Molecular Simulation Study on the Adsorption Mechanisms of Microbial Components and Metabolic Products on Activated Carbon in HVAC Systems

Abstract

Activated carbon is widely known for its porous structure and diverse surface functional groups, making it an effective adsorbent for removing various organic and inorganic pollutants from air and water. However, as a filtration material in air conditioning systems, activated carbon can also provide favorable conditions for microbial growth, potentially leading to the proliferation of microorganisms on its surface. These microorganisms, along with their metabolic products, can be released into indoor environments, posing potential health risks. This study employs molecular simulation to investigate the adsorption and release mechanisms of microorganisms and their volatile organic compound (VOC) metabolic products on activated carbon. Peptidoglycan (PDG) (as a representative bacterial cell wall component) and p-xylene (as a representative microbial metabolic product) were used as model compounds. The adsorption behavior of these compounds was simulated on activated carbon under different environmental conditions, including varying temperatures. The study found that activated carbon has a higher affinity for peptidoglycan than for p-xylene; at 303.15 K, the diffusion coefficients of peptidoglycan and p-xylene in activated carbon are 0.842 × 10⁻⁹ m²/s and 0.587 × 10⁻⁸ m²/s, respectively. Temperature plays an important role in affecting adsorption capacity; when the temperature rises by 10 K, the diffusion coefficients of peptidoglycan and p-xylene in activated carbon increase by 32.8% and 34.3%, respectively. These insights contribute to the development of efficient and health-conscious air purification materials, offering theoretical and practical guidance for optimizing the use of activated carbon in HVAC systems.

1. Introduction

Activated carbon is renowned for its developed porous structure and extensive surface functional groups, which form the foundation of its efficacy as an adsorbent, capable of removing a wide range of organic and inorganic pollutants from aqueous solutions or air streams [1,2,3]. However, when utilized as a filter medium in air conditioning systems, activated carbon can also become a breeding ground for microbial growth, providing the necessary temperature, humidity, and nutrients, leading to the proliferation of microbes on its surface [4]. During this process, microbial metabolites may enter indoor environments through the air conditioning system, increasing the presence of biofilm components and microbial metabolites indoors, thereby posing potential health risks to inhabitants [5,6].

Despite extensive research into the adsorptive capabilities of activated carbon, studies on its adsorption processes and mechanisms concerning microbes and their metabolites are relatively scarce. Existing research has primarily focused on the experimental level, examining the adsorption effects of activated carbon on specific biofilms and microbial metabolites, and their influencing factors, such as temperature, relative humidity, dust accumulation, and air velocity [7,8,9] However, these studies have often not delved into the molecular principles underlying the adsorption mechanisms of activated carbon. In addition, microorganisms and their metabolites are usually a variety of compounds; common fungi in HVAC systems are penicillium, Aspergillus, cladosporium, and common bacteria are coccus and Bacillus [10,11,12]. Microbial metabolites are more complex, including chlorinated hydrocarbons, amines, terpenes, alcohol, aldehydes, ketones, sulfuric compounds, aromatic compounds, etc. [13,14,15]. The complexity of microorganisms and their metabolites can make it difficult to accurately measure their adsorption and diffusion behavior.

This study uses peptidoglycan (PDG) as a substitute for bacterial biofilm. The cell wall components are important criteria for bacterial taxonomy, and peptidoglycan is an essential and specific component in the cell walls of almost all bacteria [16,17]. In Gram-positive bacteria, the peptidoglycan layer constitutes over 90% of the cell wall structure, while in Gram-negative bacteria, the peptidoglycan layer accounts for 10% to 20% of the cell wall. The specific anionic functional groups present on their peptidoglycan are key components that enable the bacterial cell wall to exhibit anionic properties and binding functions [18,19,20,21].

In the current cross-disciplinary research of air conditioning system engineering and microbiology, the study of microbial metabolites, volatile organic compounds (VOCs), is increasingly receiving attention. Among them, xylene, as a typical aromatic hydrocarbon VOC, is widely present in microbial metabolic processes and has a stable molecular structure, making it a representative metabolite selected for molecular simulation studies [22,23,24].

Molecular simulation, including techniques such as molecular dynamics and quantum chemistry, is increasingly being applied in the study of adsorbent materials. In comparison to experimental research, it can also investigate the micro-mechanisms and properties between adsorbents and adsorbates [25,26,27,28]. Veclani and Melchior [29] used molecular dynamics to study the adsorption of neutral and zwitterionic forms of ciprofloxacin (CFX) on single-walled carbon nanotubes (SWCNT) in gas and water phases. Niu et al. [30] employed molecular dynamics to investigate the microscopic mechanism of dodecyl sugar wetting coal dust, thereby selecting surfactants with better dust suppression effects. Wang and Guo [31] summarized adsorption kinetic models, such as the empirical kinetic models PFO, PSO, MO, Elovich model, differential kinetic model, phenomenological intra/external model, and active site adsorption model. Sangsuradet and Worathanakul [32] used grand canonical Monte Carlo simulation to study CO₂ adsorption by Group 1A cations, finding Li+ to have the highest attraction to CO₂. Kyriakopoulos et al. [33] reviewed studies on the adsorption behavior of carbonaceous materials, where molecular simulation techniques are often used to calculate structural characteristics and gas adsorption properties, as well as to calculate adsorption isotherms and diffusion coefficients. Nazarizadeh et al. [34] investigated Rhodamine B and Gemifloxacin adsorption from wastewater, demonstrating the effectiveness of synthesized nanocomposites. Liu et al. [35] reviewed molecular simulation’s role in gas membrane separation processes, while Nwobodo et al. [36] used quantum mechanical simulations to evaluate Ga₁₂As₁₂ nanostructures as diclofenac adsorbent/sensors. Wang et al. [37] utilized grand canonical Monte Carlo and molecular dynamics methods to simulate the adsorption of toluene on nanoporous carbon, revealing the mass transfer mechanism of gas–solid coupling in porous materials [38]. These studies illustrate the diverse applications of molecular simulation in adsorbent research, from environmental remediation to gas separation and sensor development, offering valuable insights for designing advanced materials.

Compared to previous literature on molecular simulation of activated carbon, this article focuses on the bacterial contamination problem faced by HVAC systems and delves into the less-studied issues of adsorption and release of microorganisms and their metabolic substances on activated carbon. By constructing idealized molecular models, with peptidoglycan and p-xylene as representatives, we simulate the main components of bacterial cell membranes and typical microbial metabolic substances, respectively, to analyze their adsorption behavior on the surface of activated carbon [18,38]. Furthermore, this study will also investigate the impact of different environmental conditions (such as temperature) on the adsorption efficiency of activated carbon, in order to provide theoretical foundations and practical guidance for the development of efficient and healthy air purification materials.

Through this approach, this study is expected to unveil the fundamental principles of activated carbon’s adsorption of microbial components and metabolites, thereby providing a scientific basis for improving and optimizing the application of activated carbon in air conditioning systems.

2. Materials and Methods

2.1. Activated Carbon Model

This study refers to the method of Sheng et al. [39] to construct an activated carbon model using the “Build” module in Material Studio (Version 2020). This software, manufactured by BIOVIA in San Diego, CA, USA, provides advanced molecular modeling and simulation tools that facilitated the detailed analysis and visualization of the materials’ properties and interactions.

Common functional groups that affect the adsorption effect of activated carbon include oxygen-containing and nitrogen-containing functional groups [40,41]. Meanwhile, studies by Morris et al. [42] and Huang et al. [43] have shown that the addition of five-membered and seven-membered rings is beneficial to ensure the porosity defects of the carbon structure. Pyridine is chemically connected to a nitrogen atom, and the nitrogen atom has lone pair electrons, which makes pyridine exhibit properties similar to those of nitrogen-containing functional groups. To make the activated carbon model more reasonable, the six-membered ring is used as the basic unit of the carbon structure, and based on the non-six-membered ring and element ratio measured in the actual activated carbon structure [44], 15% of five-membered and seven-membered rings are introduced into the basic unit, as well as corresponding proportions of hydroxyl, carboxyl, and carbonyl groups to represent oxygen-containing functional groups on activated carbon, and pyridine is added to represent nitrogen-containing functional groups. The constructed basic unit of activated carbon is shown in Figure 1.

After establishing the basic unit structure, a 50 × 50 × 50 Å cubic empty crystal cell was created using the “Build-Crystals” module of the MS software. Then, using the “Amorphous Cell” module, the basic units were packed into the empty crystal cell, achieving a uniform distribution of basic units within the empty cell, resulting in a three-dimensional structural model with the characteristics of activated carbon. Geometry optimization of the activated carbon model was performed using the “Forcite” module in MS to minimize the local energy. Considering that the air temperature range in the HVAC system is generally 293 K to 303 K, the molecular dynamics (MD) method is used to simulate the model at 293 K temperature for 25 rounds of annealing kinetics to minimize the total energy and obtain the final activated carbon model. The obtained model had a porosity of 65% and an apparent density of 1.02 g/cm³.

2.2. Peptidoglycan and p-Xylene Models

To comprehensively investigate the adsorption behavior of active carbon towards diverse microbial pollutants, this study selected two representative compounds: peptidoglycan and p-xylene. Peptidoglycan was chosen to represent complex organic molecules containing nitrogen and sulfur, such as those found in bacterial cell walls, due to its structural complexity and relevance in microbiological contexts. On the other hand, p-xylene was selected as a model for aromatic and hydrophobic organic compounds, which are common among microbial metabolic products and environmental VOCs. The contrasting chemical and physical properties of these two models allow for a broad analysis of the adsorption mechanisms and interactions that may occur within the porous structure of activated carbon, providing insights into its efficacy across a spectrum of microbial contaminants.

The structural complexity of the peptidoglycan layer in bacterial cell walls stems from the intricate construction of its repeating units, which consist of disaccharides, tetrapeptide tails, and pentapeptide bridges. The disaccharide components, which are highly conserved across all true bacteria, are composed of N-acetylglucosamine (NAG) and N-acetylmuramic acid (NAM), linked by β-1,4-glycosidic bonds [45]. The tetrapeptide tails, with an amino acid sequence of L-alanine, D-glutamic acid, L-lysine, and D-alanine, are found in both Gram-positive and Gram-negative bacteria [46]. Notably, the pentapeptide bridge structure is primarily found in the peptidoglycan layer of Gram-positive bacteria, connecting adjacent tetrapeptide tails to form a robust network structure [21,47]. In this study, molecular modeling was performed for the disaccharide and tetrapeptide tail components of the peptidoglycan repeating unit. The molecular formula of the constructed peptidoglycan unit is C35H59O19N7, and its precise molecular structure is shown in Figure 2a.

p-Xylene, a major component of microbial metabolic product VOCs, has the molecular formula C8H10. The p-xylene molecular model was directly imported from the MS software database, as shown in Figure 2b.

2.3. Molecular Simulation Process

In this study, the Adsorption Locator module was used to introduce peptidoglycan and p-xylene molecular models into the simulation box to determine the interaction sites and adsorption strengths between activated carbon and these molecules. Before conducting the molecular simulations, charge calculations and force field settings were applied to the constructed models of activated carbon, peptidoglycan, and p-xylene using the COMPASS II force field with automatic calculations for charges and force field parameters. Electrostatic interactions were modeled using the Ewald and Group method, and van der Waals forces were calculated based on atomic interactions. The adsorption models underwent initial geometry optimization using the same method. Through annealing dynamics simulations, the global minimum of the potential energy surface for the activated carbon adsorption structure was identified. Annealing simulations were performed using the Forcite module, with an initial temperature set to 300 K and a mid-cycle temperature of 600 K. Each cycle’s heating ramp was set to 5, with a dynamic step size of 10,000 per ramp. Temperature control was managed using the Nose algorithm, with the number of cycles set to 10. The same method was used to obtain adsorption models at temperatures of 293.15 K, 298.15 K, and 303.15 K (in Kelvin as per the software settings). These models were then used to analyze adsorption heat and adsorption sites, providing adsorption configuration diagrams for subsequent molecular dynamics simulations.

Molecular dynamics simulations were also carried out using the Forcite module, with force field and charge settings consistent with those used in the Adsorption Locator module. The simulations began with an NPT ensemble to relax the system under constant pressure and temperature conditions, followed by further simulations using an NVT ensemble to stabilize the system under constant volume and temperature conditions. These molecular dynamics simulations were conducted at three different temperature conditions, and the resulting configuration diagrams were used as the basis for analyzing the adsorption behavior of peptidoglycan and p-xylene molecules on activated carbon, including the distribution characteristics of adsorbates and their diffusion within the activated carbon structure.

3. Results

3.1. Adsorption Sites and Radial Distribution Function (RDF)

Due to the limitations of traditional testing methods and instruments, the adsorption sites of gas molecules in the micropores of adsorbents are usually not directly visualized. However, molecular simulation technology allows for direct observation of adsorption sites in a simulated environment. The adsorption process of peptidoglycan molecules and p-xylene molecules on activated carbon was simulated at three temperatures: (a) 293.15 K, (b) 298.15 K, and (c) 303.15 K. The adsorption configuration diagrams are shown in Figure 3, where the blue part represents the activated carbon structure, the green part represents peptidoglycan molecules, and the red part represents p-xylene molecules.

The RDF quantifies the probability density of the distance between atoms in the molecular model, expressed as the ratio of local density to average density. It reveals the spatial distribution characteristics of peptidoglycan or p-xylene molecules on activated carbon. The expression is as follows:

$$g\left(r\right)={\displaystyle \frac{n}{4\pi r^2\rho dr}}$$

(1)

• where g(r) represents the probability density of molecules at a distance r from the carbon atoms on activated carbon;
• n is the number of molecules in the range of distance r to r + dr;
• ρ is the density of the molecules.

The RDF curves of the distance between the PDG molecules and the carbon atom centroids on activated carbon at different temperatures are shown in Figure 4a. The RDF curves exhibit minimal variation across different temperatures, indicating that temperature changes have a relatively small impact on RDF, suggesting that the adsorption process of peptidoglycan molecules on activated carbon has good thermal stability. A further analysis of the RDF curve reveals that the peak position indicates the distribution of distances between the PDG molecules and the carbon atom centroids on activated carbon. The distances are primarily concentrated within the range of 1–3Å, with the highest peak appearing at 1.125Å. This indicates that in activated carbon, PDG molecules have the most adsorption sites at a distance of 1.125Å, which may be due to the interaction between the specific pore structure of activated carbon and the PDG molecules. When the distance is less than 1Å, the RDF value is zero, indicating that within 1Å of the basic unit of activated carbon, PDG molecules are almost absent, possibly because the interaction between PDG molecules and activated carbon is insufficient to overcome their repulsive force. When the distance is greater than 3Å, the RDF value approaches 0.7, indicating that the local density is close to the average density, and at distances greater than 3Å, the interaction between the PDG molecules and the carbon atom centroids of activated carbon weakens, resulting in a relatively free distribution of PDG molecules in the activated carbon.

The RDF curves showing the distance between p-xylene molecules and the carbon atom centroids on activated carbon at different temperatures are illustrated in Figure 4b. The minimal changes in the RDF curves across different temperatures indicate that temperature has a relatively small impact on the RDF, implying that the adsorption process of p-xylene molecules on activated carbon exhibits good thermal stability. Further analysis of the RDF curves reveals two higher peaks, which is consistent with the results of the study by Li et al.’s on the adsorption of benzene molecules by activated carbon. The two peaks of the radial distribution function for activated carbon adsorbing benzene molecules are located at about 1.7Å and 2.5Å [48]. In this study, the two peaks of activated carbon adsorbing para-xylene molecules are located at 1.125Å and 1.375Å, with the peak at 1.125Å being particularly prominent, indicating that this distance is the optimal adsorption site. The sub-peak at 1.375Å reflects the double-layer adsorption characteristics of activated carbon for para-xylene molecules. In addition, there are two smaller peaks, after which the peak values gradually decay to 1, indicating that the distance between p-xylene molecules and the carbon atom centroids on activated carbon mainly falls within the range of 1–2.4Å. When the distance between p-xylene molecules and the carbon atoms on activated carbon is less than 1Å, the RDF value is zero, indicating that there are no p-xylene molecules within 1Å of the basic unit of activated carbon. This may be due to the fact that the interaction between p-xylene molecules and activated carbon is insufficient to overcome their repulsive force. When the distance exceeds 4Å, the RDF curve gradually flattens out and approaches 1, indicating that the local density approaches the average density, and there is no significant adsorption layer beyond 4Å.

According to the RDF curves, the distance between PDG molecules and the center of carbon atoms in activated carbon has a highest peak at 1.125Å, and the optimal adsorption sites for p-xylene are 1.125Å and 1.375Å. Based on this, the thickness of the activated carbon adsorption bed and the size of the activated carbon particles can be optimized to ensure effective capture of PDG molecules and p-xylene molecules during the adsorption process. Moreover, considering the double-layer adsorption characteristics of p-xylene molecules, a multi-layer activated carbon bed layer can be designed in the HVAC system to improve adsorption efficiency and capacity. At the same time, since the adsorption layers of activated carbon for both PDG molecules and p-xylene molecules are mainly concentrated within the range of 1–2.4Å, and the optimal adsorption distance is relatively short, the airflow speed should be appropriately reduced to avoid the situation where PDG molecules and p-xylene molecules are not fully adsorbed and are discharged from the system.

3.2. Average Adsorption Heat and Energy Distribution

This study compares the average adsorption heat of peptidoglycan (PDG) molecules and p-xylene molecules on activated carbon at 293.15 K, 298.15 K, and 303.15 K. As shown in Figure 5, the average adsorption heat of PDG molecules is significantly higher than that of p-xylene molecules at all temperatures, indicating that activated carbon has a stronger adsorption tendency toward PDG molecules. The adsorption heat of activated carbon for p-xylene is about 13 kcal/mol, which is close to the adsorption heat of activated carbon for benzene in the study by Li et al. [48], and is far below the threshold of 42 kcal/mol for chemical adsorption heat, indicating that the process is mainly physical adsorption, caused by the van der Waals forces between p-xylene molecules and the surface of activated carbon. As the temperature increases, the average adsorption heat for both PDG and p-xylene decreases, consistent with the sensitivity of exothermic adsorption processes to temperature. Overall, the adsorption heat for the representative biofilm molecule PDG is greater than that for the metabolic product p-xylene, suggesting that biofilm components are more strongly adsorbed by activated carbon than microbial metabolic products. Higher temperatures reduce the adsorption capacity of activated carbon, potentially leading to the desorption of metabolic products, which could then be introduced into the indoor environment, posing potential risks.

Figure 6 illustrates the relationship between van der Waals energy and adsorption probability for PDG and p-xylene on activated carbon, where peak values represent the optimal adsorption energy, with negative values indicating the spontaneity of adsorption. The larger the absolute value of adsorption energy, the stronger the adsorption. At different temperatures, PDG exhibits the highest energy density in the −60 to −65 kcal/mol range, while p-xylene shows peaks in the −10 to −18 kcal/mol range. The results demonstrate that the adsorption energy of PDG is significantly higher than that of p-xylene, indicating that activated carbon has a more pronounced adsorption effect on PDG.

3.3. Diffusion Coefficient

When considering the application of activated carbon as a filter material in air conditioning units, the diffusion behavior of microorganisms and their metabolic products in activated carbon is a critical factor. An increase in temperature may enhance the desorption risk of these two types of molecules, potentially allowing them to diffuse into the indoor environment. This poses a threat to the health of indoor occupants, potentially causing Legionnaires’ disease, fungal pneumonia, and viral respiratory infections, and exacerbating indoor air pollution, which can trigger or worsen conditions such as asthma [49,50,51]. By analyzing the mean square displacement (MSD) curves and applying the following formula (Equation (2)), the diffusion coefficients of peptidoglycan and p-xylene at different temperatures were calculated. Using the least squares method to fit the MSD curves, the mean square displacement of PDG molecules and p-xylene molecules during the dynamic simulation process are shown in Figure 7 and Figure 8.

$$D_{\alpha }={\displaystyle \frac{1}{6N_{\alpha }}}{\displaystyle \sum }_{t\to \infty }{\displaystyle \frac{d}{dt}}{{\displaystyle \sum }}_{t=1}^{N_{\alpha }}\left\{{\left[r_1\left(t\right)-r_0\left(t\right)\right]}^2\right\}$$

(2)

• where D_α is the diffusion coefficient;
• [$r_1\left(t\right)-r_0\left(t\right)$]² is the mean square displacement of the atoms in the structure.

Figure 7. Mean square displacement of PDG molecules in the activated carbon model.

Figure 7. Mean square displacement of PDG molecules in the activated carbon model.

Figure 8. Mean square displacement of p-xylene molecules in the activated carbon model.

Figure 8. Mean square displacement of p-xylene molecules in the activated carbon model.

An increase in temperature will lead to an increase in the diffusion coefficient. Therefore, in actual air conditioning systems, it is preferable to operate within a lower temperature range. When the operating temperature range is higher, it is necessary to consider increasing the amount of activated carbon filter material or reducing the filter replacement cycle. The diffusion coefficient of p-xylene is one order of magnitude greater than that of peptidoglycan molecules. Therefore, for activated carbon filter materials, more emphasis should be placed on enhancing the adsorption effect for p-xylene, that is, the design and consideration should be targeted at microbial metabolites.

4. Discussion

Due to experimental limitations, direct data on the diffusion coefficients of PDG and p-xylene in activated carbon are not currently available. Consequently, this study relies on indirect experimental data for diffusion coefficients of other compounds with similar properties as a basis for validation. Although these compounds differ in type, they share similarities with the model compounds in terms of molecular structure, size, and hydrophilicity. While these data may not be perfectly aligned, they provide preliminary validation of the simulation results, offering insights into their reliability and trends and establishing a foundation for further experimental research.

Under low concentration conditions, the diffusion coefficient D of gases in the air is approximately inversely proportional to the square root of the molecular weight M, as shown by the equation [52]:

$$D\propto {\displaystyle \frac{1}{\sqrt{M}}}$$

(3)

Wang et al. demonstrated that the diffusion coefficient of benzene derivatives in activated carbon at 303.15 K is approximately 0.28 × 10⁻⁸ m²/s. Based on the above equation, the theoretical diffusion coefficients for PDG and p-xylene at the same temperature should be 0.083 × 10⁻⁸ m²/s and 0.240 × 10⁻⁸ m²/s, respectively. According to the simulation results, at 303.15 K, the diffusion coefficient of PDG increases to 0.0842 × 10⁻⁸ m²/s, while the diffusion coefficient of p-xylene reaches 0.587 × 10⁻⁸ m²/s.

The validation results indicate that the simulated diffusion coefficient for PDG closely matches the theoretical estimate, demonstrating that the simulation method performs well for complex organic molecules. This agreement underscores the reliability of the model in predicting diffusion coefficients for larger molecules. However, the simulated diffusion coefficient for p-xylene shows a significant deviation from the theoretical value, with the simulated value being considerably higher. This discrepancy may stem from several factors, including simplified assumptions regarding intermolecular interactions, relative differences in molecular size, and inherent limitations of the diffusion model when applied to small hydrophobic molecules such as p-xylene.

5. Conclusions

This study utilized molecular simulations to investigate the adsorption behavior of activated carbon toward bacterial cell wall components, specifically peptidoglycan (PDG), and the metabolic product p-xylene. The results indicate that activated carbon exhibits a higher adsorption heat for peptidoglycan molecules, demonstrating a stronger adsorption affinity. In contrast, the adsorption of p-xylene is primarily characterized by physical adsorption, with lower adsorption heat. While the adsorption of both peptidoglycan and p-xylene on activated carbon showed thermal stability, an increase in temperature significantly reduced the adsorption heat, thereby weakening the adsorption efficiency.

Radial distribution function (RDF) analysis revealed that the adsorption distances for peptidoglycan and p-xylene molecules on activated carbon are mainly concentrated within the range of 1 to 3Å, with peptidoglycan molecules exhibiting the most dense adsorption sites at 1.125Å. In comparison, p-xylene molecules displayed bilayer adsorption characteristics, with primary adsorption sites located at 1.125Å and 1.375Å on the activated carbon surface.

In the analysis of diffusion coefficients, temperature increases significantly enhanced the diffusion capacity of both peptidoglycan and p-xylene molecules, with p-xylene molecules generally showing diffusion coefficients an order of magnitude higher than those of peptidoglycan. This suggests that the interaction energy between peptidoglycan molecules and activated carbon is stronger, making peptidoglycan molecules less likely to desorb from adsorption sites, whereas p-xylene molecules are more easily desorbed into the gas phase.

Overall, activated carbon holds potential advantages in air purification, particularly in the adsorption of microbial biofilm components. However, attention should be given to the impact of temperature changes on adsorption performance. Future research should focus on optimizing the structure and surface chemistry of activated carbon to enhance its adsorption performance under varying environmental conditions.