Monte Carlo Dynamics Simulations Research Articles

Atom-centered machine-learning force field package

In recent years, machine learning algorithms have been widely used for constructing force fields with an accuracy of ab initio methods and the efficiency of classical force fields. Here, we developed a python-based atom-centered machine-learning force field (PyAMFF) package to provide a simple and efficient platform for fitting and using machine learning force fields by implementing an atom-centered neural-network algorithm with Behler-Parrinello symmetry functions as structural fingerprints. The following three features are included in PyAMFF: (1) integrated Fortran modules for fast fingerprint calculations and Python modules for user-friendly integration through scripts and facile extension of future algorithms; (2) a pure Fortran backend to interface with the software, including the long-timescale dynamic simulation package EON, enabling both molecular dynamic simulations and adaptive kinetic Monte Carlo simulations with machine-learning force fields; and (3) integration with the Atomic Simulation Environment package for active learning and ML-based algorithm development. Here, we demonstrate an efficient parallelization of PyAMFF in terms of CPU and memory usage and show that the Fortran-based PyAMFF calculator exhibits a linear scaling relationship with the number of symmetry functions and the system size. Program summaryProgram title: python-based atom-centered machine-learning force field (PyAMFF)CPC Library link to program files:https://doi.org/10.17632/fsn6dkcvrv.1Developer's repository link:https://gitlab.com/pyamff/pyamffLicensing provisions: Apache License, 2.0Nature of problem: Determine an approximate (surrogate) model based upon atomic forces and energies from density functional theory (DFT). With a surrogate model that is less computationally expensive to evaluate than DFT, there can be a rapid exploration of the potential energy surface, accelerated optimization to minima and saddle points, and ultimately, accelerated design of active materials where the kinetics are key to the material function.Solution method: The atomic environments of training data are calculated in terms of Behler-Parrinello fingerprints. These fingerprints are passed to a neural network which is trained to reproduce the energy and force of the training data. A parallel implementation and Fortran backend allow for efficient training and calculation of the resulting surrogate model. Examples of long-time simulations of materials on the surrogate model surfaces are provided.

Adsorption and Corrosion Mitigation Effect of Two New Salen-type Schiff Bases on Mild Steel in Acidic Medium: Experimental and Computational Studies

The quest for more green inhibitors for suppression of material corrosion continues to appreciate due to rising industrialization and advancement in technology. In this work, the abilities of two new salen-type Schiff bases: bis(3,5-dibromosalicylaldehyde) ethylenediamine (DBSE) and bis(3,5- dichlorosalicylaldehyde) ethylenediamine (DCSE) to suppress corrosion of mild steel in 1 M HCl solution were investigated by weight loss method, scanning electron microscopy (SEM), conceptual DFT calculation and molecular dynamics (Monte-Carlo) simulation. The results showed that these compounds are excellent suppressors of mild steel degradation in the acid solution as the degradation process was efficiently retarded to the tune of 92.9% and 97.5% by DCSE and DBSE, respectively at 500 µM inhibitor concentration and 313 K. Suppression efficiency was found to increase with concentration and decrease at elevated temperature due to prevalence of desorption. Adsorption of the inhibitor molecules on mild steel surface occurred by physisorption and in compliance with the Temkin isotherm. The results of SEM analysis confirmed successful formation of protective layers of the inhibitor molecules on the steel surface. Interaction descriptors from DFT calculations and Monte Carlo simulations confirmed the observed ranking of suppression ability as DBSE > DCSE with suspected contributions from both the neutral and protonated forms of the Schiff bases. We conclude that both DCSE and DBSE can be deployed as efficient green inhibitors for the mitigation of mild steel corrosion especially at low to moderately high temperatures.

Roles of specific hydrogen-bonding interactions in the crystallization kinetics of polymers

Polyamides hold specific hydrogen-bonding interactions as the hierarchical thermodynamic driving forces for crystallization. Their roles in crystallization kinetics are worthy of further investigation. We performed dynamic Monte Carlo simulations to compare crystallization kinetics among 16-mer melts holding hydrogen-bonding interactions with variable strengths specifically assigned to 2, 4 and 8 monomers on the chain, respectively. The results demonstrate higher densities and strengths of hydrogen-bonding interactions generally accelerating the cooling and isothermal crystallization as well as the lateral growth of lamellar crystals, consistent with the experimental observations of polyamide crystallization. Too strong hydrogen-bonding interactions will slow down polymer diffusion and thus bring retardation to crystallization kinetics. Furthermore, hydrogen-bonding interactions at the central 8–9 monomers make higher crystal growth rates than those at the evenly distributed 5–12 monomers, demonstrating the dominant roles of specific interactions in the hierarchical parallel packing of polymer chains at the lateral growth front of lamellar crystals.

A theoretical study on the separation of CO2/CH4 through MFI zeolite

The separation of carbon dioxide (CO2) and methane (CH4) is important in addressing global warming and energy shortages. Porous materials play a large role, of which MFI zeolite has received much attention. To better analyse mechanisms or guide experiments, the adsorption and diffusion properties of CO2 and CH4 in MFI zeolite have been studied by Monte Carlo and molecular dynamics simulations. Due to stronger interactions, the loading of pure CO2 is significantly higher than that of CH4. For mixtures (biogas or natural gas), CO2 dominates in competitive adsorption. Lower temperatures and higher pressures correspond to higher adsorption selectivity. In addition, the self-diffusion coefficients of guest molecules in MFI zeolite were also calculated. The diffusion performance of pure CH4 is superior to CO2 under the same conditions. And their self-diffusion coefficient increases with increasing temperature and decreasing load. For mixed components, CO2 greatly limits the diffusion of CH4.

Adsorption-Induced Deformation of Zeolites 4A and 13X: Experimental and Molecular Simulation Study.

Gas adsorption in zeolites leads to adsorption-induced deformation, which can significantly affect the adsorption and diffusive properties of the system. In this study, we conducted both experimental investigations and molecular simulations to understand the deformation of zeolites 13X and 4A during carbon dioxide adsorption at 273 K. To measure the sample's adsorption isotherm and strain simultaneously, we used a commercial sorption instrument with a custom-made sample holder equipped with a dilatometer. Our experimental data showed that while the zeolites 13X and 4A exhibited similar adsorption isotherms, their strain isotherms differed significantly. To gain more insight into the adsorption process and adsorption-induced deformation of these zeolites, we employed coupled Monte Carlo and molecular dynamics simulations with atomistically detailed models of the frameworks. Our modeling results were consistent with the experimental data and helped us identify the reasons behind the different deformation behaviors of the considered structures. Our study also revealed the sensitivity of the strain isotherm of zeolites to pore size and other structural and energetic features, suggesting that measuring adsorption-induced deformation could serve as a complementary method for material characterization and provide guidelines for related technical applications.

Insight into the Viscoelasticity of Self-Assembling Smectic Liquid Crystals of Colloidal Rods from Active Microrheology Simulations.

The rheology of colloidal suspensions is of utmost importance in a wide variety of interdisciplinary applications in formulation technology, determining equally interesting questions in fundamental science. This is especially intriguing when colloids exhibit a degree of long-range positional or orientational ordering, as in liquid crystals (LCs) of elongated particles. Along with standard methods, microrheology (MR) has emerged in recent years as a tool to assess the mechanical properties of materials at the microscopic level. In particular, by active MR one can infer the viscoelastic response of a soft material from the dynamics of a tracer particle being dragged through it by external forces. Although considerable efforts have been made to study the diffusion of guest particles in LCs, little is known about the combined effect of tracer size and directionality of the dragging force on the system's viscoelastic response. By dynamic Monte Carlo simulations, we apply active MR to investigate the viscoelasticity of self-assembling smectic (Sm) LCs consisting of rodlike particles. In particular, we track the motion of a spherical tracer whose size is varied within a range of values matching the system's characteristic length scales and being dragged by constant forces that are parallel, perpendicular, or at 45° to the nematic director. Our results reveal a uniform value of the effective friction coefficient as probed by the tracer at small and large forces, whereas a nonlinear, force-thinning regime is observed at intermediate forces. However, at relatively weak forces the effective friction is strongly determined by correlations between the tracer size and the structure of the host fluid. Moreover, we also show that external forces forming an angle with the nematic director provide additional details that cannot be simply inferred from the mere analysis of parallel and perpendicular forces. Our results highlight the fundamental interplay between tracer size and force direction in assessing the MR of Sm LC fluids.

Research on Influencing Factors of Residential Building Carbon Emissions and Carbon Peak: A Case of Henan Province in China

Buildings are considered to have significant emission reduction potential. Residential building carbon emissions, as the most significant type of building-related carbon emissions, represent a crucial factor in achieving both carbon peak and carbon neutrality targets for China. Based on carbon emission data from Henan Province, a large province located in central China, between 2010 and 2020, this study employed the Kaya-LMDI decomposition method to analyze seven driving factors of carbon emission evolution, encompassing energy, population, and income, and assessed the historical reduction in CO2 emissions from residential buildings. Then, by integrating Kaya identity static analysis with Monte Carlo dynamic simulation, various scenarios were established to infer the future evolution trend, peak time, and potential for carbon emission reduction in residential buildings. The analysis results are as follows: (1) The carbon emissions of residential buildings in Henan exhibited a rising trend from 2010 to 2020, albeit with a decelerating growth rate. (2) Per capita household disposable income is the main driving factor for the increase in carbon emissions, but the household housing purchase index inhibits most of the growth of carbon emissions for the residential buildings in Henan, with the total carbon emission reduction of residential buildings reaches 106.42 million tons of CO2 during the research period. (3) During the period from 2020 to 2050, residential buildings in Henan Province will exhibit an “inverted U-shaped” trend in carbon emissions under the three static scenarios. The base scenario predicts that carbon emissions will reach their peak of 131.66 million tons in 2036, while the low-carbon scenario forecasts a peak of 998.8 million tons in 2030 and the high-carbon scenario projects a peak of 138.65 million tonnes in 2041. (4) Under the dynamic simulation scenario, it is anticipated that residential buildings in Henan Province will reach their carbon peak in 2036 ± 3 years, with a corresponding carbon emission of 155.34 million tons. This study can serve as a valuable reference for the future development of low-carbon pathways within the building sector.

Effects of pore size, water content, and oxygen-containing functional groups on oxygen adsorption in bituminous coal

To further explore the mechanism of coal spontaneous combustion and better grasp the laws of spontaneous combustion, this article studied the adsorption behavior of O2 in coal. Materials studio software was applied to study the adsorption of oxygen under different water content, different pore sizes, and different oxygen-containing functional groups by means of grand canonical Monte Carlo and molecular dynamics simulation methods. The results show that the adsorption capacity of O2 decreases with the increase in water content. With the increase of molecular pore size of coal, the adsorption capacity of O2 increases, and the tight adsorption amounts decrease. The equivalent adsorption heat is less than 42 kJ/mol, indicating that the adsorption of O2 in coal pores is physical adsorption. The smaller the physical adsorption energy and charge transfer value of the hydroxyl group for O2, it indicates that the hydroxyl group is the active group for the physical adsorption of O2.

Hybrid molecular dynamic Monte Carlo simulation and experimental production of a multi-component Cu–Fe–Ni–Mo–W alloy

High-entropy alloys are a class of materials intensely studied in the last years due to their innovative properties. Their unconventional compositions and chemical structures hold promise for achieving unprecedented combinations of mechanical properties. The Cu–Fe–Ni–Mo–W multicomponent alloy was studied using a combination of simulation and experimental production to test the possibility of formation of a simple solid solution. Therefore, Molecular Dynamics and hybrid Molecular Dynamic/Monte Carlo simulations from 10K up to the melting point of the alloy were analyzed together with the experimental production by arc furnace and powder milling. The Molecular Dynamics simulations starting with a bcc type-structure show the formation of a single-phase bcc solid solution type-structure, whereas using Monte Carlo one, generally produced a two-phase mixture. Moreover, the lowest potential energy was obtained when starting from a fcc type-structure and using Monte Carlo simulation giving rise to the formation of a bcc Fe–Mo–W phase and a Cu–Ni fcc type-structure. Dendritic and interdendritic phases were observed in the sample produced by arc furnace while the milled powder evidence an separation of two phases Cu–Fe–Ni phase and W–Mo type-structures. Samples produced by both methods show the formation of bcc and a fcc type-structures. Therefore, the Monte Carlo simulation seems to be closer with the experimental results, which points to a two-phase mixture formation for the Cu–Fe–Ni–Mo–W multicomponent system.

Deuterium occupation of interatomic hole sites in Ni67Zr33 amorphous alloy

The occupation of interatomic hole sites by deuterium in a deuterated Ni67Zr33 amorphous alloy was investigated using diffraction measurements and a combination of reverse Monte Carlo and molecular dynamics simulation techniques. The results show that deuterium atoms occupy various types of polyhedral hole sites, as well as tetrahedral ones. The occupation by a deuterium atom of a tetrahedral hole site causes volume expansion, but that of a larger polyhedral hole site does not cause a substantial change in the volume. Each deuterium atom is chemically bonded with 4–6 metal atoms, even for a larger polyhedral hole formed by seven or more metal atoms.

Molecular simulation of adsorption and diffusion behavior of CO2 in pyrophyllite

Understanding the microscopic process of adsorption and diffusion of CO2 in clay minerals is important for geological storage of CO2. In this study, Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) simulations are used to obtain the adsorption and diffusion behavior of CO2 in pyrophyllite slit pores. The influence of split pore size, temperature, pressure, and water content were analyzed in detail. The adsorption characteristics of CO2 in pyrophyllite were revealed by discussing the distribution of CO2 density profile, adsorption capacity, isosteric heat of adsorption, interaction energy, mean square displacement, self-diffusion coefficient, and molecular orientation distribution. It shows that the excess adsorption isotherm of CO2 in pyrophyllite slit pores demonstrate significant supercritical adsorption characteristics. Surface attractions originating from both pore walls overlap in the middle of pore, leading to an enhanced adsorption capacity of CO2 in pyrophyllite slit pores when pore aperture is lower than 3 nm. In pyrophyllite pores, the presence of water has an enhancing effect on CO2 adsorption when the water content is below 30 wt%. A maximum value of CO2 adsorption amount is reached at the water content of 10 wt%, while negative growth occurs at 35 wt%. At low water content, water molecules form a weak adsorption layer due to the weak attraction of pyrophyllite to water. As water content increases, the self-diffusion coefficient of the CO2 decreases, and the diffusion capacity decreases. The adsorption state of the CO2 molecule on the mineral surface is primarily a parallel configuration, while the water molecule has no clear orientation. Our calculated results can provide guidance for further study of clay-water-adsorbate interface reaction of hydrophobic minerals.

Double-lamella phenomenon of once-folding polymer crystallization raised by chain-end hydrogen-bonding interactions

Poly (ethylene glycol) (PEG) holding molecular weights around 7000 Da exhibits a double-lamella phenomenon on the surface replicas of bulk once-folding crystallization, whose mechanism is still unclear. Concerning to its specific hydrogen-bonding interactions at chain-ends, we performed dynamic Monte Carlo simulations to investigate the effects of specific chain-end interactions on once-folding crystallization of 16-mers. The results showed that the chain-end hydrogen-bonding interactions bring little effects to both kinetics of primary nucleation and lateral growth of chain-folded lamellar crystals but make a more significant terrace at the lateral growth front with a step of metastable once-folding towards the next step of stable chain-extending, raising the double-lamella phenomenon of their surface replicas. We found that the chain-end hydrogen-bonding interactions are rich at the surfaces of once-folded lamellar crystals, which thus enhance their metastability and retard their thickening into the chain-extended crystals. In addition, intra- and inter-molecular secondary nucleation at corresponding chain-folded and extended growth fronts show different growth rate dependences on the specific interaction strengths. Our results revealed the role of specific chain-end interactions in PEG crystallization.

A theoretical study on the CO2-ODHP in HZSM-5 zeolite: From the perspective of adsorption and diffusion

The oxidative dehydrogenation of propane (ODHP) under the action of CO2 is receiving widespread attention. However, it has not been thoroughly studied in terms of adsorption and diffusion. So, the Monte Carlo and molecular dynamics simulations were used to study the adsorption/diffusion properties of the main reactants and products in HZSM-5. C3H8 has the highest adsorption energy and the lowest diffusivity, while the opposite is true for H2. And compared to C3H8, CO2 is more difficult to adsorb, but more diffuse. And the feed ratio has a significant effect on the overall reaction. When C3H8 is more than twice the amount of CO2, the adsorption efficiency of CO2 in the pores is very low. However, excess CO2 can also replace the adsorption of C3H8, reducing the efficiency of the reaction. The ratio of CO2 to C3H8 in the channel approaches 1:1 only when the feed ratio is around 1:3.

Anticorrosive properties of aqueous Cichorium intybus seeds extract as a sustainable-green inhibitor for aluminum corrosion in hydrochloric acid solution: An experimental and DFT/MC/MD theoretical approach

The inhibitory effect of Cichorium intybus seeds (C. Intybus) on the corrosion behavior of Al 7075 alloy was evaluated in a 1 M HCl acid solution using chemical and electrochemical methods. The adsorption process was proved using FTIR, UV-Vis, Fluorescence, SEM, EDX, AFM, and contact angle measurements. The results reflect that C. Intybus provided excellent protection, and all measurements showed that the inhibition performance of extracts increased by increasing the concentration to reach 93.67% at 12% v/v. Furthermore, this substance functioned as a mixed-type inhibitor to obstruct the anodic and cathodic active sites on the surface of the metal. The study outcomes matched the monolayer Langmuir isotherm, and the calculated adsorption free energy and activation energy reflect that the inhibition mechanism featured the physisorption process. The computational studies were used to provide further confirmation of the adsorption mechanism and to find out how organic inhibitor molecules interact with metal surface using Density Functional Theory (DFT) with Lee/Yang/Parr (B3LYP) level, 6–311 + + G(d,p) as the basis function set calculation, Monte Carlo (MC), and Molecular Dynamic (MD) simulations. The findings showed good agreement with both the experimental and theoretical results. One of the important findings of this work is the possibility of using C. Intybus as a greener alternative and environmentally friendly resource for corrosion inhibition in an acidic medium.

Theory of chromatin organization maintained by active loop extrusion

The active loop extrusion hypothesis proposes that chromatin threads through the cohesin protein complex into progressively larger loops until reaching specific boundary elements. We build upon this hypothesis and develop an analytical theory for active loop extrusion which predicts that loop formation probability is a nonmonotonic function of loop length and describes chromatin contact probabilities. We validate our model with Monte Carlo and hybrid Molecular Dynamics-Monte Carlo simulations and demonstrate that our theory recapitulates experimental chromatin conformation capture data. Our results support active loop extrusion as a mechanism for chromatin organization and provide an analytical description of chromatin organization that may be used to specifically modify chromatin contact probabilities.

An Efficient Strategy for Electroreduction Reactor Outlet Fractioning into Valuable Products.

In this work, two industrial dual-step pressure swing adsorption (PSA) processes were designed and simulated to obtain high-purity methane, CO2, and syngas from a gas effluent of a CO2 electroreduction reactor using different design configurations. Among the set of zeolites that was investigated using Monte Carlo and molecular dynamics simulations, NaX and MFI were the ones selected. The dual-PSA process for case study 1 is only capable of achieving a 90.5% methane purity with a 95.2% recovery. As for case study 2, methane is obtained with a 97.5% purity and 95.3% recovery. Both case studies can produce CO2 with high purity and recovery (>97 and 95%, respectively) and syngas with a H2/CO ratio above 4. Although case study 2 allows methane to be used as domestic gas, a much higher value for its energy consumption is observed compared to case study 1 (64.9 vs 29.8 W h molCH4-1).

Clustering of caffeine in water and its adsorption in activated carbon: Molecular simulations and experiments

Motivated by the importance of caffeine removal from wastewater, the clustering and adsorption of caffeine in activated carbon are studied using Molecular Dynamics and Grand Canonical Monte Carlo simulations, and the results validated by experiments showing similar clustering mechanisms in the large pores as well as high caffeine concentrations in water. The mechanism of caffeine clustering as a function of concentration from high concentration up to solubility threshold is described by the creation of hydrogen bonds between dimers (hydrogen of methyl group and oxygen of caffeine) and between dimers and another caffeine molecule (hydrogen bonds between the hydrogen of methyl group and nitrogen of another caffeine molecule). The caffeine solvation pattern shows strong interaction between water and nitrogen atoms of the caffeine molecule. Analysis of the unfolding of caffeine aggregates shows that the solvent accessible surface area varies from 120 to 350 Å2/caffeine molecule (solvent accessible surface area of a single caffeine molecule). Caffeine dimers and more complex forms are also observed in the GCMC simulations, and show that the same mechanism behind the caffeine clustering produces caffeine stacks in the large pores of nanoporous carbon (Activated Carbon Cloth (ACC)). For all molecular simulations, we have utilized our new computed force field for the caffeine molecule as the most accurate force field for both MD and GCMC. This new force field is examined by neutron scattering experiments in the literature for MD simulations and by adsorption isotherm and X-ray scattering experiments for GCMC simulations. According to the X-ray intensity measurements on ACC before and after adsorption, and molecular simulation results, we conclude that this new force field is more accurate than similar force fields in the literature as it produces satisfactory results for both MD and GCMC simulations.

Confinement effect on transport diffusivity of adsorbed CO2–CH4 mixture in coal nanopores for CO2 sequestration and enhanced CH4 recovery

The transport of CO2–CH4 mixture in coal nanopores is crucial to CO2-enhanced coalbed (CO2-ECBM) recovery, but is highly challenging on adsorption-diffusion dominated nanoscale due to the gas-surface and intermolecular interactions. Using Monte Carlo and molecular dynamics simulation, the confinement effect of nanopores with two slit widths (2 and 6 nm) on the CO2–CH4 binary diffusion in the adsorption layer are investigated. A modified computational method for multi-component transport diffusivity in the adsorption layer is proposed by incorporating the survival probability function. The results show that the transport diffusivity in the semi-confined adsorption layer shows a general decreasing tendency with the increase of pressure, while it slightly decreases when the pressure <6.4 MPa in the confined adsorption layer, following an inverse parabola trend with the maximum value at around 12 MPa. Three mechanisms are classified regarding this pressure-dependent evolution. Firstly, the collision between molecules of weaker attraction and surface dominates the transport capacity, and this collisional frequency reduces at the low-pressure region. Accompanying the pressure exceeds the critical threshold, surface diffusion becomes the primary contribution. Lastly, significant intermolecular interactions appear after the adsorption saturation. During the CO2-ECBM process, pressure drawdown is the primary method to release the adsorbed CH4, and the largest recovery ratio can reach 25.9% in 2 nm micropore and 30.1% in 6 nm mesopore. After the early CO2 injection, the transport diffusion of CH4 exceeds that of CO2, and the selectivity of CH4 over CO2 increases in the subsequent CO2 huff-n-puff cycles. The CO2–CH4 mixture under greater confinement effect manifests higher diffusion selectivity, which benefits the separation of the CO2–CH4 mixture and further contributes to the CH4 recovery.

Prediction of Adsorption and Diffusion of Shale Gas in Composite Pores Consisting of Kaolinite and Kerogen using Molecular Simulation.

Natural gas production from shale formations is one of the most recent and fast growing developments in the oil and gas industry. The accurate prediction of the adsorption and transport of shale gas is essential for estimating shale gas production capacity and improving existing extractions. To realistically represent heterogeneous shale formations, a composite pore model was built from a kaolinite slit mesopore hosting a kerogen matrix. Moreover, empty slabs (2, 3, and 4 nm) were added between the kerogen matrix and siloxane surface of kaolinite. Using Grand-Canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations, the adsorption and diffusion of pure methane, pure ethane, and a shale gas mixture were computed at various high pressures (100, 150, and 250 atm) and temperature of 298.15 K. The addition of an inner slit pore was found to significantly increase the excess adsorption of methane, as a pure component and in the shale gas mixture. The saturation of the composite pore with methane was observed to be at a higher pressure compared to ethane. The excess adsorption of carbon dioxide was not largely affected by pressure, and the local number density profile showed its strong affinity to kerogen micropores and the hydroxylated gibbsite surface under all conditions and pore widths. Lateral diffusion coefficients were found to increase with increasing the width of the empty slab inside the composite pore. Statistical errors of diffusion coefficients were found to be large for the case of shale gas components present at low composition. A larger composite pore configuration was created to investigate the diffusion of methane in different regions of the composite pore. The calculated diffusion coefficients and mean residence times were found to be indicative of the different adsorption mechanisms occurring inside the pore.

Phase equilibria and structure of inhomogeneous logarithmic fluids: An atomistic simulation study

Monte Carlo and molecular dynamics simulations are applied to study the phase equilibria and structure of a fluid described by a logarithmic interparticle potential. The two-phase pure species phase envelope was generated for various values of the size term of the potential, and the critical point (the set of conditions at which both phases became indistinguishable) was estimated in each case. A monotonic relationship between both the reduced critical density and temperature and the size term was demonstrated. Molecular dynamics simulations were employed to study the influence of the thermodynamic conditions on the fluid structure, and three different fluid structures were elucidated.