Molecular Monte Carlo Simulations Research Articles

3D graphene for ultra-high methane and hydrogen storage

The exceptional potential of three-dimensional (3D) graphene materials for ultra-high methane and hydrogen storage is explored in this study, utilizing the grand canonical Monte Carlo (GCMC) molecular simulation method. The 3D boron nitride (BN) graphene materials, synthesized through the substitution of boron and nitrogen for carbon atoms, exhibit superior adsorption capacities. At 298 K, the weight adsorption capacities of two BN materials for methane reach up to 1.134 g/g and 0.82 g/g, respectively, at 30 MPa, significantly exceeding the DOE target of 0.5 g/g. For hydrogen, remarkably, at 77 K and pressures exceeding 1 MPa, the weight adsorption capacity surpasses 5.5 wt%, achieving an impressive 27 wt% at 30 MPa, nearly quintupling the DOE’s hydrogen storage target. Although the volumetric adsorption capacity is lower compared to Metal-Organic Frameworks (MOFs), the 3D graphene materials’ weight adsorption performance positions them as strong contenders for next-generation energy storage solutions. The GCMC simulations substantiate the significance of 3D graphene materials as highly promising adsorbents for efficient methane and hydrogen storage.

Investigation on the methane emissions from permeation of urban gas polyethylene pipes under the background of hydrogen-mixed natural gas transportation

Methane, a more potent greenhouse gas than carbon dioxide, aggravates the greenhouse effect of ecological environment through its emissions. When transporting hydrogen-mixed natural gas through urban polyethylene pipes, methane will be emitted due to the permeation characteristic of polyethylene pipe material. Therefore, it is crucial to pay attention to the methane emissions from permeation of polyethylene pipes for protecting the environment and climate. In this paper, the solubility and diffusion coefficients of methane within hydrogen-mixed natural gas in polyethylene pipe materials are calculated through the Monte Carlo method and molecular dynamics simulation to determine the permeation coefficient of methane. Simultaneously, the methane emissions and equivalent carbon dioxide emissions of the hydrogen-mixed natural gas in polyethylene pipes are investigated. Results indicate the methane solubility coefficient decreases with increasing temperature and hydrogen mixing ratio. The methane diffusion and permeation coefficients increase with the rising temperature and pressure, and decreasing hydrogen mixing ratio. The pressure exerts minor influence while the temperature and hydrogen mixing ratio have more significant impact. That is, the lower the temperature and the higher the hydrogen mixing ratio, the less methane emissions caused by permeation. Therefore, the effective reduction of methane emissions can be achieved by adding the insulation layer to mitigate the impact of high temperature and increasing the hydrogen mixing ratio. For example, for the polyethylene pipe with the operating pressure of 4 bar and the size specification of SDR11, when the temperature drops from 300 K to 260 K, the methane emissions of hydrogen-mixed natural gas with hydrogen mixing ratios of 0 vol%, 20 vol%, 50 vol% and 80 vol% will be drastically reduced by 73.3%, 74.4%, 77.2% and 78.5% respectively, and when 20 vol%∼80 vol% hydrogen are mixed in the natural gas at 260 K, 300 K and 310 K, the methane emissions will be effectively reduced by 26.7%–85.6%, 23.3%–82.1% and 23.9%–82.4% respectively. The findings of this study can serve as guidance for reducing the methane emissions from permeation of polyethylene pipes transporting hydrogen-mixed natural gas.

Atomic cluster expansion interatomic potential for defects and thermodynamics of Cu–W system

The unique properties exhibited in immiscible metals, such as excellent strength, hardness, and radiation-damage tolerance, have stimulated the interest of many researchers. As a typical immiscible metal system, the Cu–W nano-multilayers combine the plasticity of copper and the strength of tungsten, making it a suitable candidate for applications in aerospace, nuclear fusion engineering, and electronic packaging, etc. To understand the atomistic origin of the defects (e.g., vacancies, free surfaces, grain boundaries, and stacking faults and thermodynamical properties), we developed an accurate machine learning interatomic potential for Cu–W based on the atomic cluster expansion (ACE) method. The Cu–W ACE potential can faithfully reproduce the fundamental properties of Cu and W predicted by density functional theory (DFT) calculations. Moreover, the thermodynamical properties, such as the melting point, coefficient of thermal expansion, diffusion coefficient, and equation of the state curve of the Cu–W solid solution, are calculated and compared against DFT and experiments. Monte Carlo molecular dynamics simulations performed with the Cu–W ACE potential predict the experimentally observed phase separation and uphill diffusion phenomena. Our findings not only provide an accurate ACE potential for describing the Cu–W immiscible system but also shed light on understanding the atomistic mechanism during the Cu–W nano-multilayers formation process.

Multilayer Adsorption Characteristics of CO2 in Organic Nanopores with Different Pore Sizes: Molecular Simulation and Ono-Kondo Lattice Model.

Shale contains numerous organic micropores with significant potential for CO2 storage. To precisely evaluate the CO2 storage potential of shale reservoirs, it is essential to accurately quantify the adsorption of CO2 within these pores. This study used Grand Canonical Monte Carlo (GCMC) molecular simulations to analyze the CO2 adsorption behavior in organic micropores of varying sizes. The study clarified the number and width of the CO2 adsorption layers in micropores of various sizes and proposed a method for segmenting the multilayer adsorption structure. Additionally, the classic Ono-Kondo lattice (OK) model was extended to characterize pore-filling adsorption, incorporating solid-gas and gas-gas interactions. Accurate characterization of CO2 multilayer adsorption and precise calculation of CO2 absolute adsorption in micropores were achieved. Results indicate that CO2 exhibits pore-filling adsorption behavior in organic micropores, forming a multilayer adsorption structure governed by the pore size. Following symmetry principles, the adsorption layer structure in organic micropores can be simplified to a maximum of three layers. When only one adsorption layer forms, its width equals the gas-accessible pore size. For two or more layers, the width of the original layer stabilizes as additional layers form. The stable adsorption layer widths, from nearest to farthest from the pore wall, are 0.33, 0.45, and 0.39 nm. The improved OK model accurately describes CO2 excess and absolute adsorption isotherms across different pore sizes and calculates the CO2 density in each adsorption layer, showing high consistency with GCMC simulation results. These findings highlight the importance of understanding the CO2 multilayer adsorption structure for accurately estimating CO2 adsorption in organic micropores.

Adsorption of difluoromethane (HFC-32) and pentafluoroethane (HFC-125) and their mixtures in silicalite-1: An experimental and Monte Carlo simulation study.

Hydrofluorocarbons are a class of fluorinated molecules used extensively in residential and industrial refrigeration systems. This study examines the potential of using adsorption processes with the silicalite-1 zeolite to separate a mixture of difluoromethane (CH2F2, HFC-32) and pentafluoroethane (CF3CF2H, HFC-125) at various concentrations. Pure adsorption data were measured using a XEMIS gravimetric microbalance, whereas binary data were determined using the Integral Mass Balance method. Grand canonical Monte Carlo molecular simulations were performed with the Cassandra package. We found that the results from molecular simulations are in satisfactory agreement with experimental loading measurements. Moreover, we show that ideal adsorbed solution theory could not quantitatively match the experimental or computational measurements of binary adsorption or selectivity. Molecular simulations show that refrigerant molecules do not have a uniform distribution in the zeolite framework.

Molecular Simulation Insights into Chemical-Grafted EPDM for Improving Charge Traps, Moisture Resistance, and Pyrolysis Tolerance

This study explores and verifies the chemical modifications achieved by grafting 4-formylcyclohexyl heptanoate (FH) and 4-(2,5-dioxopyrrolidin-1-yl) cyclohexane-1-carbaldehyde (CC) onto ethylene propylene diene monomer (EPDM) elastomer, a prevalent dielectric material used for reinforced insulation in cable accessories. Employing a rigorous theoretical methodology combining first-principles calculations, molecular dynamics, and Monte Carlo molecular simulations, we elucidate the intricate effects of these chemical-graft modifications on the polymeric structure of EPDM to resist charge transport, moisture-aging, and thermal impact of partial discharge. Our investigation uncovers the emergence of both shallow and deep charge traps within the material, effectively mitigating electron avalanche breakdown. Additionally, we scrutinize the influence of two proposed organic species, acting as grafting agents, on several crucial properties of EPDM including water adsorption uptake, heat capacity, molecular thermal vibration, and polymer pyrolysis. These modifications substantially bolster EPDM’s resistance to high-temperature electrical breakdown and water thermodynamic adsorption, while also enhancing its thermal stability, rendering the proposed chemical-graft modifications an effective way and underling mechanisms for ameliorating electrical insulation performances of EPDM elastomer. Our findings highlight the significant potential of graft modification in molecular structures through comprehensive molecular simulations, offering valuable insights for advancing competent elastomeric polymers in cable accessory insulation.

Unveiling the anti-corrosion Potential of seaweed macroalga Codium tomentosum: A multifaceted investigation into its mechanisms of copper protection

The seaweed macroalga Codium tomentosum (GAE) was extracted by the maceration method, and it was used as an eco-friendly, nontoxic inhibitor of copper in 1 M H2SO4 corrosion media. To evaluate the composition and protective capacity of the GAE, several methods were employed, gravimetric measurements, electrochemical testing include polarization curves and electrochemical impedance spectroscopy, Fourier infrared spectroscopy, UV–visible spectroscopy, and scanning electron microscopy. The findings indicate the green algae extract successfully prevents copper corrosion when immersed in a corrosive medium. The inhibition efficiency demonstrates an increase with rising inhibitor concentration, reaching its peak at 82 % at concentration of 1 g/L. Operating solely through adsorption and inhibiting active sites on the copper surface, the inhibitor has a mixed inhibition characteristic. Temperature sensitivity is observed, resulting in a decrease in efficiency. The hypothesis of physisorption nature and adherence to the Langmuir isotherm type is supported by the alignment of thermodynamic and kinetic research. In addition, the inhibition mechanism of GAE was studied by quantum chemical calculations and molecular Monte Carlo simulation. This work provides a useful insight into the anti–corrosion of copper during industrial pickling or descaling processes.

Binary phase behavior of select organosulfur compounds in supercritical carbon dioxide: A Monte Carlo molecular simulation study.

Pressure-composition binary phase diagrams were determined for methanethiol, dimethyl sulfide, thiophene, benzothiophene, or dibenzothiophene with carbon dioxide at temperatures from 363 to 453K and pressures from 2 to 20 MPa. Utilizing Gibbs ensemble Monte Carlo molecular simulation, phase coexistence compositions were determined, along with the impact of 4% water cosolvent on select results. Solution structure as a function of pressure and temperature is characterized via radial distribution functions. Comparison to available experimental composition data gives overall mean absolute percentage deviations of 2.2% for thiophene, 37% for methanethiol, and 99% for benzothiophene. Solubilities in a CO2-rich phase are calculated to be sufficient to allow extraction and detection of the compounds studied here via supercritical fluid chromatography and mass spectrometry as a possible analysis approach for future Mars rover missions.

Barocaloric effect in a Gay-Berne liquid crystal.

A coarse-grained molecular Monte Carlo simulation of the barocaloric effect in a model Gay-Berne liquid crystal is presented, following the so-called indirect approach wherein the caloric response is obtained from thermodynamic arguments applied to the simulated equilibrium relation between pressure, density, and temperature. From simulation, the magnitude of the effect across the isotropic-nematic and nematic-smectic phase transitions is estimated, together with the heat exchanged outside these transitions, in order to assess its potential for novel cooling and heat pumping applications. Under adiabatic conditions, pressure-induced phase transitions are predicted to result in a temperature variation of a few degrees Kelvin. As a by-product of the simulation, an approximate partial phase diagram of the Gay-Berne fluid under study is also obtained.

Molecular simulation of adsorption and separation of N2 and CF4 on carbon and boron nitride nanostructures

Grand canonical ensemble Monte Carlo (GCMC) molecular simulations were performed to study CF4 adsorption on carbon nanotubes, boron nitride (BN) nanotubes, carbon nanoscrolls, and BN nanoscrolls. At 298 K and 2 MPa, (15,15) BN nanotubes exhibited 4.57 mmol/g and 98 v/v in excess weight and volume adsorption for CF4, respectively, which is a 50 % and 44 % increase over (15,15) carbon nanotubes at 3.04 mmol/g and 68 v/v. BN nanoscrolls with a 1.3 nm interlayer spacing showed even higher adsorption at 13.63 mmol/g and 145 v/v, a 33 % increase over carbon nanoscrolls with a 10.23 mmol/g and 108 v/v. Utilizing Ideal Adsorbed Solution Theory (IAST), we predicted that (14,14) BN nanotubes would have a CF4 adsorption capacity of 4.27 mmol/g and a selectivity of 6.4 at 298 K and 4 MPa for equimolar CF4/N2 mixtures, surpassing (14,14) carbon nanotubes at 3.01 mmol/g and 4.5. BN nanoscrolls with a 1.2 nm spacing showed a 13.35 mmol/g and 8.1 adsorption capacity and selectivity for CF4, respectively, which is superior to carbon nanoscrolls at 9.33 mmol/g and 5.1. These results outperform other porous materials, indicating that BN nanoscrolls are highly promising for CF4 capture.

Capture of carbonyl sulfide trace from natural gas by adsorption on zeolitic Nanostructure: Monte Carlo molecular simulation

The economic and environmental challenge for the oil and gas industries is to eliminate carbonyl sulfide (COS) from natural gas selectively. This compound can lead to corrosion and environmental damage, even when it is present in small amounts. The zeolites have been known as the appropriate adsorbent for COS. Grand Canonical Monte Carlo (GCMC) simulation has been used to explore the suitability of zeolite frameworks with different topologies on the adsorption and separation properties of mixtures containing industrial concentrations of COS in order to overcome the experimental tests that are difficult to handle. The adsorption isotherms for pure COS and COS/methane mixture on purely siliceous zeolites such as BEA, FAU, LTL, MFI, and MOR have been recorded at 298 K within a pressure range of 0–100 kPa. MFI zeolite, with its high adsorption capacity and isosteric heat, has been identified as the most suitable candidate for COS adsorption due to its ideal pore size and shape. Examining the density distribution snapshots reveals the preferred locations of zeolites for the COS adsorption. The findings could be systematically used in various case studies, thereby providing insights into selecting the best zeolitic nanostructure for the industrial removal processes of COS.

Improving separation of CH4 and N2 by adsorption on zeolite Y Ion–Exchanged with ammonium Cations: An experimental and Grand–Canonical Monte Carlo (GCMC) simulation investigation

The separation of methane (CH4) from industrially–important nitrogen (N2)-rich vent streams such as those in liquefied natural gas processing plants is challenging. Pressure swing adsorption (PSA) is a promising, cost–effective solution in gas separation, especially for small–scale units. Further development and commercialisation of PSA–based technologies require access to low–cost, selective adsorbent materials. The current work investigates the improved separation of CH4 from N2 by TMA–Y zeolite which is obtained from the ion exchange treatment of Na–Y zeolite with the ammonium salt tetramethylammonium chloride (TMACl). TMA–Y is commercially called Ionic Liquidic Zeolite (ILZ), patented at The University of Western Australia, and has now been demonstrated on tonne–scale. In particular, we use a combination of experimental and molecular simulation techniques to provide insights into the high CH4–over–N2 selectivity of TMA–Y. For this, we obtain equilibrium isotherms of CH4 and N2 on Na–Y at different temperatures and pressures before and after ion exchange. The true selectivities of the zeolite samples are determined using the Ideal Adsorbed Solution Theory (IAST) and binary–gas grand–canonical Monte Carlo (GCMC) molecular simulations. From experiments and IAST calculations, we report an increase of >110% in the CH4/N2 selectivity of Na–Y after treatment with TMACl (from 2.2 to 4.7 at 5.0 MPa and 303.15 K for a mixture of 0.1 CH4+0.9 N2 mol.mol−1). GCMC molecular simulations provide a detailed picture of the molecular origins of this effect. Specifically, the introduction of TMA+ ions into the structure of Na–Y zeolite leads to a reduction of the available adsorption volume by more than 40% (from 0.30 to 0.17 cm3.g−1 with N2 as the probe molecule) for both adsorbing gas species (i.e. CH4 and N2). However, at the same time, this leads to stronger CH4–cation interactions due to the much higher affinity of TMA+ cations (5 kJ.mol−1) than extra–framework Na+ cations (1 kJ.mol−1) towards CH4. The overall effect of these two trends combined is the higher selectivity of the resulting TMA–Y zeolite for CH4. These molecular insights are useful in the systematic engineering of new materials with improved separation performance.

Application of thermodynamics at different scales to describe the behaviour of fast reacting binary mixtures in vapour-liquid equilibrium

The use of reactive working fluids in thermodynamic cycles is currently being considered as an alternative to inert working fluids, because of the preliminarily attested higher energy-efficiency potential. The current needs to simulate their use in thermodynamic cycles, which may operate in liquid, vapour or vapour-liquid state, are an accurate real-fluid equation of state and ideal gas thermochemical properties of each molecule constituting the mixture, to calculate the equilibrium constant. To this end, the appeal to a multi-scale theoretical methodology is paramount and its definition represents the objective of the present work. This methodology is applied and validated on the system N2O4 ⇌ 2NO2. Firstly, the equations solved for simultaneous two-phase and reaction equilibrium are presented. Secondly, ideal gas thermochemical properties of N2O4 and NO2 are computed at atomic scale by quantum mechanics simulations. Then, to apply the selected cubic equation of state, pure-component properties of the species forming the reactive mixture (critical point coordinates and acentric factor) are required as input. However, these properties are not measurable, since NO2 and N2O4 do not exist in nature as pure components. To get around this difficulty, the methodology relies on molecular Monte Carlo simulations of the pure N2O4 and NO2, as well as on the reactive N2O4 ⇌ 2NO2, enabling the determination of those missing pure-component properties and thus the calculation, on a macroscopic scale, of the reactive mixture properties. Finally, the comparison of calculated mixture properties with available experimental data leads to validate the accuracy of the proposed methodology.

From groove to hillocks – Atomic-scale simulations of swift heavy ion grazing impacts on CaF2

Surface nanopatterning of CaF2 by swift heavy ions irradiation under oblique angles is studied with a combination of the event-by-event Monte Carlo particle transport model and molecular dynamics simulations. The model describes the electronic system excitation and energy transfer to the lattice followed by the atomic response. The approach allowed us to simulate the kinetics of the electronic ensemble excited by a grazing ion demonstrating that the presence of the surface does not reduce the energy of the lattice as expected. On the contrary, the track core temperature near the surface is slightly higher than in the bulk, because electrons reflected from the surface bring a part of the energy back to the core.The formation kinetics of entire grazing ion tracks is studied revealing the mechanisms of various surface nanostructures formation. Depending on the penetration depth, the ion produces a groove bordered by hillocks, a single chain of nanohillocks, a huge hillock at the end of the rift, and a single continuous structure afterward. The critical depth of the material expulsion from the surface equals approximately to the transient molten zone radius (∼4–4.5 nm). The simulated structures are in reasonable agreement with the available experimental data.

Impact of polypyrrole units (pyr*n; n=3, 5, 7, or 9) on the adsorption and excitation dynamics of enrofloxacin antibiotic interaction with hafnium-doped graphene/boron nitride (Hf@GP/BN) heterostructure: A theoretical perspective

This research work focuses on investigating on influence of pyrrole units (pyr) on the structural stability, reactivity, adsorption potential, bonding variation, and the visible-light interactions of enrofloxacin (xacin) antibiotic with hafnium-doped graphene/boron nitride (Hf@GP_BN) heterostructure within the framework of hybrid exchange-correlation functional and the Monte Carlo molecular simulations. The interaction of enrofloxacin (xacin) with the hybrid surface pyr*n_Hf@GP_BN (where n = 3, 5, 7, or 9) provided insights into the effects of changing the polypyrrole (pyr) chain length on the resulting interactions: xacin_pyr3_Hf@GP_BN, xacin_pyr5_Hf@GP_BN, and xacin_pyr7_Hf@GP_BN respectively to gain more efficient degradation capabilities and the influence of the increase polymer chain. The calculated energy gap decreases due to the increase in LUMO energy experienced upon the addition another of ring, nonetheless when the length of the polypyrrole was further adjusted to seven, the energy gap of the composite increased from 2.184 eV to 2.205 eV which is in the range of semi-conductor to support efficient electron excitation. Results of the molecular dynamic (MD) simulation reveal that while the potential energy of the system decreased for all pyr*n_Hf@GP_BN combinations, the magnitude of the potential energy reduction varied with different pyr chain lengths. Pyr3 exhibited the least reduction of 1310.899 ± 36.119 kcal/mol, followed by 1402.128 ± 38.678 for pyr5, 1511.129 ± 40.494 for pyr7, and 1616.720 ± 43.445 kcal/mol for pyr9, which displayed the most substantial reduction. Longer pyr chains (pyr7 and pyr9) seem to have stronger attractive interactions with enrofloxacin, leading to more significant energy reductions. This indicates that longer pyr chains are more effective in stabilizing the interactions between the antibiotic and the hybrid surface. While the UV-excitation analysis revealed that an increase in the polypyrrole chain length led to a decrease in the wavelength for both the adsorbent and the interactions, decreasing order of exciton binding energy is observed as: 0.602585, 0.606008, and 0.597378 for xacin_pyr3_Hf@GP_BN, xacin_pyr5_Hf@GP_BN, and axacin_pyr7_Hf@GP_BN respectively which is below the 1.9 eV benchmark of efficient materials for photodegradation. The findings could contribute to the broader field of photocatalysis, potentially informing the design of more effective photocatalytic materials. Therefore, research contributes to the development of more efficient methods for antibiotic degradation, with potential applications in environmental remediation.

CO2 storage in organic nanopores with varying widths: Molecular simulation and simplified local density model

Accurately characterizing CO2 adsorption behavior in organic nanopores is a prerequisite for estimating CO2 storage capacity in shale reservoirs with complex pore structures. This study employs grand canonical Monte Carlo (GCMC) molecular simulations to investigate the CO2 adsorption characteristics in organic nanopores with varying widths over a wide range of temperatures and pressures. Based on GCMC simulations, the pore width in the simplified Local-Density (SLD) adsorption model is related to key adsorption parameters, enabling the SLD model to evaluate CO2 storage density rapidly and accurately in organic nanopores under complex reservoir conditions. The research findings suggest that the features of CO2 excess adsorption curves are mainly influenced by temperature and the number of adsorption layers. Higher temperatures and increased adsorption layers result in higher pressure requirements to achieve the CO2 excess adsorption peak. Under high pressures, the number of adsorption layers plays a critical role in enhancing the adsorption capacity. Due to the constraints of pore size, there are fewer adsorption layers in micropores, leading to higher CO2 excess adsorption in mesopores than in micropores under high pressures. In the SLD model, the key parameter Λb decays exponentially with the increase of pore width. The average density of CO2 in the nanopores calculated by the modified SLD model is in good agreement with the simulation results. Finally, the research reveals that smaller organic nanopore widths result in higher CO2 densities, with limited sensitivity to temperature and pressure variations. Low pressure and high temperature reservoir conditions are unfavorable for CO2 storage, but adsorption significantly enhances CO2 storage density in nanopores, particularly in micropores.

Rapid screening of gas solubility in ionic liquids using biased particle insertions with pre-sampled liquid trajectories

ABSTRACTWe present an efficient, general-purpose variant of the Widom test particle insertion method for computing chemical potentials of gaseous solutes in fluids or porous solids. The method is implemented in the Monte Carlo molecular simulation engine Cassandra, but receiving phase configurations are independent of this process and may be pre-sampled by other molecular simulation engines such as molecular dynamics codes. Efficiency enhancements present in this method include configurational biasing and accelerated atomic overlap detection. When applied to the estimation of Henry's law constants of atomistic difluoromethane and pentafluoroethane in ionic liquids, the accelerated overlap detection results in a speedup of more than an order of magnitude compared to conventional methods without sacrificing accuracy. We found good agreement between this method and Hamiltonian replica exchange (HREX) for Henry's law constant and absorption isotherm estimation. This embarrassingly parallel method is especially well suited for screening Henry's law constants of many small gases in the same solvents, since a liquid trajectory can be reused for as many solutes as desired.

Anticorrosion performance of nicotinic acid and nicotinic acid hydrazide blended with optimized potassium iodide against Q235 steel corrosion in acid-chloride medium

The most sorted corrosion-inhibiting additives are composed of compounds that are non-toxic, cheap, and soluble in an aqueous medium without requiring organic solvents or surfactants. Nicotinic acid (NTAD) and nicotinic acid hydrazide (NADH) are naturally derived compounds that are non-toxic, cheap, and very soluble in aqueous media. Hence, the present study investigates their anticorrosion performances in an equal mixture of 0.25 M H2SO4 and 0.5 M NaCl medium which mimics the acidic-chloride medium often encountered in typical industrial descaling and pickling processes. The study considered both the individual compounds and their blend with KI at different concentrations. The anticorrosion as well as the synergistic effects were evaluated with combined electrochemical and gravimetric methods. The low inhibition efficiency (%) approaching 50% and 70% were achieved with the individual NTAD and NADH, respectively, while enhanced inhibition efficiencies reaching 96% and 97% respectively, were achieved when blended respective inhibitors with an optimal KI concentration. The adsorption of the inhibitor molecules followed Langmuir isotherm with the Kads and ΔG0 increasing with the addition of KI. The positive synergistic index values confirmed synergism. The overall anticorrosion process as well as the synergistic effect of KI were validated with complementing intensive spectroscopy (FTIR and XPS analysis) and imaging (SEM and AFFM) methods. The experimental data collaborated with DFT computational and Monte Carlo molecular dynamics simulation studies in divulging the inhibition mechanisms of NTAD and NADH without and with KI blending.

Molecular Simulations of the Chain Length Dependent Adsorption of C7‐C14 n‐Alkanes in ZIF‐8

AbstractRecent experiments show that the diffusivities of C8 and C10 n‐alkanes in ZIF‐8 are higher than those of C7 and C9, respectively. We investigated this unusual ‘odd‐even' effect by simulating the adsorption of C7‐C14 n‐alkanes in ZIF‐8 using hybrid Monte Carlo molecular simulations. The resultant adsorption isotherms, guest‐host energies, isosteric heats, and chain length distributions are analyzed for trends among the n‐alkanes. ZIF‐8 cages filled with n‐alkanes are characterized using a combination of image processing and data science to quantify the differences in packing that occur with chain length. Results indicate that packing changes drastically from C7 to C8 and from C9 to C10, which is consistent with the diffusion trends previously reported in experiments.

Simulation Study for the Adsorption of Carbon Disulfide on Hydroxyl Modified Activated Carbon.

In this study, grand canonical Monte Carlo simulations (GCMC) and molecular dynamics simulations (MD) were used to construct models of activated carbon with hydroxyl-modified hexachlorobenzene basic unit contents of 0%, 12.5%, 25%, 35% and 50%. The mechanism of adsorption of carbon disulfide (CS2) by hydroxyl-modified activated carbon was then studied. It is found that the introduction of hydroxyl functional groups will improve the adsorption capacity of activated carbon for carbon disulfide. As far as the simulation results are concerned, the activated carbon model containing 25% hydroxyl modified activated carbon basic units has the best adsorption performance for carbon disulfide molecules at 318 K and atmospheric pressure. At the same time, the changes in the porosity, accessible surface area of the solvent, ultimate diameter and maximum pore diameter of the activated carbon model also led to great differences in the diffusion coefficient of carbon disulfide molecules in different hydroxyl-modified activated carbons. However, the same adsorption heat and temperature had little effect on the adsorption of carbon disulfide molecules.