Simulation Calculation Research Articles

Prediction method for re-damage behavior of the repaired CFRP bolted joint

Composite materials are widely used in various aircraft due to their high specific strength, stiffness, corrosion resistance, and robust design flexibility. However, when subjected to complex loading conditions, composite structures are susceptible to damage, necessitating prompt repair upon aircraft return. Analyzing the re-damage process of repaired structures is crucial for assessing aircraft structural reliability, lifespan, and determining whether a repeat flight is warranted. In this study, a prediction method was proposed for re-damage behavior through meso-modeling and energy analysis of the repaired composite bolted joint. First, this article established a meso-mechanical model for composite laminates, analyzed force transfer characteristics at the fiber − matrix interface, and derived equations for stress field. Additionally, a strain energy distribution model was developed for composite bolted repaired joint near fibers and repaired area, proposing a damage prediction method based on the strain energy criterion. This method could anticipate the location, type, sequence, and magnitude of damage. Finally, simulation calculations yielded mechanical characteristics of the repaired area under typical load conditions, while loading tests verified the feasibility of the prediction method. This study offered an effective means of predicting performance degradation in composite structures and provided a vital direction for optimal spacecraft structure repairing methods and parameters.

Evaluation of different computational methods for numerical simulation of aerosol distribution in the operating room

In traditional operating rooms, controlling the concentration of aerosol particles has been necessary to ensure surgical safety. The COVID-19 pandemic has further emphasized the need for protecting medical staff in operating rooms, thereby increasing the focus on aerosol concentrations. Accurate simulation calculations of aerosol concentration and distribution play a crucial role in evaluating these concentrations and the associated risk of exposure. This study aims to assess the distribution of aerosols within an operating room by employing four different calculation methods and comparing them with experimental data. These methods included two turbulence models - Reynolds Averaged Navier Stokes (RANS) and Large Eddy Simulation (LES)-combined with two different aerosol transmission calculation models -Lagrangian and Eulerian. The findings indicate that the LES model yields a more accurate representation of the flow field, whereas no significant differences were observed among the four methods when it came to calculating aerosol concentrations. However, Eulerian-based methods exhibited superior continuity in the results. The errors of the four methods were greater than 50 % at Class II sampling locations and less than 50 % at Class III sampling locations. Consequently, this study serves as a scientific reference for selecting appropriate numerical simulation methods to predict aerosol concentration and distribution in operating rooms.

Deciphering Mutational Impacts on c-Src-HK2 Interaction in Colorectal Cancer Progression, and Identification of Potential Phytocompounds Inhibitors: A Molecular Simulation and Free Energy Calculation Approach.

Colorectal cancer (CRC) stands as the third most widespread cancer worldwide in both men and women, witnessing a concerning rise, especially in younger demographics. Abnormal activation of the Non-Receptor Tyrosine Kinase c-Src has been linked to the advancement of several human cancers, including colorectal, breast, lung, and pancreatic ones. The interaction between c-Src and Hexokinase 2 (HK2) triggers enzyme phosphorylation, significantly boosting glycolysis, and ultimately contributing to the development of CRC. The objectives of this study are to examine the influence of newly identified mutations on the interaction between c-Src and the HK2 enzyme and to discover potent phytocompounds capable of disrupting this interaction. In this study, we utilized molecular docking to check the effect of the identified mutation on the binding of c-Src with HK2. Virtual drug screening, MD simulation, and binding free energy were employed to identify potent drugs against the binding interface of c-Src and HK2. Among these mutations, six (W151C, L272P, A296S, A330D, R391H, and P434A) were observed to significantly disrupt the stability of the c-Src structure. Additionally, through molecular docking analysis, we demonstrated that the mutant forms of c-Src exhibited high binding affinities with HK2. The wildtype showed a docking score of -271.80 kcal/mol, while the mutants displayed scores of -280.77 kcal/mol, -369.01 kcal/mol, -324.41 kcal/mol, -362.18 kcal/mol, 266.77 kcal/mol, and -243.28 kcal/mol for W151C, L272P, A296S, A330D, R391H, and P434A respectively. Furthermore, we identified five lead phytocompounds showing strong potential to impede the binding of c-Src with HK2 enzyme, essential for colon cancer progression. These compounds exhibit robust bonding with c-Src with docking scores of -7.37 kcal/mol, -7.26 kcal/mol, -6.88 kcal/mol, -6.81 kcal/mol, and -6.73 kcal/mol. Moreover, these compounds demonstrate dynamic stability, structural compactness, and the lowest residual fluctuation during MD simulation. The binding free energies for the top five hits (-42.44±0.28 kcal/mol, -28.31±0.25 kcal/mol, -34.95±0.44 kcal/mol, -38.92±0.25 kcal/mol, and -30.34±0.27 kcal/mol), further affirm the strong interaction of these drugs with c-Src which might impede the cascade of events that drive the progression of colon cancer. Our findings serve as a promising foundation, paving the way for future discoveries in the fight against colorectal cancer.

Numerical Analysis of Flood Invasion Path and Mass Flow Rate in Subway Stations under Heavy Rainfall Conditions

The occurrence of extreme weather, such as heavy rainfall and sudden increases in precipitation, has led to a notable rise in the frequency of flooding in subway stations. By conducting numerical simulations of flood disasters in subway stations under heavy rainfall conditions and gaining insights into the patterns of flood invasion inside the stations, it is possible to develop practical and feasible drainage designs for the stations. This paper employs the computational fluid dynamics (CFD) method, utilising the volume of fluid function (VOF) method and the renormalization k-ε group model within the vortex viscosity model. The complete process of flood invasion into subway stations with varying water levels (1500 mm, 2000 mm, and 2450 mm) is modelled, and the distribution of floods at different times under varying operational conditions is analysed to identify the evolutionary patterns of station flood history. The simulation calculations yielded the mass flow rate time history curve at the tunnel entrance and exit, which was then subjected to an analysis of its development trend over time. The total accumulated water in the subway station is calculated by integrating the difference in mass flow rate between the entrance and the tunnel exit, using the mass flow rate curve. In conclusion, the paper proposes drainage measures that provide valuable insights into pumping strategies when floodwaters infiltrate subway stations. The results indicate that the speed of flood spreading in subway stations increases with higher groundwater levels, and that the mass flow rate of floodwater entering the tunnels increases over time, eventually reaching a stable state. It was observed that, at certain times, the mass flow rate of floodwater into the tunnels exhibited a linear relationship with time.

Investigation of the mechanism of carrier recombination in GaN-based blue laser diodes before lasing

Abstract The carrier recombination behavior of GaN-based blue laser diodes (LDs) is studied and analyzed by experiments and simulation calculations before lasing, with a particular focus on the role of Auger recombination. It is found that Auger recombination plays a crucial role in the decrease in differential efficiency and threshold current of GaN-based blue LDs. The theoretical calculation results show that a large Auger recombination rate may lead to a dominant recombination channel before lasing, which could exceed the radiation recombination and result in an obvious decrease in the differential efficiency. Such a high Auger recombination will dissipate a large number of carriers in the quantum well, resulting in deterioration of device performance, a higher threshold current and a lower efficiency. This work presents a method to evaluate Auger recombination through differential efficiency and also provides evidence that suppressing the Auger recombination rate is beneficial to improve the performance of blue LDs.

Adsorption mechanism of cefradine on three microplastics: A combined molecular dynamics simulation and density functional theory calculation study

Microplastics and antibiotics are receiving increasing attention as two emerging pollutants in the aquatic ecosystem. The absorption of antibiotics by microplastics can potentially intensify their impact on marine organisms and human health. However, the detailed mechanisms underlying this interaction remain to be elucidated. Through molecular dynamics (MD) simulations and density functional theory (DFT) calculations, this study investigated the adsorption of cefradine (CED) onto three typical microplastics (MPs)-polyethylene (PE), polypropylene (PP), and polyamide (PA). The results of the molecular dynamics simulations showed that the interaction energy between CED and microplastics followed the order of PA-CED > PP-CED > PE-CED, indicating that PA microplastics had the highest adsorption capacity for CED antibiotics. The total energy contribution of the microplastics-cefradine (MPs-CED) systems suggested that the van der Waals and electrostatic interactions were the two primary mechanisms for the adsorption of CED by these three microplastics. In DFT calculations, the adsorption of CED on PA was found to be significantly influenced by both electrostatic and van der Waals effects, while the main driving force in the adsorption of PE and PP is van der Waals effect. In addition, IGMH analysis and AIM topological analysis confirmed that the adsorption of CED on PA relied heavily on the synergistic effect of hydrogen bonding and the van der Waals effect. The findings of this study validate the results obtained from molecular dynamics simulations, laying a foundation for a comprehensive exploration of the interaction mechanisms between microplastics and organic pollutants by integrating MD simulations and DFT calculations.

Stable novel silicon allotropes in space group P2/m with various band gap structures by high-throughput screening

Silicon is the fundamental material for the semiconductor and microelectronics industries, but controlling the electronic band gap structure of diamond-type silicon remains a huge challenge to adapt to growing applications. Here, we have predicated 23 new silicon allotropes in space group P2/m from 279 possible structures by high-throughput screening accompanied by graph and group theory based on random strategy (RG2) code. The mechanical, electronic and optical properties of these structures were studied in detail. These novel silicon allotropes demonstrate various electronic structures, including metal, direct/quasi direct bandgap structure, and indirect bandgap structures. These new silicon allotropes demonstrate various electronic structures, including metal, direct/quasi direct bandgap structure, and indirect bandgap structures. Besides different electronic bandgap structures, all 23 structures exhibit strong absorption in the visible light region and P2/m-15 demonstrates the excellent mechanical properties (Bulk modulus beyond 80 GPa). Based on their nice stability, good mechanical, electronic and optical properties validated by the ab inito molecular dynamics simulation, phonon spectra and density functional theoretical calculations, these predicted silicon allotropes provide not only ideas for the synthesis of new silicon allotropes but also dawn for expanding the application of semiconductor materials.

Solute structure effect on polycyclic aromatics separation from fuel oil: Molecular mechanism and experimental insights

AbstractIonic liquids (ILs) are promising solvents for separating aromatics from fuel oils. However, studies for separate polycyclic aromatics with ILs are rare and insufficient, and the impact of solute structure on extraction performance still needs to be determined. In this work, we use 1‐ethyl‐3‐methylimidazolium bis([trifluoromethyl]sulfonyl)imide ([EMIM][NTF2]) as an extractant to separate 1‐methylnaphthalene, quinoline, and benzothiophene from dodecane mixtures. Liquid–liquid equilibrium experiments identified the optimal operating conditions. Nine solute molecules, including five alkanes and four aromatic hydrocarbons, were used to study the relationship between extraction performance and solute structure. Molecular dynamics simulation and quantum chemistry calculations gave a deep insight and reasonable interpretation of the structure‐performance relationship at the molecular level. An industrial‐scale extraction process was proposed. The IL can be easily regenerated using heptane as a back‐extractive solvent. A high‐purity fuel oil with aromatic content below 0.5 wt% is obtained after 8‐stage extraction.

Highly reversible Zn anode by guiding uniform Zn deposition through LiF protective layer

Deep-seated issues such as ineluctable dendrite deposition and parasitic reaction of Zn anode pose a major obstacle to the commercialization of aqueous zinc ion batteries (AZIBs). Herein, we proposed LiF as a solid-electrolyte interphase for highly reversible Zn anode. Combining experimental analyses and theoretical simulation calculations, the electronegative fluorine atoms could provide uniform zincophilic nucleation sites to regulate Zn deposition behavior. Additionally, a ZnF2 layer with outstanding Zn2+ conductive can be formed insitu thus further shielding bulk water molecules and expediting the Zn2+ transfer kinetics. Therefore, the LiF@Zn symmetric cells manifest long-cycling stability with 650 h at 1.0 mA/cm2 and 1.0 mAh/cm2 and 1000 h at 2.0 mA/cm2 and 1.0 mAh/cm2. Meanwhile, the rate performance of Zn//MnO2 and Zn//NH4V4O10 full cells are also enhanced by the LiF coating. This work provides a horizon for the design of artificial protective layer and promotes the large-scale practical development of AZIBs.

Simulation Analysis of Three-Point Bending Fracture Process of Yellow River Ice

During the ice flood period of the Yellow River, the fracture and destruction of river ice can easily lead to the formation of ice jams and ice dams in the curved and narrow reaches. However, the occurrence and development mechanism of river ice fracture remain incompletely understood in the Yellow River. Therefore, based on the three-point bending physical test of the Yellow River ice, a three-point bending fracture numerical model of the Yellow River ice was constructed. The fracture failure process of the Yellow River ice under three-point bending was simulated, and the effects of the crack-to-height ratio and ice grain size on the fracture properties of the river ice were analyzed. By comparing the results with those of physical tests on river ice, it is evident that the fracture model can effectively simulate the cracking process of river ice. Within the confines of the simulated sample size spectrum, as the crack-to-height ratio varies from 0.2 to 0.8, the fracture toughness value of the Yellow River ice spans a range from 115.01 to 143.37 KPa·m1/2. Correspondingly, within the simulated calculation values ranging from 5.38 mm to 24.07 mm for ice crystal size, the fracture toughness value of the Yellow River ice exhibits a range from 116.89 to 143.37 KPa·m1/2. The findings reveal that an increase in the crack-to-depth ratio leads to a decrement in the fracture toughness of river ice. Within the scale range encompassed by the model calculations, as the average size of the ice crystal grains augments, the fracture toughness of the river ice exhibits a gradual ascending trend. The research results provide a parameter basis for studying the fracture performance of the Yellow River ice using a numerical simulation method and lays a foundation for investigating the cracking process of river ice from macro and micro multi-scales.

Study on microstructure characterization of steel using on multi-frequency electromagnetic detection and FE simulation calculation

Microstructures dominate mechanical properties of steel materials. Monitoring and controlling microstructure variations are important for high-quality steel productions. In this study, the multi-frequency electromagnetic technology is used to effectively characterize changes of steel microstructures. Steel samples with individual micro- components are obtained using different heat treatments and are measured using a self-designed multi-frequency electromagnetic system. Micro- and Macro- FE models are developed to discuss electromagnetic responses on steel microstructures with different phases, grain size and grain boundaries. The relative permeability of different steel microstructures are calculated and discussed. Results show that the low frequency inductance will increase with the increase of ferrite grain size and ferrite fraction. The relative permeability of single ferrite grain boundary is determined to be 165 and the orientation of grain boundary can influence the relative permeability of steel microstructures.

Neutral beam microscopy with a reciprocal space approach using magnetic beam spin encoding

The emerging technique of neutral beam microscopy offers a non-perturbative way of imaging surfaces of various materials which cannot be studied using conventional microscopes. Current neutral beam microscopes use either diffractive focusing or pin-hole scanning to achieve spatial resolution, and are characterised by a strong dependence of the imaging time on the required resolution. In this work we introduce an alternative method for achieving spatial resolution with neutral atom beams which is based on manipulating the magnetic moments of the beam particles in a gradient field, and is characterised by a much weaker dependence of the imaging time on the image resolution. The validity of the imaging approach is demonstrated experimentally by reconstructing one dimensional profiles of the beam which are in good agreement with numerical simulation calculations. Numerical simulations are used to demonstrate the dependence of the signal to noise on the scan resolution and the topography of the sample, and assess the broadening effect due to the spread of velocities of the beam particles. The route towards implementing magnetic encoding in high resolution microscopes is discussed.

Insights from Ab Initio Molecular Dynamics on the Interface Reaction between Electrolyte and Li2MnO3 Cathode during the Charging Process.

The complex interface reactions are crucial to the performance of the Li2MnO3 cathode material. Here, the interface reactions between the liquid electrolyte and the typical surfaces of Li2MnO3 during the charging process are systematically investigated by ab initio molecular dynamics (AIMD) simulation and first-principles calculation. The results indicate that these interface reactions lead to the formation of hydroxide radicals, oxygen, carbon dioxide, carbonate radicals, and other products, which are consistent with the experimental findings. These processes primarily result from the conversion of the stable closed-shell O2- into reactive oxygen ions by electron loss. All surfaces exhibit some degree of layered- and spinel-like phase transitions during the AIMD simulations, consistent with the experiment. This is mainly attributed to the decrease in the Mn-O bond strength and the increase in the Li/O ion vacancy concentration. This study offers valuable theoretical insights into the interface reaction between lithium-rich cathode materials and liquid electrolytes.

Determination on Effective Drainage Radius of In-Seam Borehole Based on Gas Content Test and Numerical Simulation Calculation Method.

In order to accurately and efficiently determine the effective drainage radius of the in-seam borehole, the advantages and disadvantages of the current effective drainage radius test methods are analyzed, and the method of combining the gas content field and numerical simulation calculation is proposed to accurately determine the effective drainage radius of the borehole, which is applied in the mine. The results show that the method combining gas content test and numerical simulation calculation has the advantages of a short measurement period and advanced means. The effective drainage radius of the borehole increases rapidly at the initial stage of gas drainage and then gradually slows, eventually reaching a limit value. The relationship between the effective drainage radius and drainage time follows a Langmuir function relationship. When the drainage time exceeds 300 days, the effect of the drainage time on the effective drainage radius becomes relatively small. The average error between the numerical simulation results of effective drainage radius and the field verification results of gas content is 2.2%, which validates the rationality of the constructed coal seam gas-solid coupling model. The research can provide theoretical references for accurately determining and reasonably laying out the effective drainage radius of the bedding borehole in the mining seam of the coal mine, which is of great practical significance for the safety production of the mine.

Engineering ion diffusion and electron transfer dual pathways within porous spherical H1.6Mn1.6O4 for highly efficient Li+ separation

Efficient and selective electrochemical lithium adsorption from liquid resources is crucial for sustainable lithium extraction and purification. However, the sluggish Li+ diffusion kinetics often lag behind electron transfer rates, hindering the overall adsorption efficiency in capacity and kinetics. This work addresses this challenge by introducing a tunable porous spherical architecture in H1.6Mn1.6O4 adsorbent particles. The Li+ diffusion coefficient (DLi+) enhanced from 1.32 × 10-12 cm2/s to 3.61 × 10-12 cm2/s, the solution resistance (Rs) decreased from 28.88 ohm to 25.30 ohm, the charge transfer resistance (Rct) decreased from 31.04 ohm to 30.40 ohm, and the desolvation activation energy (Ea) reduced from 10.81 kJ/mol to 9.81 kJ/mol. Consequently, the optimized porous spherical H1.6Mn1.6O4 demonstrates superior adsorption capacity and adsorption kinetics, exceeding 24.23 mg/g at 180 min, which is 1.26 times that of the dense spherical counterpart (19.28 mg/g). The simulation calculations of Li+ diffusion highlight the pivotal role of the porous structure in accelerating internal Li+ diffusion, thereby significantly contributing to the enhanced overall adsorption efficiency of H1.6Mn1.6O4. This work emphasizes the significance of synergistically optimizing ion diffusion channels and electron transfer paths for enhancing electrochemical processes and provides a path for constructing similar pore structures in various ion–electron-related applications.

Self-Supporting Hierarchical Carbon Network Loaded with NiW Nanoparticles for Efficient Hydrogen Evolution.

Water splitting technology can convert renewable energies such as solar and wind into hydrogen energy, which is key to achieving a low-carbon hydrogen economy cycle. However, Pt-based catalysts for hydrogen evolution reaction (HER) are too expensive, thus it needs to develop efficient non-noble metal catalysts as alternatives. Herein, Ni-BDC-loaded carbon cloth (CC) is co-pyrolyzed with urea to obtain a composite structure of carbon nanotubes (CNT) and porous carbon (PC) embedded with W-doped Ni nanoparticles on CC, resulting in NiW-CNT/PC/CC. Benefiting from the synergistic effect between Ni and W, the high conductivity of CNT, and the high mass transfer rate of PC, NiW-CNT/PC/CC exhibits excellent HER activity in KOH, which only requires a low overpotential of 45mV to drive a current density of 10mAcm-2 with stability exceeding 40 h. Simulation calculations confirm that the W doping in metal Ni can optimize its electronic structure by lowering the d-band center and weakening hydrogen adsorption, thus reducing its HER barrier.

Mechanism analysis of pitting induced by Al2O3 inclusions: insight from simulation calculation

Mechanism analysis of pitting induced by Al2O3 inclusions: insight from simulation calculation

Rational Design of Non-Covalent Imprinted Polymers Based on the Combination of Molecular Dynamics Simulation and Quantum Mechanics Calculations.

Molecular imprinting is a promising approach for developing polymeric materials as artificial receptors. However, only a few types of molecularly imprinted polymers (MIPs) are commercially available, and most research on MIPS is still in the experimental phase. The significant limitation has been a challenge for screening imprinting systems, particularly for weak functional target molecules. Herein, a combined method of quantum mechanics (QM) computations and molecular dynamics (MD) simulations was employed to screen an appropriate 2,4-dichlorophenoxyacetic acid (2,4-D) imprinting system. QM calculations were performed using the Gaussian 09 software. MD simulations were conducted using the Gromacs2018.8 software suite. The QM computation results were consistent with those of the MD simulations. In the MD simulations, a realistic model of the 'actual' pre-polymerisation mixture was obtained by introducing numerous components in the simulations to thoroughly investigate all non-covalent interactions during imprinting. This study systematically examined MIP systems using computer simulations and established a theoretical prediction model for the affinity and selectivity of MIPs. The combined method of QM computations and MD simulations provides a robust foundation for the rational design of MIPs.

Natural product-derived ALK inhibitors for treating ALK-driven lung cancers: an in silico study.

Anaplastic lymphoma kinase (ALK)-driven lung cancer represents a critical therapeutic target, demanding innovative approaches for the identification of effective inhibitors. Anaplastic lymphoma kinase (ALK), a key protein involved in the pathogenesis of ALK-driven lung cancers, has been the focus of extensive drug discovery efforts. This study employed a comprehensive computational drug discovery approach, integrating virtual screening with the Lipinski filter, re-docking, molecular dynamics (MD) simulations, and free energy calculations to identify potential inhibitors from a natural compound library. Utilizing the MTiOpenScreen web server, we screened for compounds that exhibit favorable interactions with ALK, resulting in 1227 compounds with virtual screening scores ranging from -10.2 to -3.7kcal/mol. Subsequent re-docking of three selected compounds (ZINC000059779788, ZINC000043552589, and ZINC000003594862) and one reference compound against ALK yielded docking scores -10.4, -10.2, -10.2, and -10.1kcal/mol, respectively. These compounds demonstrated promising interactions with ALK, suggesting potential inhibitory effects. Advanced analyses, including MD simulation and binding free energy calculations, further supported the potential efficacy of these compounds. MD simulations, particularly the root mean square deviation (RMSD) and root mean square fluctuation (RMSF) analyses, revealed that compounds ZINC000059779788 and ZINC000003594862 achieved better stability compared to compound ZINC000043552589. These stable conformations suggest effective binding over time. Free energy calculations using the MM/GBSA method showed that ZINC000059779788 had the most favorable binding energy, indicating a strong and stable interaction with the ALK protein. The promising computational findings from this study emphasize the necessity for additional experimental testing to verify the therapeutic efficacy of these natural compounds for treating lung cancers.

Molecular simulation of the slurrying mechanism in microplastic semi-coke water slurry.

This study explores the interaction between particles in microplastic semi-coke water slurry at the molecular level using molecular simulation methods, specifically DFT calculations and MD simulations. In addition, the experiment of slurry preparation was carried out to study the viscosity and stability of the slurry. The electrostatic potential analysis shows that the interaction between microplastics and dispersant molecules occurs on atoms with large electronegativity or oxygen-containing functional groups, and the energy gap of frontier molecular orbitals indicated that PVC interacts most easily with the dispersant (0.39eV), followed by PS (1.08eV) and PET (3.65eV). In addition, it is also noted that due to the steric hindrance effect, the adsorption energy was opposite to the DFT calculation results: PET was - 213.338kcal/mol (NNO) which was highest, followed by PS (- 107.603kcal/mol, NNO), and PVC (NNO) was lowest which was - 94.808kcal/mol. And RDF shows similar results, which the probability of water molecules in the PET system was the highest, followed by PS, and finally, PVC. The MD results are consistent with the viscosity and stability characterization results of the slurry which PET has the lowest viscosity of 87.3mPa·s. Finally, this study provides new ideas for the treatment of microplastics and the improvement of the performance of semi-coke water slurry and reveals the interaction mechanism between microplastics and semi-coke water slurry. All calculations were performed using Materials Studio (MS) version 2020 software, BIOVIA Corporation. The DFT calculation was carried out through the DMol3 module. The DFT calculations include electron density, electrostatics, orbitals, and population analysis. In DMol3 module, the GGA-PBE function was selected to consider gradient changes in density in the simulated calculation. The DFT-D correction was selected, and all electrons were calculated by DNP for accurate core potentials and the DNP file was 4.4. MD simulation was performed through the Forcite module. MD simulation mainly focuses on relative concentration distribution analysis, radial distribution function, and adsorption energy calculation. All molecular geometry optimizations are performed in the Forcite module. In the molecular dynamic part, all simulations used PCFF forcefield. The NVT ensemble was adopted and using the Nosé thermostat.