Grand Canonical Monte Carlo Simulations Research Articles

Hydrogen permeability of polyamide 6 as the liner material of Type Ⅳ hydrogen storage tanks: A molecular dynamics investigation

To attain a lightweight structure with high pressure and a high hydrogen storage mass ratio, the type IV hydrogen storage tank is the most popular choice for many fuel cell vehicle enterprises. Using polymer as the liner material prevents hydrogen embrittlement and hydrogen-induced damage of the tanks, but hydrogen permeation is inevitable. Within the service conditions (233–358 K, 0–87.5 MPa) of the Type-IV tanks, the dissolution and diffusion behaviors of H2 in polyamide 6 are comprehensively explored for the first time through the molecular dynamics and Grand Canonical Monte Carlo simulations in this study. The diffusion mechanism of H2 in polyamide 6 is further revealed. The results show that both the diffusion and permeability coefficients have positive correlations with temperature, whereas the opposite is true for the solubility coefficient. These relationships are all consistent with Arrhenius's law in the temperature range, although multiple Arrhenius regions are needed to describe them. A slight decrease in the diffusion and permeability coefficients is observed with increasing pressure. However, this effect is not as significant as that of temperature and can be ignored when the pressure range is narrow enough. The “hopping” mechanism can be used to describe the diffusion of H2 in polyamide 6, where the continuous vibrations and “hopping” allow the diffusion of H2 molecules. These findings will contribute to a more comprehensive understanding of the permeation behavior of H2 in polyamide 6 and evaluate the gas barrier property of the material in practical applications.

Solvent-Directed Construction of a Nanoporous Metal-Organic Framework with Potential in Selective Adsorption and Separation of Gas Mixtures Studied by Grand Canonical Monte Carlo Simulations.

In this report, a microporous metal-organic framework of [Ca(TDC)(DMA)]n (1) and a two-dimensional coordination polymer of [Ca(TDC)(DMF)2 ]n (2), (TDC2- =Thiophene-2,5-dicarboxylate, DMA=N, N'-dimethylacetamide and DMF=N, N'-dimethylformamide) based on Ca(II) were designed by the effect of solvent, and X-ray analysis was performed for the single crystals of 1 and 2. Then, compound 1 was synthesized in three different methods and identified with a set of analyses. Compared to other adsorbents, MOFs are widely used in the field of adsorption and separation of various gases due to a series of distinctive features such as diverse and adjustable structures pores with different dimensions, high porosity and surface area with regular distribution of active sites. Therefore, the ability of 1 to uptake single gases (CH4 , CO2 , C2 H2 , H2, and N2 ) and separation of several binary mixtures of gases (CO2 /CH4 , CO2 /N2 , CO2 /H2 and CO2 /C2 H2 ), were investigated using Grand Canonical Monte Carlo simulations. Volumetric and gravimetric adsorption isotherms in various operating conditions, the isosteric heat of adsorption (qst ), the chemical potential for each thermodynamic state, and snapshots during the simulation process were reported in all cases. The results obtained from the adsorption simulation indicate that compound 1 has a high capacity for uptake of H2 (16 mmol g-1 ) and N2 (12.5 mmol g-1 ), CO2 (6.6 mmol g-1 ), C2 H2 (5 mmol g-1 ) and CH4 (1.5 mmol g-1 ) gases at 1 bar. It also performs well in separating CO2 in binary mixtures, which can be attributed to the presence of open metal sites in nodes of 1 and their electrostatic tendency to interact with CO2 containing the higher quadrupole dipole moment compared to other components of the mixture.

Theoretical Investigation of Inorganic Particulate Matter: The Case of Water Adsorption on a NaCl Particle Model Studied Using Grand Canonical Monte Carlo Simulations

Sodium chloride (NaCl) represents the principal component of atmospheric particulates of marine origin. To gain a molecular-level understanding of the adsorption process of water vapor on the NaCl surface, Monte Carlo simulations performed in the Grand Canonical ensemble were carried out, considering the water adsorption at different water pressures on a NaCl(001) surface. The calculated adsorption isotherm shows four different regions, whose coverages correspond to those of the low-, transition-, high-, and pre-solution-coverage regions experimentally observed. Detailed analysis reveals how the structure of the adsorbed water molecules (islands, layer, and multi-layer) changes depending on water pressure, and how their orientation with respect to the surface varies with the distance from the surface. This detailed information further supports the picture coming from previous experimental IR absorption spectroscopy studies.

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.

Investigation of the effect of the key pore size on the radon adsorption performance by combining grand canonical Monte Carlo and activated carbon modification experiments

Radon (Rn) is an important contributing factor to lung cancer. Activated carbon (AC) is currently the only Rn adsorbent for industrial applications. However, the effect of the key pore size of AC on Rn adsorption remains unclear, and enhancement of the Rn adsorption performance when using AC is still a challenge. In this work, grand canonical Monte Carlo (GCMC) simulations were performed to simulate the Rn adsorption ability of AC with different pore sizes. The adsorption selectivity of AC with pore sizes from 0.42 nm to 0.60 nm for Rn in the atmospheric environment was much greater than that for nitrogen and oxygen. The Rn adsorption performance was also investigated using KOH-modified activated carbon (KAC) with different pore sizes experimentally prepared using high-temperature roasting. The results showed that when the pore volume of KAC was significantly increased to approximately 0.55 nm, the Rn adsorption performance was obviously improved. Its adsorption coefficient reached 6.50 ± 0.11 m3 kg−1, which was 46.7 % higher than that of AC. After heating and regeneration in air, the Rn adsorption performance of KAC was basically unchanged. Combined with the comparative analysis using theoretical and experimental results, the relationship between the Rn adsorption performance of KAC and the pore volume at 0.55 nm is determined, and the accuracy of the GCMC calculation results was substantiated. This research provides a theoretical basis and an experimental method for improving the Rn adsorption performance of AC.

Rational Design of Porous Ionic Liquids for Coupling Natural Gas Purification with Waste Gas Conversion

AbstractRemoval of trace impurities for natural gas purification coupled with waste gas conversion is highly desired in industry. We here report a type of porous ionic liquids (PILs) that can realize the continuous flow separation of CH4/CO2/H2S and the conversion of the captured H2S to useful products. The PILs are synthesized through a step‐by‐step surface modification of ionic liquids (ILs) onto UiO‐66‐OH nanocrystals. The introduction of free tertiary amine groups on the nanocrystal surface endows these PILs with an exceptional ability to enrich H2S from CO2 and CH4 with impressive selectivity, while the permanent pores of UiO‐66‐OH act as containers to store an exceptionally higher amount of the selectively captured H2S than the corresponding nonporous ILs. Simultaneously, the tertiary amines as dual functional moieties offer effective catalytic sites for the conversion of the H2S stored in PILs into 3‐mercaptoisobutyric acid, a key intermediate required for the synthesis of Captopril (an antihypertensive drug). Molecular dynamics, density functional theory calculations and Grand Canonical Monte Carlo simulations help understand both the mechanisms of separation and catalysis performance, confirming that the tertiary amines as well as the permanent pores in UiO‐66‐OH play vital roles in the whole procedure.

Rational Design of Porous Ionic Liquids for Coupling Natural Gas Purification with Waste Gas Conversion.

Removal of trace impurities for natural gas purification coupled with waste gas conversion is highly desired in industry. We here report a type of porous ionic liquids (PILs) that can realize the continuous flow separation of CH4 /CO2 /H2 S and the conversion of the captured H2 S to useful products. The PILs are synthesized through a step-by-step surface modification of ionic liquids (ILs) onto UiO-66-OH nanocrystals. The introduction of free tertiary amine groups on the nanocrystal surface endows these PILs with an exceptional ability to enrich H2 S from CO2 and CH4 with impressive selectivity, while the permanent pores of UiO-66-OH act as containers to store an exceptionally higher amount of the selectively captured H2 S than the corresponding nonporous ILs. Simultaneously, the tertiary amines as dual functional moieties offer effective catalytic sites for the conversion of the H2 S stored in PILs into 3-mercaptoisobutyric acid, a key intermediate required for the synthesis of Captopril (an antihypertensive drug). Molecular dynamics, density functional theory calculations and Grand Canonical Monte Carlo simulations help understand both the mechanisms of separation and catalysis performance, confirming that the tertiary amines as well as the permanent pores in UiO-66-OH play vital roles in the whole procedure.

Fabrication of Pillar‐Cage Fluorinated Anion Pillared Metal–Organic Frameworks via a Pillar Embedding Strategy and Efficient Separation of SO2 through Multi‐Site Trapping

AbstractFlue gas desulfurization is crucial for both human health and ecological environments. However, developing efficient SO2 adsorbents that can break the trade‐off between adsorption capacity and selectivity is still challenging. In this work, a new type of fluorinated anion‐pillared metal–organic frameworks (APMOFs) with a pillar‐cage structure is fabricated through pillar‐embedding into a highly porous and robust framework. This type of APMOFs comprises smaller tetrahedral cages and larger icosahedral cages interconnected by embedded [NbOF5]2− and [TaOF5]2− anions acting as pillars. The APMOFs exhibits high porosity and density of fluorinated anions, ensuring exceptional SO2 adsorption capacity and ultrahigh selectivity for SO2/CO2 and SO2/N2 gas mixtures. Furthermore, these two structures demonstrate excellent stability towards water, acid/alkali, and SO2 adsorption. Cycle dynamic breakthrough experiments confirm the excellent separation performance of SO2/CO2 gas mixtures and their cyclic stability. SO2‐loaded single‐crystal X‐ray diffraction, Grand canonical Monte Carlo (GCMC) simulations combined with density functional theory (DFT) calculations reveal the preferred adsorption domains for SO2 molecules. The multiple‐site host–guest and guest‐guest interactions facilitate selective recognition and dense packing of SO2 in this hybrid porous material. This work will be instructive for designing porous materials for flue gas desulfurization and other gas‐purification processes.

Fabrication of Pillar-Cage Fluorinated Anion Pillared Metal-Organic Frameworks via a Pillar Embedding Strategy and Efficient Separation of SO2 through Multi-Site Trapping.

Flue gas desulfurization is crucial for both human health and ecological environments. However, developing efficient SO2 adsorbents that can break the trade-off between adsorption capacity and selectivity is still challenging. In this work, a new type of fluorinated anion-pillared metal-organic frameworks (APMOFs) with a pillar-cage structure is fabricated through pillar-embedding into a highly porous and robust framework. This type of APMOFs comprises smaller tetrahedral cages and larger icosahedral cages interconnected by embedded [NbOF5]2- and [TaOF5]2- anions acting as pillars. The APMOFs exhibits high porosity and density of fluorinated anions, ensuring exceptional SO2 adsorption capacity and ultrahigh selectivity for SO2/CO2 and SO2/N2 gas mixtures. Furthermore, these two structures demonstrate excellent stability towards water, acid/alkali, and SO2 adsorption. Cycle dynamic breakthrough experiments confirm the excellent separation performance of SO2/CO2 gas mixtures and their cyclic stability. SO2-loaded single-crystal X-ray diffraction, Grand canonical Monte Carlo (GCMC) simulations combined with density functional theory (DFT) calculations reveal the preferred adsorption domains for SO2 molecules. The multiple-site host-guest and guest-guest interactions facilitate selective recognition and dense packing of SO2 in this hybrid porous material. This work will be instructive for designing porous materials for flue gas desulfurization and other gas-purification processes.

Experimental Measurements and Molecular Simulation of Carbon Dioxide Adsorption on Carbon Surface

Summary Geological sequestration of carbon dioxide (CO2) in depleted gas reservoirs represents a cost-effective solution to mitigate global carbon emissions. The surface chemistry of the reservoir rock, pressure, temperature, and moisture content are critical factors that determine the CO2 adsorption capacity and storage mechanisms. Shale-gas reservoirs are good candidates for this application. However, the interactions between CO2 and organic content still need further investigation. The objectives of this paper are to (i) experimentally evaluate the adsorption isotherm of CO2 on activated carbon, (ii) quantify the nanoscale interfacial interactions between CO2 and the activated carbon surface using Monte Carlo (MC) and molecular dynamic (MD) simulations, (iii) evaluate the modeling reliability using experimental measurements, and (iv) quantify the influence of temperature and geochemistry on the adsorption behavior of CO2 on the surface of activated carbon. These objectives aim at obtaining a better understanding of the behavior of CO2 injection and storage in the kerogen structure of shale-gas formations, where activated carbon is used as a proxy for thermally mature kerogen. We performed experimental measurements, grand canonical Monte Carlo (GCMC) simulations, and MD simulations of CO2 adsorption and diffusion on activated carbon. The experimental work involved measurements of the high-pressure adsorption capacity of activated carbon using pure CO2 gas at a temperature of 300 K. The simulation work started with modeling and validating an activated carbon structure by calibrating the GCMC simulations with experimental CO2 adsorption measurements. Then, we extended the simulation work to quantify the adsorption isotherms at a temperature range of 250–500 K and various surface chemistry conditions. Moreover, CO2 self-diffusion coefficients were quantified at gas pressures of 0.5 MPa, 1 MPa, and 2 MPa using MD simulations. The experimental results showed a typical CO2 excess adsorption trend for the nanoporous structures, with a density of the sorbed gas phase of 504.76 kg/m3. The simulation results were in agreement with experimental adsorption isotherms with a 10.6% average absolute relative difference. The self-diffusion results showed a decrease in gas diffusion with increasing pressure due to the increase in the adsorbed gas amount. Increasing the simulation temperature from 300 K to 400 K led to a decrease in the amount of adsorbed CO2 molecules by about 87% at 2 MPa pressure. Finally, the presence of charged functional groups (e.g., hydroxyl–OH and carboxyl–COOH) led to an increase in the adsorption of CO2 gas to the activated carbon surface. The outcomes of this paper provide new insights about the parameters affecting CO2 adsorption and sequestration in depleted shale-gas reservoirs. This in turn helps in screening the candidate shale-gas reservoirs for carbon capture, sequestration, and storage to maximize the CO2 storage capacity.

Molecular Simulation of Adsorption and Diffusion of Methane and Ethane in Kaolinite Clay under Supercritical Conditions: Effects of Water and Temperature

Grand Canonical Monte Carlo (GCMC) simulation and Molecular Dynamics (MD) simulations were used to study the effects of temperature (310 K to 400 K), pressure (≤30 MPa) and water content (0 molecule/nm3 to 9 molecule/nm3) on the adsorption and diffusion behavior of CH4 and C2H6 in 3 nm kaolinite slit under supercritical conditions. The obtained adsorption capacity, isosteric adsorption heat, concentration distribution and diffusion coefficient were analyzed and compared. The simulation results show that the adsorption capacity of C2H6 is higher under low pressure conditions, and the adsorption capacity of CH4 is higher under high pressure conditions due to the small molecular radius and increased adsorption space. The addition of water molecules and the increase in temperature will reduce the adsorption capacity and isosteric adsorption heat of the two gases. We analyzed the changes in Langmuir volume and Langmuir pressure of the two gases under different temperature and water content conditions. The addition of water molecules and the increase in temperature will reduce the saturation adsorption capacity (which has a greater effect on C2H6) and the adsorption rate of the two gases in the kaolinite slit. The water molecules occupy the adsorption site of the gas molecules (limiting the diffusion of the gas molecules), which reduces the interaction between gas molecules and the wall surface, thus altering the distribution of the two gases in the slit. The increase in temperature will accelerate the oscillation of the gas molecules, increasing diffusion, and also leads to a reduction in the peak value of the adsorption peaks of the two gases.

Data Driven Discovery of MOFs for Hydrogen Gas Adsorption.

Hydrogen gas (H2) is a clean and renewable energy source, but the lack of efficient and cost-effective storage materials is a challenge to its widespread use. Metal-organic frameworks (MOFs), a class of porous materials, have been extensively studied for H2 storage due to their tunable structural and chemical features. However, the large design space offered by MOFs makes it challenging to select or design appropriate MOFs with a high H2 storage capacity. To overcome these challenges, we present a data-driven computational approach that systematically designs new functionalized MOFs for H2 storage. In particular, we showcase the framework of a hybrid particle swarm optimization integrated genetic algorithm, grand canonical Monte Carlo (GCMC) simulations, and our in-house MOF structure generation code to design new MOFs with excellent H2 uptake. This automated, data driven framework adds appropriate functional groups to IRMOF-10 to improve its H2 adsorption capacity. A detailed analysis of the top selected MOFs, their adsorption isotherms, and MOF design rules to enhance H2 adsorption are presented. We found a functionalized IRMOF-10 with an enhanced H2 adsorption increased by ∼6 times compared to that of pure IRMOF-10 at 1 bar and 77 K. Furthermore, this study also utilizes machine learning and deep learning techniques to analyze a large data set of MOF structures and properties, in order to identify the key factors that influence hydrogen adsorption. The proof-of-concept that uses a machine learning/deep learning approach to predict hydrogen adsorption based on the identified structural and chemical properties of the MOF is demonstrated.

High-throughput screening of MXenes for hydrogen storage via graph neural network

To better understand the recent experiment on hydrogen storage in MXene multilayers [Nature Nanotechnol. 2021, 16, 331], we propose a multiscale workflow to computationally screen 23,857 compounds of MXene for hydrogen storage in near ambient condition. By using density functional theory simulation to produce the dataset, we trained physics-informed atomistic line graph neural networks to predict hydrogen’s adsorption performance on MXenes, which is further validated through grand canonical Monte Carlo simulation. As a result, ScYC is identified to exhibit a hydrogen storage capacity of 5.7 wt% at 230 K and 100 bar, showing the promise for hydrogen storage.

Hydrocarbons (C8–C12) separation in porous metallocavitand M-PPX (M = Cu, Ag, Au): From computational insight

High throughput computational approach has been employed to investigate the adsorption and separation of C8–C12 hydrocarbons (HCs) on a tube-shaped metallocavitand, pillarplex (PPX). The Cu (I), Ag (I), and Au (I) seamed PPX and their HC complexes has been examined using density functional theory (DFT), proclaiming Cu-PPX has a higher binding affinity with the HCs whereas Ag-PPX is lower. The thermodynamic properties reveal the host–guest complex is stable at ambient condition. Noncovalent interaction (NCI) analysis shows the interaction of guests within the cavity of PPX is mainly attributed by Van der Waals type. The energy decomposition analysis (EDA) enunciates the percentage contribution of dispersion interaction (ΔEdisp) is 59–62%, the electrostatic (ΔEelct) and orbital (ΔEorb) terms have a moderate contribution towards the total binding energy. The Grand canonical Monte Carlo (GCMC) simulation manifests the Cu-PPX and Au-PPX are the ideal hosts with the optimum capacity to store HCs at ambient conditions. The octane uptake is 18.01, 17.50, and 25.31 cm3STP/g in Cu, Ag and Au-PPX and the uptake reduces upon increasing the HC chain length. The isosteric heat of adsorption (Qst) is corroborated with the computed DFT data at ambient setup. The ideal adsorption solution theory (IAST) claims the C8 selectivity in Cu, Ag and Au-PPX is optimum at 298 K and the increasing temperature from 298 K to 323 K, the selectivity of the C9 and C12 in Cu-PPX and Au-PPX, respectively is remarkable after the complete separation of C8. Hence Cu-PPX and Au-PPX is the potential candidate for industrial use to separate the heavy HCs.

Methane adsorption of nanocomposite shale in the presence of water: Insights from molecular simulations

Accurately predicting gas adsorption in shale gas is essential for estimating production capacity and optimizing extraction processes. However, the complex nature of shale reservoirs (heterogeneous structure, organic–inorganic nanopores, moisture content, etc.) presents significant challenges in understanding the mechanism of methane adsorption. To address these challenges, a nanocomposite shale model incorporating kerogen and illite with slit pore widths of 1 nm, 2 nm, and 4 nm is created. The hybrid grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations are used to investigate methane adsorption in rigid and flexible shale models (kerogen matrix and clay mineral) at three different temperatures, several pressures, and various moisture contents. The simulation results show that the methane density distributions revealed asymmetrical behavior due to the heterogeneous surfaces. Factors such as kerogen flexibility, pore width, moisture content, temperature, and pressure were found to significantly influence fluid behavior. A comparative analysis between the rigid and flexible shale models, considering varying pore widths under both dry and moist conditions, revealed noteworthy differences. Kerogen's flexibility led to increased surface roughness and decreased adsorbed density. Conversely, the presence of water reduced methane adsorption sites in illite, resulting in diverse and complex behaviors dependent on pore widths in the shale model. Finally, the results suggest that using adsorbed volume instead of classical adsorption models is recommended for converting excess adsorption into absolute adsorption. This alternative approach can provide more accurate predictions and enhance the understanding of adsorption in shale gas systems.

Molecular simulation of adsorption behaviors of methane and carbon dioxide on typical clay minerals

Knowledge of the interaction mechanisms between shale and CH4/CO2 is crucial for the implementation of CO2 sequestration with enhanced CH4 recovery (CS-EGR) in shale reservoir. As one of the main constituents of shale, clay minerals can profoundly affect the storage capacity of gases in nanopores. In this paper, the adsorption behaviors of both CO2 and CH4 on montmorillonite, illite as well as kaolinite under dry condition are investigated by Grand Canonical Monte Carlo (GCMC) simulation. The results exhibit that the maximum adsorption capacity of single-component CH4 and CO2 is associated with the types of clay crystals. Specifically, the montmorillonite has the strongest adsorption capacity for CO2, followed by illite and kaolinite, while the sequence in maximum adsorption capacity of CH4 is predicted in the order of kaolinite > montmorillonite > illite. These discrepancies are closely related to the characteristics of adsorbate molecules as well as the different structures of clay crystals. Meanwhile, the maximum adsorption capacity of CH4 in studied clay minerals gradually decreases as pore size increases, while nanopores with 2-nm basal spacing demonstrate the highest adsorption capacity for CO2. In addition, it is observed that the studied clay minerals tend to preferentially adsorb CO2 rather than CH4 during binary gas mixtures simulation. The selectivity of CH4/CO2 mixtures in montmorillonite and kaolinite exhibits various performances as the adsorption pressure increases, with the selectivity in montmorillonite being the largest, especially at low pressure. The cation exchange significantly enhances the electrostatic interaction with CO2 molecules, leading to a higher loading of CO2 as well as larger value of selectivity. These findings can provide basis and guidance for the CS-EGR project in shale reservoirs.

Copolyimide Brushes as a Component of a Hybrid Poly(phenylene Oxide) Membrane for Controlling Gas Separation: Effect of Water, Methanol, and Hexane Vapors.

The effect of water, methanol, and hexane vapors on gas permeability was studied in a hybrid membrane containing 5 wt% copolyimide brushes with poly(methyl methacrylate) side chains (PI-g-PMMA) in a poly(phenylene oxide) (PPO) matrix, and in a pristine PPO membrane. These membranes in the form of dense nonporous films were further examined by atomic force microscopy (AFM) and scanning electron microscopy (SEM), as well as by measuring their mechanical and gas transport properties. A gas separation study of the membranes in a dry state and the membranes saturated with water, methanol, and hexane vapors was performed to estimate the effect of each vapor on the H2, CO2, N2 permeability and selectivity in the separation of H2/N2 and CO2/N2 pairs. In general, saturation with water, methanol, and hexane vapors caused a decrease in the gas permeability of both membranes. The hybrid membrane containing copolyimide brushes demonstrated enhanced selectivity in the separation of H2/N2 and CO2/N2 pairs. It was found that a special effect of the vapors used for membrane saturation is associated with their molar volume. The solubility and diffusion coefficients of N2 and CO2 were obtained by Grand Canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations.

Combination of High-Throughput Screening and Assembly to Discover Efficient Metal-Organic Frameworks on Kr/Xe Adsorption Separation.

Recycling Kr and Xe from used nuclear fuel (UNF) is conducive to regenerating economy and protecting the environment, and it is urgent to screen or design high-performance cutting-edge metal-organic framework (MOF) materials for Kr/Xe adsorption separation. After grand canonical Monte Carlo (GCMC) simulations of Kr/Xe adsorption separation on 11,000 frameworks in CoRE MOFs (2019), the important structure-adsorption property relationship (SAPR) was induced; that is, the porosity (φ) at 0.30-0.40, LCD/PLD at 1.00-1.49, density (ρ) range between 1.20 and 2.30 g/cm3, and PLD at 2.40-3.38 Å can be utilized to screen for high-performance G-MOFs and hMOFs. In addition, the key "genes" (metal nodes and linkers) of MOFs determining the Kr/Xe adsorption separation were data-mined by a machine learning technique, which were assembled into novel MOFs. After comprehensive consideration of thermal stability and the adsorbent performance score (APS), eight promising MOFs on Kr/Xe separation with the APS more than 1290.89 were screened out and assembled, which are better than most of the reported frameworks. Note that the adsorption isotherms of these MOFs on Kr and Xe belong to type I curve with the thermodynamic equilibrium mechanism on Kr/Xe based on the confinement effect. Furthermore, according to the electronic structure calculations of the independent gradient model based on Hirshfeld partition (IGMH) and energy decomposition analysis, it is found that the interactions between guests and frameworks are vdW forces with dominant induction energy (Eind). In addition, the electrostatic potential gradients of frameworks are generally linearly negative correlated with Kr uptakes. Therefore, both the geometrical and electronic structures dominate the adsorption separation performance on Kr/Xe. Interestingly, these eight MOFs are also suitable for the separation of CH4/H2 with considerable selectivities and CH4 uptakes of up to 2566.67 and 3.04 mmol/g, respectively. Herein, the accurately constructed SAPR and material genomics strategy should be helpful for the experimental discovery of novel MOFs on Kr/Xe separation experimentally.

Adsorptive separation of CH4, H2, CO2, and N2 using fullerene pillared graphene nanocomposites: Insights from molecular simulations.

The adsorptive separation performances of fullerene pillared graphene nanocomposites (FPGNs) with tunable micro and meso porous morphology are investigated for the binary mixtures of CH4, H2, CO2 and N2 by using grand canonical Monte Carlo (GCMC) simulations. Different fullerene types are considered in designs as pillar to investigate the effects of porosity on the gas separation performances of FPGNs, and the GCMC simulations are performed for an equimolar binary mixture of CO2/H2, CO2/CH4, CO2/N2 and CH4/H2 inspired by industrial gas mixtures. It is found that CO2/N2, CO2/H2 and CH4/H2 selectivity of FPGNs are about 72, 410 and 145 at 298K and 1bar, which are higher than those for several adsorbent materials reported. Five different FPGN models which contain covalently bonded periodical fullerene and graphene units were constructed using C60, C180, C320, C540 and C720 fullerenes, followed by geometry optimization using Open Babel. All GCMC simulations of adsorption were performed in the RASPA. The adsorption isotherms of FPGNs for pure gases are comparatively examined, and their performances are discussed based on the pore structure and isosteric heat of adsorption. Then, the separation factors of FPGNs for equimolar binary mixtures of these gases are elucidated from the difference in the heat of adsorption and the adsorption selectivity.

Molecular Simulation Study Based on Adsorption of Gas (CO2,O2,CH4) on Coal

This study aimed to further explore the adsorption properties of different gases (CO2, O2, and CH4) on the coking coal surface by establishing a molecular model. Changes in the absolute adsorption capacity and the isosteric heat of adsorption of gases under different temperatures, pressures, and compositions were simulated using grand canonical Monte Carlo (GCMC) and molecular dynamics simulations. Interaction energy and energy distribution were used to analyze the adsorption behavior of gases, and the diffusion properties were investigated using the diffusion coefficient and diffusion activation energy. The absolute adsorption results fit well with the Langmuir–Freundlich model. The absolute adsorption capacity had a significant positive correlation with pressure and the corresponding mole fraction, and a significant negative correlation with temperature. The competitiveness, based on binary adsorption selectivity, was in the order of CO2 > O2 > CH4. The isosteric heat of adsorption of CH4 was slightly higher than that of O2, and that of CO2 was 1.49–1.64 times that of O2 and CH4. The isosteric heat of the adsorption of gases was also barely influenced by temperature and pressure. The interaction energy between CO2 and coal was greater than that of O2 or CH4, but the high pressure and high content were not conducive to the adsorption of O2 by CO2. The preferred adsorption site for CO2 was stronger than that for O2 and CH4, and its peak value negatively correlated with the molar fraction. The diffusion coefficient for single component gases initially increased and then decreased with increased pressure, showing a positive correlation with temperature. A close inverse correlation existed between diffusion activation energy and pressure. These results revealed the microscopic adsorption and diffusion regularities of CO2, O2, and CH4 in the coal model, indicating great significance in accurately predicting coal fires.