as shown in Figure 8, indicate that all investigated carbohydrate-based mono- and disaccharide derivatives (glucose, fructose, D-glucose, D-β-fructofuranose, D-galactose, sucrose, maltose, and β-lactose) exhibit negative adsorption energy values on the Al(111) surface, confirming the spontaneous nature of their adsorption process.

Figure 8.

Equilibrium adsorption geometries of the studied saccharide derivatives on the Al(111) surface, along with their corresponding adsorption energies.

The calculated adsorption energies indicate that the disaccharide inhibitors Sucrose, β-Lactose, and Maltose exhibit the most negative values, at −46.197 kcal/mol, −44.561 kcal/mol, and −31.565 kcal/mol, respectively, compared to the monosaccharide derivatives. The adsorption energies follow the decreasing order: Sucrose (−46.197 kcal/mol) > β-Lactose (−44.561 kcal/mol) > Maltose (−31.565 kcal/mol) > D-Glucose (−28.153 kcal/mol) > Glucose ‘OC’ (−26.580 kcal/mol) > D-β-fructofuranose (−22.260 kcal/mol) > Fructose ‘OC’ (−20.300 kcal/mol) > D-galactose (−16.370 kcal/mol).

According to the results of the adsorption study, only the monosaccharides Glucose (OC) and Fructose (OC), along with the disaccharides Sucrose, Maltose, and β-Lactose, are able to adsorb onto the Al(111) surface through the formation of coordinate covalent O–Al bonds between the oxygen atom of the inhibitor and the nearest aluminum atom on the Al(111) surface. This finding supports and confirms that chemisorption is the adsorption mechanism for these inhibitors. In contrast, the adsorption of the three cyclic monosaccharides (D-Glucose, D-β-Fructofuranose and D-Galactose) onto the Al(111) surface, although supported by their negative adsorption energy values, occurs without the formation of covalent bonds, as shown in Figure 9, indicating that the adsorption process involves physisorption.

Figure 9.

Equilibrium adsorption geometries of the studied saccharide derivatives on the Al(111) surface, highlighting the distances between the closest atoms of the inhibitors and the Al(111) surface.

As illustrated in Figure 9, the disaccharide Sucrose inhibitor adsorbs onto the Al(111) surface via the oxygen atom of one of its hydroxyl groups, forming an O–Al bond with a bond length of 1.592 Å. This value is markedly shorter than the combined covalent radii of aluminum and oxygen ( $r_{O}^{c o v}$ + $r_{A l}^{c o v}$ = 0.60 + 1.25 = 1.85 Å),⁵⁷ reflecting a strong interaction between the sucrose molecule and the aluminum Al(111) surface. This bond length strongly implies that the adsorption process is predominantly governed by chemisorption.

Maltose and β-Lactose, which appear to be the most effective inhibitors after sucrose according to the calculated adsorption energies, form bonds between the oxygen atom of a hydroxyl group and the nearest atom on the Al(111) surface, as illustrated in Figure 9. These bonds have lengths of 2.195 Å for maltose and 2.107 Å for β-lactose. While these distances slightly exceed the sum of the covalent radii of oxygen and aluminum ( $r_{O}^{c o v}$ + $r_{A l}^{c o v}$ = 0.60 + 1.25 = 1.85 Å),⁵² they remain significantly shorter than the van der Waals contact threshold ( $r_{O}^{v a n}$ + $r_{A l}^{v a n}$ = 1.51 + 2.17 = 3.68 Å),⁵⁸ indicating a considerable interaction with the surface—albeit less pronounced than that of sucrose.

It is worth highlighting that a comparable interaction pattern is observed for the disaccharides sucrose and β-lactose (excluding maltose), where the strong affinity for the Al(111) surface is attributed not only to the formation of O–Al bonds but also to the favorable orientation of hydrogen atoms from the second ring toward the surface, with distances of 2.246 Å and 2.340 Å, respectively, as shown by the dashed red lines in Figure 9. Additional support for this interaction comes from the charge density maps in Figure 10, which reveal regions of charge accumulation (in red) between the bottommost hydrogen atoms of the second ring and the Al(111) surface, even in the absence of direct covalent bonding.

Figure 10.

Side and top views of the charge density difference (CDD) plots for the equilibrium adsorption geometries on the Al(111) surface.

This synergistic interaction mechanism provides a compelling explanation for the high adsorption energies calculated for sucrose (–46.197 kcal/mol) and β-lactose (–44.561 kcal/mol). The robustness of the adsorption arises from a combination of factors: the presence of O–Al bonds and the spatial proximity of hydrogen atoms to the surface, highlighting a dual contribution of covalent and non-covalent forces that reinforce the overall stability of the adsorption process.

On the other hand, the adsorption results illustrated in Figure 9, demonstrate that the monosaccharide inhibitors, Glucose and Fructose (in their open-chain forms), interact with the Al(111) surface by forming O–Al bonds through the oxygen atom of the carbonyl group.

The bond lengths, measured at 1.948 Å and 1.987 Å, are indicative of chemical bonds, even though they slightly exceed the sum of the covalent radii of oxygen and aluminum ( $r_{O}^{c o v}$ + $r_{A l}^{c o v}$ = 0.60 + 1.25 = 1.85 Å),⁵⁷ and significantly shorter than the van der Waals sum ( $r_{O}^{v a n}$ + $r_{A l}^{v a n}$ = 1.51 + 2.17 = 3.68 Å).⁵⁸ This interaction is further corroborated by charge density difference (CDD) analysis, which reveals significant redistribution of electronic density around the Al–O bond, confirming the chemical nature of the adsorption process.

The three cyclic monosaccharides, D-glucose, D-β-fructofuranose, and D-galactose, can adsorb onto the Al(111) surface without forming covalent bonds, as illustrated in Figure 9. The observed distances between the adsorbed molecules and the surface range from 2.530 to 2.828 Å. These contact distances are significantly shorter than the sum of the van der Waals radii ( $r_{O}^{v a n}$ + $r_{A l}^{v a n}$ = 1.51 + 2.17 = 3.68 Å),⁵⁸ suggesting that the adsorption occurs through physisorption rather than chemisorption. This mechanism underpins their role in the corrosion inhibition process, highlighting non-covalent interactions as the dominant driving force.This result is further supported by CDD analysis, which does not reveal substantial density redistribution between these inhibitors and the Al(111) surface. Charge density difference (CDD) analysis provides a detailed visualization of electronic redistribution during interactions, where regions of electron accumulation (depicted in red) and electron depletion (depicted in blue) are identified, serving as indicators of bond formation.^59,60 However, the analysis does indicate localized charge redistribution, with notable regions of red charge accumulation observed at specific sites on the Al(111) surface. This suggests the presence of weak interactions and highlights the role of surface characteristics in influencing the adsorption behavior.

The observed adsorption behavior indicates strong interactions between the selected inhibitors and the Al(111) surface, as demonstrated by the reduced adsorption bond distances (Figure 9) and the significant charge density redistribution shown by the CDD analysis (Figure 10). The disaccharide-derived inhibitors (sucrose, maltose, and β-lactose) display distinctly different behavior compared to other monosaccharide analogues, in both cyclic and open-chain forms. This distinction cannot be attributed solely to molecular size, but is primarily related to the specific spatial distribution and orientation of the hydroxyl groups, which substantially enhance the adhesion of these inhibitors to the aluminum surface.

Conclusion

This work provides a molecular-level understanding of how saccharide-based compounds interact with aluminum surfaces, with direct relevance to their use as green corrosion inhibitors. By combining density functional theory calculations with adsorption modeling on the Al(111) surface, the study clarifies the relationship between molecular structure, adsorption mechanism, and inhibition potential. These insights are essential for translating computational predictions into rational experimental design and for guiding the selection or synthesis of effective, environmentally friendly corrosion inhibitors.

The main conclusions of this study are as follows:

Molecular DFT calculations reveal that the oxygen atoms of hydroxyl groups in all eight studied saccharide inhibitors serve as highly reactive centers, identifying them as the most nucleophilic sites.

The adsorption study indicates that only the monosaccharides glucose (OC) and fructose (OC), along with the disaccharides sucrose, maltose, and β-lactose, adsorb onto the Al(111) surface through the formation of coordinate covalent O-Al bonds between the oxygen atom of the inhibitor and the nearest aluminum atom, suggesting chemisorption as the primary adsorption mechanism.

The findings show that the monosaccharide inhibitors glucose and fructose (in their open-chain forms) interact with the Al(111) surface by forming O–Al bonds through the oxygen atom of the carbonyl group.

The cyclic monosaccharides D-glucose, D-β-fructofuranose, and D-galactose adsorb onto the Al(111) surface without forming covalent bonds, indicating that physisorption, rather than chemisorption, is the dominant mechanism.

It is important to further examine the synergistic interactions between different saccharide molecules to better understand their cooperative adsorption on the Al(111) surface.

Footnotes

ORCID iDs

Ali Bensaddek

Adel Bouhdjer

Authors contributions

A.B., administration of projects, composing, reviewing, and editing, overseeing, and validating; M.D., writing original draft,administration of projects, composing, reviewing, and editing, overseeing, and validating; H.A., administration of projects, reviewing, and editing, overseeing, and validating; S.B.B., investigation and ORCA software; A.B., investigation; D.S., investigation, O.B., revision.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

No datasets were generated or analysed during the current study.

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