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Quantum Mechanical Studies And Monte Carlo Simulations On The Corrosion Inhibitive Potentials Of Some Imidazole Derivatives

This study utilizes Density Functional Theory (DFT) and Monte Carlo simulations to demonstrate that imidazole derivative C exhibits the highest corrosion inhibition potential among three tested compounds due to its narrowest energy gap and strongest covalent adsorption on iron surfaces.

Original authors: T.O Esan, K. E Ajibulu, O.L Adebayo, Ilesanmi Osasona, A.D Olanipekun

Published 2026-07-06

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CC BY 4.0

Original authors: T.O Esan, K. E Ajibulu, O.L Adebayo, Ilesanmi Osasona, A.D Olanipekun

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine your car's engine or a bridge's steel beams are like a house made of Lego bricks. Over time, rain and air (specifically acidic environments) act like tiny, invisible vandals that start pulling those bricks apart. This process is called corrosion (or rusting). It costs billions of dollars to fix and can be dangerous.

To stop this, scientists usually try to coat the metal with a protective "shield" made of special chemicals called inhibitors. Traditionally, finding the best shield involves mixing chemicals in a lab, waiting to see if they work, and repeating the process. This is slow, expensive, and messy.

This paper is about using super-fast computer simulations to predict which chemical shields will work best before anyone ever mixes a single drop of liquid in a lab.

Here is how the researchers did it, explained simply:

1. The "Digital Lab" (Quantum Mechanics)

Instead of a physical lab, the researchers used a digital one powered by Density Functional Theory (DFT). Think of this as a high-tech video game engine that simulates how atoms behave.

They looked at three specific chemical shapes (let's call them Molecule A, B, and C). These are all variations of a family called "imidazole derivatives." You can imagine them as three slightly different keys, and the metal surface is a lock. The goal is to find which key fits the lock best to stop the vandals.

The computer calculated:

The Energy Gap: Imagine the molecule has a "battery" (electrons). The "gap" is how hard it is to move those electrons. A smaller gap means the molecule is more "willing" to share its electrons with the metal.
- Result: Molecule C had the smallest gap (4.23 eV), followed by B, then A. This suggested C would be the most active.
The "Stickiness" (Hardness/Softness): In this world, "soft" molecules are like Velcro—they are flexible and stick easily. "Hard" molecules are like rocks—they are rigid.
- Result: Molecule C was the "softest," meaning it was the most flexible and likely to hug the metal surface tightly.
The "Fingerprints" (Fukui Indices): The computer looked at specific spots on the molecules (like Nitrogen and Sulfur atoms) to see where they were most likely to grab onto the metal. It found that the "heteroatoms" (the special atoms with extra electrons) were the main places where the molecules would latch on.

2. The "Virtual Dance Floor" (Monte Carlo Simulations)

Once they knew the molecules' properties, they ran a Monte Carlo simulation. Imagine a crowded dance floor where the metal surface is the floor and the inhibitor molecules are dancers.

The computer simulated 200,000 "steps" (movements) to see how the molecules would naturally arrange themselves on the metal.
They wanted to see: Do the molecules stand up straight? Do they lie flat? Do they clump together?
The Result: The molecules didn't just stand there; they lay flat against the metal surface, like a blanket covering a bed. This "blanket" blocks the corrosive vandals from touching the metal.

3. The Final Score: Who Won?

The researchers measured the Adsorption Energy. Think of this as a "hug score." The more negative the number, the tighter the hug.

Molecule A: Hug score of -13,032 (A decent hug).
Molecule B: Hug score of -13,039 (A slightly tighter hug).
Molecule C: Hug score of -13,719 (The strongest, tightest hug).

The Conclusion:
According to the computer, Molecule C is the champion. It has the right shape, the right electron energy, and it sticks to the metal surface the hardest. The study suggests that Molecule C forms a very strong, protective layer (a "chemical blanket") that stops rust from forming.

In a Nutshell

The researchers used a computer to play "what-if" games with three different chemical shapes. They found that Molecule C is the best at hugging the metal surface tightly, creating a shield that would theoretically stop rust better than the other two. This saves time and money by telling scientists exactly which chemical to test in the real world first.

Technical Summary: Quantum Mechanical Studies and Monte Carlo Simulations on the Corrosion Inhibitive Potentials of Some Imidazole Derivatives

Problem Statement
Corrosion represents a significant economic and safety challenge globally, causing infrastructure failure and substantial financial loss through the degradation of metals, particularly in industrial, marine, and atmospheric environments. While traditional mitigation strategies exist, the search for effective, sustainable corrosion inhibitors remains critical. Experimental determination of inhibition mechanisms is often expensive and time-consuming. Consequently, there is a need for efficient theoretical modeling to correlate molecular structures with inhibitory efficacy, specifically for heterocyclic compounds like imidazole derivatives which possess electron-donating heteroatoms (N, S, O) suitable for adsorption on metal surfaces.

Methodology
This study employed a dual computational approach to investigate the corrosion inhibition potentials of three imidazole derivatives (designated A, B, and C) on an iron (Fe) surface:

Density Functional Theory (DFT): Calculations were performed using the B3LYP functional with the 6-31G(d) basis set in the Spartan 10 software package. The workflow included geometry definition, conformational searches to identify global minimum energy structures, and geometric optimization. Key quantum chemical descriptors were calculated, including frontier molecular orbital energies ( $E_{HOMO}$ , $E_{LUMO}$ ), energy gaps ( $E_g$ ), ionization potential, electron affinity, global hardness, softness, electronegativity, electrophilicity, nucleophilicity, and the fraction of electron transfer ( $\Delta N$ ). Fukui indices and Mulliken charge distributions were also analyzed to identify active adsorption sites.
Monte Carlo (MC) Simulations: Adsorption behavior was simulated using the Material Studio 8.0 package with the COMPASS force field. Simulations were conducted on an Fe(110) surface using an NVT ensemble at 298 K for 200,000 cycles (100,000 equilibration and 100,000 production steps). Adsorption energies ( $E_{ads}$ ) were calculated to determine the stability of the inhibitor-metal interaction.

Key Results

Electronic Properties and Reactivity:
- Energy Gaps: The calculated energy gaps ( $E_g$ ) were 4.50 eV (A), 4.28 eV (B), and 4.23 eV (C). The lower gap in C and B suggests higher reactivity and better inhibition potential compared to A.
- Donor/Acceptor Capabilities: Molecule C exhibited the highest $E_{HOMO}$ (-5.45 eV) and the lowest ionization potential (5.45 eV), indicating it is the strongest electron donor. Conversely, Molecules A and B showed higher electron affinity values (1.72 eV and 1.73 eV, respectively) compared to C (1.22 eV), suggesting A and B have a stronger capacity to accept electrons from the metal surface.
- Global Descriptors: Molecule C displayed the highest nucleophilicity (0.32) and the lowest global hardness (2.11 eV), implying a "softer" character favorable for adsorption. Molecule B exhibited the highest global electrophilicity (3.61 eV).
- Fukui Indices: Analysis identified heteroatoms, specifically Nitrogen and Sulfur, as the primary active sites for adsorption. The Fukui function values indicated specific sites for nucleophilic and electrophilic attacks, confirming the role of these heteroatoms in the inhibition mechanism.
Adsorption and Monte Carlo Simulations:
- Adsorption Energies: The MC simulations revealed strong, negative adsorption energies for all compounds, indicating spontaneous and stable adsorption. The values followed the order: C (-13719.09 kcal/mol) > B (-13039.52 kcal/mol) > A (-13032.45 kcal/mol).
- Mechanism: The highly negative adsorption energies suggest a chemisorption mechanism involving covalent bonding between the inhibitor molecules and the Fe(110) surface.
- Configuration: The simulations showed that the molecules adopt a parallel orientation on the Fe(110) surface, maximizing surface coverage. This arrangement supports the DFT findings of back-donation, where electrons from the filled d-orbitals of iron transfer to the empty orbitals (LUMO) of the inhibitors.

Significance and Claims
The paper claims that theoretical modeling provides a viable, cost-effective alternative to experimental methods for screening corrosion inhibitors. The study concludes that among the three derivatives investigated, Molecule C possesses the most favorable characteristics for corrosion inhibition. This conclusion is based on its lower energy gap, higher nucleophilicity, and the most negative adsorption energy, which collectively suggest superior adsorption strength and surface coverage on mild steel.

The authors assert that the inhibition mechanism involves a dual process: the donation of electrons from the inhibitor's HOMO to the vacant d-orbitals of the iron, and the back-donation of electrons from the iron's d-orbitals to the inhibitor's LUMO. The study highlights that the presence of heteroatoms (N, S) and the specific electronic distribution within the imidazole derivatives are critical factors in their ability to form protective films against corrosion. The results confirm that these imidazole derivatives act as effective chemical adsorbents, with Molecule C demonstrating the highest potential for preventing rusting on metal surfaces.

1. The "Digital Lab" (Quantum Mechanics)

2. The "Virtual Dance Floor" (Monte Carlo Simulations)

3. The Final Score: Who Won?

In a Nutshell

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