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Article

Investigation on the Interfacial Behavior of Thiols on Silver Surface by DFT Study and MD Simulation

School of Chemical Engineering, Ocean and Life Sciences, Dalian University of Technology, Panjin 124221, China
*
Author to whom correspondence should be addressed.
Coatings 2025, 15(10), 1134; https://doi.org/10.3390/coatings15101134
Submission received: 12 August 2025 / Revised: 24 August 2025 / Accepted: 2 September 2025 / Published: 1 October 2025
(This article belongs to the Section Corrosion, Wear and Erosion)

Abstract

The adsorption of organic substances on the surface of silver is a crucial method for the anti-tarnish treatment of silver, and thiol organic substances have a significant protective effect on silver. Through quantum chemical calculations and molecular dynamics simulations, the adsorption performance of thiol compounds on silver surfaces was investigated as the research object. Thiol compounds are classified into five categories, including short-chain saturated fat thiols and long-chain saturated fat thiols, and their adsorption properties are compared. After screening, thiol compounds with better adsorption performance on the surface of Ag were obtained. Long-chain saturated aliphatic thiols have the best protective effect for silver anti-tarnish treatment, followed by aromatic thiols, while short-chain saturated aliphatic thiols give the worst effect.

1. Introduction

In recent years, silver nanoparticles, as important research objects, have been widely applied in fields such as heat conduction, electrical conduction, and catalysis [1,2,3,4]. However, silver is prone to corrosion in the air, especially in the presence of sulfides such as hydrogen sulfide (H2S) and carbonyl sulfide (OCS) [5,6]. The sulfation of silver is accompanied by the formation of Ag2S, also known as tarnishing [7,8,9]. Problems such as reduced thermal and electrical conductivity caused by sulfidation have limited the various applications of silver. Accordingly, the anti-corrosion and anti-tarnish research of Ag-based material has been highly valued [10].
To get rid of the influence of this problem, scientists have come up with the idea of protecting silver through physical barriers to separate it from corrosive substances, such as organic polymer films, self-assembling films, precious metal films, etc. [11,12,13,14,15]. However, various types of films have obvious drawbacks: the cost of metal coatings is high, they are prone to galvanic corrosion and affect conductivity; inorganic coatings are brittle and prone to cracking, and have poor protective stability.
Over years of research, people have turned their attention to the adsorption of organic substances on the surface of silver. Some studies have shown that thiol compounds have a protective effect on silver. Mercaptans have significant advantages in preventing silver corrosion [16,17]. They can not only quickly form a dense and stable chemical adsorption film on the silver surface, but also effectively isolate corrosive media such as sulfides and oxygen [18]. Moreover, the film layer is thin and has little impact on the conductivity and appearance of silver, making it suitable for various scenarios such as electronic components and jewelry [19]. Since thiol compounds have an unpleasant odor in the air, when applied to jewelry, they can be dissolved at lower concentrations in other organic compounds (such as n-hexane or ethanol) for coating. At the same time, it has good weather resistance and a long-lasting protective effect.
In the past, when studying the corrosion resistance of Ag, methods such as infrared spectroscopy, electrochemical impedance spectroscopy (EIS), and Tafel curve analysis were commonly used [20,21,22]. Infrared spectroscopy can qualitatively analyze the chemical structure of corrosion products on the surface of silver by detecting characteristic absorption peaks generated by molecular vibrational energy level transitions, thereby inferring the type and path of corrosion reactions [23,24,25]. EIS is an electrochemical method that analyzes the dynamic behaviors of the interface during corrosion, such as charge transfer, diffusion, and film formation, by applying a small alternating signal and measuring the impedance response of the silver electrode at different frequencies [26,27,28]. Tafel curves directly calculate the corrosion rate by measuring the corrosion current density of the silver electrode at different potentials [29,30,31]. Combining these three methods in experiments enables a comprehensive evaluation of the corrosion resistance of silver. However, these methods are characterized by excessive workload and low efficiency. Quantum chemistry, based on the Schrödinger equation, can directly reveal the atomic-level sites where corrosion occurs through calculations. Moreover, when predicting surface anti-corrosion mechanisms, it can pre-screen efficient surface modification strategies without the need for a large number of experimental trials and errors. It can obtain the energy of the highest occupied molecular orbitals and the lowest unoccupied molecular orbitals, thereby researching the interaction mechanisms of molecules on the Ag surface [32,33,34,35,36,37,38,39,40,41]. Molecular dynamics (MD) simulation, by solving Newton’s equations of motion, models the movement trajectories of many atoms and molecules over time and space. This approach can reproduce the dynamic processes of silver in corrosive environments, making it a strong complement to theoretical calculations and experiments. Its innovation lies in overcoming the limitations of “static observation” found in the traditional method [42,43,44,45,46,47,48,49]. These two methods have gradually become efficient approaches for studying chemical reactions at the molecular level in recent decades. Silver is a precious metal. When coating the surface of silver, there are problems such as reagent waste and a large amount of work. We can screen out organic substances with good adsorption through quantum chemical calculations and molecular dynamics simulations, and then verify them through experiments to reduce workload and improve efficiency [50,51,52].
In this work, the adsorption performance between thiol compounds and the Ag surface was taken as the research subject. Thiol compounds were classified into short-chain saturated aliphatic thiols, long-chain saturated aliphatic thiols, aromatic thiols, binary thiols, and unsaturated aliphatic thiols for the comparison of adsorption performance. Firstly, the adsorption behavior of thiol compounds on the silver surface is estimated based on the orbital and electronic information obtained from quantum chemical calculations. Then, the adsorption mechanism is studied through molecular dynamics simulation, thereby screening out thiol compounds with better adsorption performance with the Ag surface.

2. Details of the Theoretical Calculation

In this study, quantum chemical calculations of thiol compounds were conducted based on density functional theory (DFT). Through the Dmol3 module in Materials Studio, with the maximum number of iterations set to 1000, the orbital and electronic properties of thiol compounds were investigated using the DFT method of generalized gradient approximation (GGA), and the exchange correlation functional was the Lee-Yang-Parr (BLYP) functional [53,54,55,56,57,58,59]. Firstly, perform geometric optimization on the molecule using Dmol3. Select ‘use symmetry’, ‘core treatment’ as ‘all electron’, ‘key point set’ as 1 × 1 × 1, the dispersion correction method as ‘DFT-D’, the basis set as ‘DND’, and the basis files as ‘3.5’. Secondly, the energy of the optimized molecules is calculated. By selecting orbitals in properties, the energy values of the highest occupied molecular orbital(HOMO) and lowest unoccupied molecular orbital(LUMO) can be obtained. In the analysis of Dmol3, the distribution of HOMO and LUMO orbitals of the molecule can be displayed.
Charge density difference is a key analytical tool used to describe the changes in the electronic distribution of a system [60,61]. It visually reflects the laws of electron transfer, aggregation, or consumption in processes such as chemical reactions, doping, adsorption, and interface formation by comparing the differences in charge density between two related systems. We selected one molecule with excellent performance from each group of thiols to obtain the electron transfer between the molecule and silver.
MD simulation can obtain the interfacial interaction and the adsorption energy of thiol compounds. First, use silver as the base and cut it in a (1 1 1) plane pattern. Then, use it to build a supercell, whose dimensions are as follows: a = 20.23 Å, b = 20.23 Å, and c = 9.44 Å. Using the build layer tool, combine the box containing thiol molecules with the Ag substrate and add a vacuum layer with a height of 15 Å between them to simulate the adsorption between the two in the gas phase. In the calculation of forcite, the force field used for dynamic calculation is the COMPASS III (Condensed-Phase Optimized Molecular potential for Atomistic Simulation Studies). Using the NVT ensemble at 298 K (room temperature), the total simulation time is 500 ps, and the time step is 1 fs. The adsorption energies ( E a d s o r p t i o n ) of thiol compounds on the Ag surface were calculated by the following Equation (1):
E a d s o r p t i o n =   E t o t a l     E m o l e c u l e     E s u r f a c e

3. Results and Discussion

3.1. Short-Chain Saturated Aliphatic Thiols

Four short-chain saturated aliphatic mercaptans were selected as the research objects, namely methanethiol, ethanethiol, propanethiol, and cyclohexanethiol. The optimized structures of the investigated thiols with atom label symbols are shown in Figure 1.
Based on DFT of quantum chemical calculations, the orbital and electronic properties of the selected thiols were studied after geometric optimization. The energy and distribution of the highest occupied molecular orbital (HOMO), the lowest unoccupied molecular orbital (LUMO), and the energy gap ( E =   E L U M O     E H O M O ) of four molecules are illustrated in Table S1 (Supplementary Materials) and Figure 2, Figure 3 and Figure 4.
In Figure 2 and Figure 3, the distribution of the HOMO and LUMO of the four molecules can be seen. In the figure, yellow represents the positive phase of the orbital wave function, and blue represents the negative phase. During orbital interaction, the overlap of regions with the same phase leads to the formation of bonding orbitals, while the overlap of regions with opposite phases results in the formation of antibonding orbitals. The degree of phase matching between the HOMO and LUMO affects the possibility of electron transfer between molecules. In Figure 4, the energy and energy gap of HOMO and LUMO can be observed. The size of the E reflects the strength of a molecule’s adsorption capacity. The smaller the E , the stronger the molecule’s adsorption capacity. Therefore, it can be observed that the four short-chain saturated aliphatic thiol molecules exhibit comparable adsorption capabilities, all of which are relatively low.
Detailed numerical data are compiled in Table S1.
MD simulation can effectively characterize the physical adsorption mechanism of thiols on the Ag (1 1 1) surface under equilibrium conditions. Since the protection of silver is generally carried out in the air, all MD simulations in this paper are conducted in the gas phase. Therefore, the variation in the deviations of temperature and energy are larger than those in the liquid phase. As shown in Figure S1, although the fluctuation range of the studied system is relatively large, it can be stabilized within a reasonable range. The structural comparison before and after adsorption in Figure 5 can prove that thiols can spontaneously adsorb on the silver surface. Through calculation, E t o t a l , E m o l e c u l e , and E s u r f a c e were obtained, and then the E a d s o r p t i o n was obtained as shown in Table 1. It can be observed from Table 1 that the E a d s o r p t i o n of the four thiols are all negative, indicating that the adsorption process is thermodynamically spontaneous. A comparative analysis reveals that cyclohexanethiol exhibits the highest absolute E a d s o r p t i o n (−179.813 kJ/mol), suggesting a stronger adsorption capacity compared to the other compounds. The essence of E a d s o r p t i o n is the interaction between molecules and metals, while E is merely a characteristic of the molecules themselves. Therefore, when evaluating the adsorption performance of molecules, the weight of E a d s o r p t i o n is even more significant. As illustrated in Figure S6, among the short-chain saturated aliphatic thiols studied, the adsorption performance ranking is as follows: cyclohexanethiol > propanethiol > methanethiol > ethanethiol. However, the adsorption performance of short-chain saturated aliphatic mercaptans is generally low.

3.2. Long-Chain Saturated Aliphatic Thiols

For long-chain saturated aliphatic mercaptans, we have selected the following four mercaptans: 1-dodecanethiol, 1-tetradecanethiol, 1-hexadecanethiol and 1-octadecanethiol. Their optimized structure is shown in Figure 6.
After the quantum chemical calculation of DFT, the energy, distribution, and E of the HOMO and LUMO orbitals of four long-chain saturated aliphatic thiol molecules were obtained. Among them, Table S2 details the orbital energy data of four molecules, Figure 7 and Figure 8 show the distribution of HOMO and LUMO orbitals of the four molecules, yellow and blue represent the positive and negative phase orbital wave functions, respectively, which are related to the electron transfer of molecules. Figure 9 makes a more intuitive comparison of the strength of adsorption capacity among the four molecules. As can be observed, the E values of the four molecules are quite close, and all exhibit favorable adsorption performance.
The equilibrium of temperature and energy of long-chain saturated aliphatic thiols is shown in Figure S2. The structure in Figure 10 indicates that thiols can adsorb spontaneously on the silver surface. The detailed data are shown in Table 2. It reveals the spontaneous adsorption of four molecules; moreover, their adsorption energies are lower compared to short-chain saturated aliphatic thiols, suggesting stronger adsorption capacity. Figure S7 indicates that the adsorption capacities of the four molecules derived from both quantum chemical calculations and MD simulations are comparable; it can be known by ranking them that 1-dodecanethiol > 1-octadecanethiol > 1-hexadecanethiol > 1-tetradecanethiol. Furthermore, due to the relatively low values of E and E a d s o r p t i o n , all four molecules in this group exhibit extremely strong adsorption capacity, which also reflects the mutual validation between DFT and MD calculations.

3.3. Aromatic Thiols

For aromatic thiols benzenethiol, 2-methylthiophenol, 4-methylthiophenol, and phenylmethanethiol, we conducted the following analysis on their optimized structures, as shown in Figure 11.
Figure 12 and Figure 13 show the distribution of HOMO and LUMO orbitals of aromatic thiols. Table S3 contains the energy and E of the HOMO and LUMO orbitals of the molecules. Figure 14 provides a more intuitive comparison of the strength of adsorption capacity among the four molecules.
Figure S3 shows the equilibrium of aromatic thiols in MD simulation. As can be seen from Figure 15, thiols are adsorbed on the surface of silver metal after 500 ps. Table 3 presents detailed data on the E a d s o r p t i o n of the four molecules. The adsorption performance ranking of aromatic thiols is as follows: 4-methylthiophenol > 2-methylthiophenol > phenylmethanethiol > benzenethiol.
Based on the comprehensive quantum chemical calculation and MD simulation, it can be seen from Figure S8 that the adsorption performance of phenylmethanethiol is the most favorable.

3.4. Binary Thiols

Binary thiol can participate in cross-linking, catalysis, or be used as ligands through thiol reactions. In this study, we selected four binary thiols, namely 1,1-propanedithiol, ethanedithiol, 1,4-butanedithiol, and 2,3-butanedithiol, as the research objects, and their optimized structures are shown in Figure 16.
Through the quantum chemical calculation of DFT, we obtained the energy, distribution and E of the HOMO and LUMO orbitals of four molecules. Table S4 details the orbital energy data of four molecules. Figure 17 and Figure 18 show the distribution of HOMO and LUMO orbitals of the four molecules. Among them, Figure 19 makes a clearer comparison of the strength of adsorption capacity among the four molecules.
Figure S4 shows the equilibrium of binary thiols in MD simulation. It can be seen from Figure 20 that thiols adsorbed on the surface of silver metal before and after the simulation. Table 4 presents detailed data on the adsorption energies of the four molecules. Combined with Figure S9, the adsorption performance ranking of thiols in this group can be obtained: 1,4-butanedithiol > 2,3-butanedithiol > 1,1-propanedithiol > ethanedithiol.

3.5. Unsaturated Aliphatic Thiols

In unsaturated aliphatic thiols, we studied four thiol compounds, namely 3-methyl-2-buten-1-thiol, 2-propene-1-thiol, 2-butene-1-thiol, and thiogeraniol. Figure 21 shows the optimized structures of these thiols.
Figure 22 and Figure 23 show the distribution of HOMO and LUMO orbitals of the unsaturated aliphatic thiols. Table S5 records the energies and E of the HOMO and LUMO orbitals of four molecules, and Figure 24 describes the E of the molecule.
Figure S5 shows the equilibrium of unsaturated aliphatic thiols in MD simulation. As can be seen from Figure 25, thiol molecules have a certain adsorption tendency with the silver surface during the MD simulation process. Table 5 presents detailed data on the adsorption energies of four molecules. Combined with Figure S10, the adsorption performance ranking of thiols in this group can be obtained: thiogeraniol > 3-methyl-2-buten-1-thiol > 2-butene-1-thiol > 2-propene-1-thiol.

3.6. Charge Density Difference

In this section, one molecule with excellent performance was selected from the five types of thiols for differential charge density treatment, namely cyclohexanethiol, 1-dodecanethiol, phenylmethanethiol, 1,1-propanedithiol, and 2-butene-1-thiol. The obtained results are shown in Figure 26. The analysis of differential charge density falls within the scope of quantum chemistry. In principle, the molecule with the lowest E among various thiols should be selected for analysis. However, the molecular E of long-chain saturated aliphatic thiols differs minimally, essentially being at the same level. Therefore, for the convenience of observation, we chose 1-dodecanethiol, the smallest in molecular structure, for the operation.
The charge density difference is represented by a blue-white-red legend, where red represents the maximum charge density and blue represents the minimum charge density [61]. Due to the higher electronegativity of S compared to Ag, electrons are biased toward S during the adsorption and bonding process, resulting in an increased negative charge density on S. After adsorption, the thiol molecule as a whole carries a negative charge, while the internal C-C bonds carry a positive charge, and the charge density on the Ag surface decreases. This is consistent with the results in Figure 26 where the red area around the molecule is darker, the internal area appears blue, and the red area around Ag is lighter. Therefore, performing charge density difference calculations on representative thiol molecules can verify their adsorption behavior and reveal the adsorption mechanism, The detailed data are shown in Table S6.

4. Conclusions

In this study, the adsorption properties of five types of thiol compounds (short-chain saturated aliphatic thiols, long-chain saturated aliphatic thiols, aromatic thiols, binary thiols, and unsaturated aliphatic thiols) on the surface of silver were systematically investigated through DFT and MD simulations. The results show that there are significant differences in the adsorption capacity of different types of thiols. The long-chain saturated aliphatic thiols (such as dodecanethiol, octadecanethiol, etc.) show the best protective effect, their E is smaller and the absolute value of E a d s o r p t i o n is the largest, and they have a tendency for monomolecular adsorption on the surface of silver. Aromatic thiols followed, among which 4-methylthiophenol had the most outstanding adsorption performance. Short-chain saturated aliphatic thiols have the poorest adsorption capacity, and only cyclohexanethiol performs relatively well in this category. The results of quantum chemical calculations and molecular dynamics simulations corroborate each other, confirming the strong adsorption characteristics of long-chain saturated aliphatic thiols on the surface of silver. This provides a theoretical basis for the anti-corrosion protection of silver-based materials and also offers a reliable computational method reference for screening efficient thiol protective agents.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/coatings15101134/s1, Figure S1: The equilibrium of temperature (a) and energy (b) of methanethiol; Figure S2: The equilibrium of temperature (a) and energy (b) of dodecylthiol; Figure S3: The equilibrium of temperature (a) and energy (b) of benzenethiol; Figure S4: The equilibrium of temperature (a) and energy (b) of propanedithiol; Figure S5: The equilibrium of temperature (a) and energy (b) of 3-methyl-2-buten-1-thiol; Figure S6: Comparison diagram of ΔE and adsorption energy of short-chain saturated aliphatic thiols; Figure S7: Comparison diagram of ΔE and adsorption energy of long-chain saturated aliphatic thiols; Figure S8: Comparison diagram of ΔE and adsorption energy of aromatic thiols; Figure S9: Comparison diagram of ΔE and adsorption energy of binary thiols; Figure S10: Comparison diagram of ΔE and adsorption energy of unsaturated aliphatic thiols; Table S1: HOMO and LUMO data of four short-chain saturated aliphatic thiol molecules; Table S2: HOMO and LUMO data of four long-chain saturated aliphatic thiol molecules; Table S3: HOMO and LUMO data of four aromatic thiol molecules; Table S4: HOMO and LUMO data of four binary thiol molecules; Table S5: HOMO and LUMO data of four unsaturated aliphatic thiol molecules; Table S6: Adsorption energy data of thiol molecules on a metal monolayer Ag (1 1 1).

Author Contributions

Conceptualization: W.G.; investigation: Y.A.; writing—original draft: A.L.; writing—review and editing, H.Z. and B.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article and Supplementary Information.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Optimized structure of investigated inhibitors with atom label symbols: (a) methanethiol, (b) ethanethiol, (c) propanethiol, and (d) cyclohexanethiol.
Figure 1. Optimized structure of investigated inhibitors with atom label symbols: (a) methanethiol, (b) ethanethiol, (c) propanethiol, and (d) cyclohexanethiol.
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Figure 2. The HOMO energy density distribution of four kinds of thiol molecules: (a) methanethiol, (b) ethanethiol, (c) propanethiol, and (d) cyclohexanethiol.
Figure 2. The HOMO energy density distribution of four kinds of thiol molecules: (a) methanethiol, (b) ethanethiol, (c) propanethiol, and (d) cyclohexanethiol.
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Figure 3. The LUMO energy density distribution of four kinds of thiol molecules: (a) methanethiol, (b) ethanethiol, (c) propanethiol, and (d) cyclohexanethiol.
Figure 3. The LUMO energy density distribution of four kinds of thiol molecules: (a) methanethiol, (b) ethanethiol, (c) propanethiol, and (d) cyclohexanethiol.
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Figure 4. The diagram E of thiol molecules: (a) methanethiol, (b) ethanethiol, (c) propanethiol, and (d) cyclohexanethiol (The red lines represent the energy of the LUMO, and the green lines represent the energy of the HOMO).
Figure 4. The diagram E of thiol molecules: (a) methanethiol, (b) ethanethiol, (c) propanethiol, and (d) cyclohexanethiol (The red lines represent the energy of the LUMO, and the green lines represent the energy of the HOMO).
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Figure 5. Configuration diagrams of thiols before and after MD simulation; (ad) refer to methanethiol, ethanethiol, propanethiol, and cyclohexanethiol before the simulation and (a′d′) refer to methanethiol, ethanethiol, propanethiol, and cyclohexanethiol after the simulation.
Figure 5. Configuration diagrams of thiols before and after MD simulation; (ad) refer to methanethiol, ethanethiol, propanethiol, and cyclohexanethiol before the simulation and (a′d′) refer to methanethiol, ethanethiol, propanethiol, and cyclohexanethiol after the simulation.
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Figure 6. Optimized structure of investigated inhibitors with atom label symbols: (a) 1-dodecanethiol, (b) 1-tetradecanethiol, (c) 1-hexadecanethiol, and (d) 1-octadecanethiol.
Figure 6. Optimized structure of investigated inhibitors with atom label symbols: (a) 1-dodecanethiol, (b) 1-tetradecanethiol, (c) 1-hexadecanethiol, and (d) 1-octadecanethiol.
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Figure 7. The HOMO energy density distribution of four kinds of thiol molecules: (a) 1-dodecanethiol, (b) 1-tetradecanethiol, (c) 1-hexadecanethiol, and (d) 1-octadecanethiol.
Figure 7. The HOMO energy density distribution of four kinds of thiol molecules: (a) 1-dodecanethiol, (b) 1-tetradecanethiol, (c) 1-hexadecanethiol, and (d) 1-octadecanethiol.
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Figure 8. The LUMO energy density distribution of four kinds of thiol molecules, (a) 1-dodecanethiol, (b) 1-tetradecanethiol, (c) 1-hexadecanethiol, and (d) 1-octadecanethiol.
Figure 8. The LUMO energy density distribution of four kinds of thiol molecules, (a) 1-dodecanethiol, (b) 1-tetradecanethiol, (c) 1-hexadecanethiol, and (d) 1-octadecanethiol.
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Figure 9. The diagram E of thiol molecules: (a) 1-dodecanethiol, (b) 1-tetradecanethiol, (c) 1-hexadecanethiol, and (d) 1-octadecanethiol (The red lines represent the energy of the LUMO, and the green lines represent the energy of the HOMO).
Figure 9. The diagram E of thiol molecules: (a) 1-dodecanethiol, (b) 1-tetradecanethiol, (c) 1-hexadecanethiol, and (d) 1-octadecanethiol (The red lines represent the energy of the LUMO, and the green lines represent the energy of the HOMO).
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Figure 10. Configuration diagrams of thiols before and after MD simulation; (ad) refer to 1-dodecanethiol, 1-tetradecanethiol, 1-hexadecanethiol, and 1-octadecanethiol before the simulation, and (a′d′) refer to 1-dodecanethiol, 1-tetradecanethiol, 1-hexadecanethiol, and 1-octadecanethiol after the simulation.
Figure 10. Configuration diagrams of thiols before and after MD simulation; (ad) refer to 1-dodecanethiol, 1-tetradecanethiol, 1-hexadecanethiol, and 1-octadecanethiol before the simulation, and (a′d′) refer to 1-dodecanethiol, 1-tetradecanethiol, 1-hexadecanethiol, and 1-octadecanethiol after the simulation.
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Figure 11. Optimized structure of investigated inhibitors with atom label symbols: (a) benzenethiol, (b) 2-methylthiophenol, (c) 4-methylthiophenol, and (d) phenylmethanethiol.
Figure 11. Optimized structure of investigated inhibitors with atom label symbols: (a) benzenethiol, (b) 2-methylthiophenol, (c) 4-methylthiophenol, and (d) phenylmethanethiol.
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Figure 12. The HOMO energy density distribution of four kinds of thiol molecules: (a) benzenethiol, (b) 2-methylthiophenol, (c) 4-methylthiophenol, and (d) phenylmethanethiol.
Figure 12. The HOMO energy density distribution of four kinds of thiol molecules: (a) benzenethiol, (b) 2-methylthiophenol, (c) 4-methylthiophenol, and (d) phenylmethanethiol.
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Figure 13. The LUMO energy density distribution of four kinds of thiol molecules: (a) benzenethiol, (b) 2-methylthiophenol, (c) 4-methylthiophenol, and (d) phenylmethanethiol.
Figure 13. The LUMO energy density distribution of four kinds of thiol molecules: (a) benzenethiol, (b) 2-methylthiophenol, (c) 4-methylthiophenol, and (d) phenylmethanethiol.
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Figure 14. The diagram E of thiol molecules (a) benzenethiol, (b) 2-methylthiophenol, (c) 4-methylthiophenol, and (d) phenylmethanethiol (The red lines represent the energy of the LUMO, and the green lines represent the energy of the HOMO).
Figure 14. The diagram E of thiol molecules (a) benzenethiol, (b) 2-methylthiophenol, (c) 4-methylthiophenol, and (d) phenylmethanethiol (The red lines represent the energy of the LUMO, and the green lines represent the energy of the HOMO).
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Figure 15. Configuration diagrams of thiols before and after MD simulation; (ad) refer to benzenethiol, 2-methylthiophenol, 4-methylthiophenol, and phenylmethanethiol before the simulation, (a′d′) refer to benzenethiol, 2-methylthiophenol, 4-methylthiophenol, and phenylmethanethiol after the simulation.
Figure 15. Configuration diagrams of thiols before and after MD simulation; (ad) refer to benzenethiol, 2-methylthiophenol, 4-methylthiophenol, and phenylmethanethiol before the simulation, (a′d′) refer to benzenethiol, 2-methylthiophenol, 4-methylthiophenol, and phenylmethanethiol after the simulation.
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Figure 16. Optimized structure of investigated inhibitors with atom label symbols: (a) 1,1-propanedithiol, (b) ethanedithiol, (c) 1,4-butanedithiol, and (d) 2,3-butanedithiol.
Figure 16. Optimized structure of investigated inhibitors with atom label symbols: (a) 1,1-propanedithiol, (b) ethanedithiol, (c) 1,4-butanedithiol, and (d) 2,3-butanedithiol.
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Figure 17. The HOMO energy density distribution of four kinds of thiol molecules: (a) 1,1-propanedithiol, (b) ethanedithiol, (c) 1,4-butanedithiol, and (d) 2,3-butanedithiol.
Figure 17. The HOMO energy density distribution of four kinds of thiol molecules: (a) 1,1-propanedithiol, (b) ethanedithiol, (c) 1,4-butanedithiol, and (d) 2,3-butanedithiol.
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Figure 18. The LUMO energy density distribution of four kinds of thiol molecules: (a) 1,1-propanedithiol, (b) ethanedithiol, (c) 1,4-butanedithiol, and (d) 2,3-butanedithiol.
Figure 18. The LUMO energy density distribution of four kinds of thiol molecules: (a) 1,1-propanedithiol, (b) ethanedithiol, (c) 1,4-butanedithiol, and (d) 2,3-butanedithiol.
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Figure 19. The diagram E of thiol molecules: (a) 1,1-propanedithiol, (b) ethanedithiol, (c) 1,4-butanedithiol, and (d) 2,3-butanedithiol (The red lines represent the energy of the LUMO, and the green lines represent the energy of the HOMO).
Figure 19. The diagram E of thiol molecules: (a) 1,1-propanedithiol, (b) ethanedithiol, (c) 1,4-butanedithiol, and (d) 2,3-butanedithiol (The red lines represent the energy of the LUMO, and the green lines represent the energy of the HOMO).
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Figure 20. Configuration diagrams of thiols before and after MD simulation; (ad) refer to 1,1-propanedithiol, ethanedithiol, 1,4-butanedithiol, and 2,3-butanedithiol before the simulation, (a′d′) refer to 1,1-propanedithiol, ethanedithiol, 1,4-butanedithiol, and 2,3-butanedithiol after the simulation.
Figure 20. Configuration diagrams of thiols before and after MD simulation; (ad) refer to 1,1-propanedithiol, ethanedithiol, 1,4-butanedithiol, and 2,3-butanedithiol before the simulation, (a′d′) refer to 1,1-propanedithiol, ethanedithiol, 1,4-butanedithiol, and 2,3-butanedithiol after the simulation.
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Figure 21. Optimized structure of investigated inhibitors with atom label symbols: (a) 3-methyl-2-buten-1-thiol, (b) 2-propene-1-thiol, (c) 2-butene-1-thiol, and (d) thiogeraniol.
Figure 21. Optimized structure of investigated inhibitors with atom label symbols: (a) 3-methyl-2-buten-1-thiol, (b) 2-propene-1-thiol, (c) 2-butene-1-thiol, and (d) thiogeraniol.
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Figure 22. The HOMO energy density distribution of four kinds of thiol molecules: (a) 3-methyl-2-buten-1-thiol, (b) 2-propene-1-thiol, (c) 2-butene-1-thiol, and (d) thiogeraniol.
Figure 22. The HOMO energy density distribution of four kinds of thiol molecules: (a) 3-methyl-2-buten-1-thiol, (b) 2-propene-1-thiol, (c) 2-butene-1-thiol, and (d) thiogeraniol.
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Figure 23. The LUMO energy density distribution of four kinds of thiol molecules: (a) 3-methyl-2-buten-1-thiol, (b) 2-propene-1-thiol, (c) 2-butene-1-thiol, and (d) thiogeraniol.
Figure 23. The LUMO energy density distribution of four kinds of thiol molecules: (a) 3-methyl-2-buten-1-thiol, (b) 2-propene-1-thiol, (c) 2-butene-1-thiol, and (d) thiogeraniol.
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Figure 24. The diagram E of thiol molecules (a) 3-methyl-2-buten-1-thiol, (b) 2-propene-1-thiol, (c) 2-butene-1-thiol, and (d) thiogeraniol (The red lines represent the energy of the LUMO, and the green lines represent the energy of the HOMO).
Figure 24. The diagram E of thiol molecules (a) 3-methyl-2-buten-1-thiol, (b) 2-propene-1-thiol, (c) 2-butene-1-thiol, and (d) thiogeraniol (The red lines represent the energy of the LUMO, and the green lines represent the energy of the HOMO).
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Figure 25. Configuration diagrams of thiols before and after MD simulation; (ad) refer to 3-methyl-2-buten-1-thiol, 2-propene-1-thiol, 2-butene-1-thiol, and thiogeraniol before the simulation, (a′d′) refer to 3-methyl-2-buten-1-thiol, 2-propene-1-thiol, 2-butene-1-thiol, and thiogeraniol after the simulation.
Figure 25. Configuration diagrams of thiols before and after MD simulation; (ad) refer to 3-methyl-2-buten-1-thiol, 2-propene-1-thiol, 2-butene-1-thiol, and thiogeraniol before the simulation, (a′d′) refer to 3-methyl-2-buten-1-thiol, 2-propene-1-thiol, 2-butene-1-thiol, and thiogeraniol after the simulation.
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Figure 26. Charge density difference of thiol molecules adsorbed on a Ag surface: (a) cyclohexanethiol, (b) 1-dodecanethiol, (c) phenylmethanethiol, (d) 1,1-propanedithiol, and (e) 2-butene-1-thiol.
Figure 26. Charge density difference of thiol molecules adsorbed on a Ag surface: (a) cyclohexanethiol, (b) 1-dodecanethiol, (c) phenylmethanethiol, (d) 1,1-propanedithiol, and (e) 2-butene-1-thiol.
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Table 1. The adsorption energy data of the four short-chain saturated aliphatic thiol molecules.
Table 1. The adsorption energy data of the four short-chain saturated aliphatic thiol molecules.
Thiol E t o t a l
(kJ/mol)
E s u r f a c e
(kJ/mol)
E m o l e c u l e
(kJ/mol)
E a d s o r p t i o n
(kJ/mol)
Methanethiol1092.0591202.212−3.916−106.236
Ethanethiol2064.1272164.6564.608−105.138
Propanethiol1082.4341196.98120.959−135.506
Cyclohexanethiol976.3031199.927−43.810−179.813
Table 2. The adsorption energy data of the four long-chain saturated aliphatic thiol molecules.
Table 2. The adsorption energy data of the four long-chain saturated aliphatic thiol molecules.
Thiol E t o t a l
(kJ/mol)
E s u r f a c e
(kJ/mol)
E m o l e c u l e
(kJ/mol)
E a d s o r p t i o n
(kJ/mol)
1-dodecanethiol1525.8751865.7242.601−342.450
1-tetradecanethiol3275.3093628.980−17.562−336.109
1-hexadecanethiol823.0261206.617−46.832−336.759
1-octadecanethiol824.2031205.771−44.534−337.035
Table 3. The adsorption energy data of the four aromatic thiol molecules.
Table 3. The adsorption energy data of the four aromatic thiol molecules.
Thiol E t o t a l
(kJ/mol)
E s u r f a c e
(kJ/mol)
E m o l e c u l e
(kJ/mol)
E a d s o r p t i o n
(kJ/mol)
Benzenethiol1581.7951712.71352.569−183.488
2-methylthiophenol2025.6252158.36577.864−210.603
4-methylthiophenol1968.0592160.37419.712−212.027
Phenylmethanethiol2057.9432158.380102.544−202.982
Table 4. The adsorption energy data of the four binary thiol molecules.
Table 4. The adsorption energy data of the four binary thiol molecules.
Thiol E t o t a l
(kJ/mol)
E s u r f a c e
(kJ/mol)
E m o l e c u l e
(kJ/mol)
E a d s o r p t i o n
(kJ/mol)
1,1-propanedithiol1294.4101482.010−21.534−166.065
Ethanedithiol2207.4312318.61432.025−143.208
1,4-butanedithiol1733.3931943.528−10.408−199.727
2,3-butanedithiol1777.0181947.29613.088−183.366
Table 5. The adsorption energy data of the four unsaturated aliphatic thiol molecules.
Table 5. The adsorption energy data of the four unsaturated aliphatic thiol molecules.
Thiol E t o t a l
(kJ/mol)
E s u r f a c e
(kJ/mol)
E m o l e c u l e
(kJ/mol)
E a d s o r p t i o n
(kJ/mol)
3-methyl-2-buten-1-thiol1818.8921997.1822.392−180.682
2-propene-1-thiol2407.4432484.68742.869−120.113
2-butene-1-thiol2789.6942870.31667.257−147.880
Thiogeraniol2285.6262552.26914.764−281.407
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Gao, W.; An, Y.; Zhai, H.; Gao, B.; Liu, A. Investigation on the Interfacial Behavior of Thiols on Silver Surface by DFT Study and MD Simulation. Coatings 2025, 15, 1134. https://doi.org/10.3390/coatings15101134

AMA Style

Gao W, An Y, Zhai H, Gao B, Liu A. Investigation on the Interfacial Behavior of Thiols on Silver Surface by DFT Study and MD Simulation. Coatings. 2025; 15(10):1134. https://doi.org/10.3390/coatings15101134

Chicago/Turabian Style

Gao, Wenjing, Yukun An, Hongjia Zhai, Boyu Gao, and Anmin Liu. 2025. "Investigation on the Interfacial Behavior of Thiols on Silver Surface by DFT Study and MD Simulation" Coatings 15, no. 10: 1134. https://doi.org/10.3390/coatings15101134

APA Style

Gao, W., An, Y., Zhai, H., Gao, B., & Liu, A. (2025). Investigation on the Interfacial Behavior of Thiols on Silver Surface by DFT Study and MD Simulation. Coatings, 15(10), 1134. https://doi.org/10.3390/coatings15101134

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