Diffusion and separation of CO2 and CH4 in silicalite, C168 schwarzite, and IRMOF-1: a comparative study from molecular dynamics simulation

Storage and Diffusion of Carbon Dioxide in the Metal Organic Framework MOF-5─A Semi-empirical Molecular Dynamics Study

Metal-organic frameworks (MOFs) have attracted increasing attention due to their high porosity for exceptional gas storage applications. MOF-5 belongs to the family of isoreticular MOFs (IRMOFs) and consists of Zn4O6+ clusters linked by 1,4-benzenedicarboxylate. Due to the large number of atoms in the unit cell, molecular dynamics simulation based on density functional theory has proved to be too demanding, while force field models are often inadequate to model complex host-guest interactions. To overcome this limitation, an alternative semi-empirical approach using a set of approximations and extensive parametrization of interactions called density functional tight binding (DFTB) was applied in this work to study CO2 in the MOF-5 host. Calculations of pristine MOF-5 yield very good agreement with experimental data in terms of X-ray diffraction patterns as well as mechanical properties, such as the negative thermal expansion coefficient and the bulk modulus. In addition, different loadings of CO2 were introduced, and the associated self-diffusion coefficients and activation energies were investigated. The results show very good agreement with those of other experimental and theoretical investigations. This study provides detailed insights into the capability of semi-empirical DFTB-based molecular dynamics simulations of these challenging guest@host systems. Based on the comparison of the guest-guest pair distributions observed inside the MOF host and the corresponding gas-phase reference, a liquid-like structure of CO2 can be deduced upon storage in the host material.

The Role of Diffusivity in Oil and Gas Industries: Fundamentals, Measurement, and Correlative Techniques

The existence of various native or nonnative species/fluids, along with having more than one phase in the subsurface and within the integrated production and injection systems, generates unique challenges as the pressure, temperature, composition and time (P-T-z and t) domains exhibit multi-scale characteristics. In such systems, fluid/component mixing, whether for natural reasons or man-made reasons, is one of the most complex aspects of the behavior of the system, as inherent compositions are partially or all due to these phenomena. Any time a gradient is introduced, these systems try to converge thermodynamically to an equilibrium state while being in the disequilibrium state at scale during the transitional process. These disequilibrium states create diffusive gradients, which, in the absence of flow, control the mixing processes leading to equilibrium at a certain time scale, which could also be a function of various time and length scales associated with the system. Therefore, it is crucial to understand these aspects, especially when technologies that need or utilize these concepts are under development. For example, as the technology of gas-injection-based enhanced oil recovery, CO2 sequestration and flooding have been developed, deployed and applied to several reservoirs/aquifers worldwide, performing research on mass-transfer mechanisms between gas, oil and aqueous phases became more important, especially in terms of optimal design considerations. It is well-known that in absence of direct frontal contact and convective mixing, diffusive mixing is one of most dominant mass-transfer mechanisms, which has an impact on the effectiveness of the oil recovery and gas injection processes. Therefore, in this work, we review the fundamentals of diffusive mixing processes in general terms and summarize the theoretical, experimental and empirical studies to estimate the diffusion coefficients at high pressure—temperature conditions at various time and length scales relevant to reservoir-fluid systems.

Modeling of CO2 adsorption capacity by porous metal organic frameworks using advanced decision tree-based models

In recent years, metal organic frameworks (MOFs) have been distinguished as a very promising and efficient group of materials which can be used in carbon capture and storage (CCS) projects. In the present study, the potential ability of modern and powerful decision tree-based methods such as Categorical Boosting (CatBoost), Light Gradient Boosting Machine (LightGBM), Extreme Gradient Boosting (XGBoost), and Random Forest (RF) was investigated to predict carbon dioxide adsorption by 19 different MOFs. Reviewing the literature, a comprehensive databank was gathered including 1191 data points related to the adsorption capacity of different MOFs in various conditions. The inputs of the implemented models were selected as temperature (K), pressure (bar), specific surface area (m²/g) and pore volume (cm³/g) of the MOFs and the output was CO₂ uptake capacity (mmol/g). Root mean square error (RMSE) values of 0.5682, 1.5712, 1.0853, and 1.9667 were obtained for XGBoost, CatBoost, LightGBM, and RF models, respectively. The sensitivity analysis showed that among all investigated parameters, only the temperature negatively impacts the CO₂ adsorption capacity and the pressure and specific surface area of the MOFs had the most significant effects. Among all implemented models, the XGBoost was found to be the most trustable model. Moreover, this model showed well-fitting with experimental data in comparison with different isotherm models. The accurate prediction of CO₂ adsorption capacity by MOFs using the XGBoost approach confirmed that it is capable of handling a wide range of data, cost-efficient and straightforward to apply in environmental applications.

Molecular Diffusion in a Flexible Mesoporous Metal-Organic Framework over the Course of Structural Contraction

In situ 1H pulsed field gradient (PFG) NMR was used to investigate the molecular diffusion of n-butane in the pores of the flexible metal-organic framework DUT-49(Cu) at 298 K at different pore loadings, including pressure ranges below and above the negative gas adsorption (NGA) transition caused by structural contraction of the material. Supported by molecular dynamics simulations, the investigation provided crucial insight into confined diffusion within a highly flexible pore environment. The self-diffusion coefficients were derived from the experiment and compared with simulations, capturing the diffusion during n-butane adsorption and desorption. This complementary approach has yielded experimental characterization of molecular diffusion mechanisms during the unique process of NGA. This includes the observation of a 4-fold decrease of diffusivity within a less than 2 kPa gas pressure variation, corresponding to the NGA transition point.

Separation of CF4/N2, C2F6/N2, and SF6/N2 Mixtures in Amorphous Activated Carbons Using Molecular Simulations

The capture and separation of CF₄, C₂F₆, and SF₆ and their mixtures containing nitrogen is a challenging process. To solve this, we propose the use of saccharose coke-based carbons as membranes for the adsorption and separation of these gases. By means of advanced techniques of Monte Carlo and molecular dynamics simulations, we have studied the adsorption and diffusion of CF₄, C₂F₆, and SF₆ as well as their mixtures with nitrogen in three HRMC carbon models, namely, CS400, CS1000, and CS1000a. We have computed the adsorption isotherms of the single components and the heat of adsorption as a function of the adsorbed concentration. We have also calculated the competitive adsorption of fluoride molecules and nitrogen at two different molar fractions, 0.1 and 0.9. We have computed the transport properties of the adsorbed gases in terms of the self-diffusivities and corrected diffusivities. The performance of the membranes for the targeted separations has been characterized by the calculation of the permselectivity. Our results indicate that the activated amorphous carbon CS1000a is an efficient adsorbent for the capture of the fluoride adsorbates as well as their purification from nitrogen-based mixtures.

Large-Scale Screening and Machine Learning to Predict the Computation-Ready, Experimental Metal-Organic Frameworks for CO2 Capture from Air

The rising level of CO2 in the atmosphere has attracted attention in recent years. The technique of capturing CO2 from higher CO2 concentrations, such as power plants, has been widely studied, but capturing lower concentrations of CO2 directly from the air remains a challenge. This study uses high-throughput computer (Monte Carlo and molecular dynamics simulation) and machine learning (ML) to study 6013 computation-ready, experimental metal-organic frameworks (CoRE-MOFs) for CO2 adsorption and diffusion properties in the air with very low concentrations of CO2. First, the law influencing CO2 adsorption and diffusion in air is obtained as a structure-performance relationship, and then the law influencing the performance of CO2 adsorption and diffusion in air is further explored by four ML algorithms. Random forest (RF) was considered the optimal algorithm for prediction of CO2 selectivity, with an R value of 0.981, and this algorithm was further applied to analyze the relative importance of each metal-organic framework (MOF) descriptor quantitatively. Finally, 14 MOFs with the best properties were successfully screened out, and it was found that a key to capturing a low concentration CO2 from the air was the diffusion performance of CO2 in MOFs. When the pore-limiting diameter (PLD) of a MOF was closer to the CO2 dynamic diameter, this MOF could possess higher CO2 diffusion separation selectivity. This study could provide valuable guidance for the synthesis of new MOFs in experiments that capture directly low concentration CO2 from the air.

Extremely permeable porous graphene with high H2/CO2 separation ability achieved by graphene surface rejection

Fabrication of a graphene separation sheet is difficult because of the necessity for leakage-free graphene transfer onto a substrate. In this study, porous graphene sheets with thicknesses of one, two, and four layers were directly fabricated on stainless-steel mesh substrates and demonstrated to display high separation ability for H₂, CO₂, and CH₄. The single-layer graphene sample exhibited higher permeance for these molecules than double- and four-layer graphene and displayed similar high selectivity to that of other porous materials. Permeance was proportional to molecular velocity and inversely proportional to interaction strength with graphene; molecular size-dependent permeance was not seen. Molecules that interacted strongly with graphene were attracted to the graphene surface, which hindered permeation. Such graphene surface rejection allowed graphene containing larger pores than the molecular size to provide both high molecular permeance and selectivity. The relationship between the permeance of porous graphene for H₂ and H₂/CO₂ with selectivity suggested that its permeance was higher than that of other materials with high separation performance. Therefore, the porous graphene samples separated molecules with extremely high permeance by graphene surface rejection.

Aggregation Behavior of Nano-Silica in Polyvinyl Alcohol/Polyacrylamide Hydrogels Based on Dissipative Particle Dynamics

Due to the aggregation behavior of nano-silica in aqueous solution, the use of nano-silica without surface modification for synthesizing hydrogels is still a challenging task. This paper presents our study on the use of dissipative particle dynamics simulations to discover the aggregation behavior of nano-silica in polyvinyl alcohol (PVA)/polyacrylamide (PAM) blended hydrogels. By simulations, we aimed at investigating the effects of such factors as nano-silica content, polymer component ratio, temperature and shear rate on the aggregation behavior of nano-silica in terms of the mesoscopic morphologies and the relative concentration distribution functions. Our results reveal that the dispersion of nano-silica is seen if the nano-silica content is increased to 1.5%, and the aggregation of nano-silica becomes noticeable in blended hydrogels with an increase in the nano-silica content. This finding agrees well with the experimental results obtained by means of scanning electron microscopy. Furthermore, it is also found that the dispersion of nano-silica becomes more uniform with an increase in PAM content, temperature and shear rate. These findings greatly enrich our understanding of the aggregation behavior of nano-silica in PVA/PAM blended hydrogels.

Molecular simulations of MOF membranes for separation of ethane/ethene and ethane/methane mixtures

Metal organic framework (MOF) membranes have been widely investigated for gas separation applications. Several MOFs have been recently examined for selective separation of C2H6. Considering the large number of available MOFs, it is not possible to fabricate and test the C2H6 separation performance of every single MOF membrane using purely experimental methods. In this study, we used molecular simulations to assess the membrane-based C2H6/C2H4 and C2H6/CH4 separation performances of 175 different MOF structures. This is the largest number of MOF membranes studied to date for C2H6 separation. We computed adsorption selectivity, diffusion selectivity, membrane selectivity and gas permeability of MOFs for C2H6/C2H4 and C2H6/CH4 mixtures. Our results show that a significant number of MOF membranes are C2H6 selective for C2H6/C2H4 separation in contrast to traditional nanoporous materials. Selectivity and permeability of MOF membranes were compared with other membrane materials, such as polymers, zeolites, and carbon molecular sieves. Several MOFs were identified to exceed the upper bound established for polymeric membranes and many MOF membranes exhibited higher gas permeabilities than zeolites and carbon molecular sieves. Examining the structure-performance relations of MOF membranes revealed that MOFs with cavity diameters between 6 and 9 Å, porosities lower than 0.50, and surface areas between 500-1000 m2 g-1 have high C2H6 selectivities. The results of this study will be useful to guide the experiments to the most promising MOF membranes for efficient separation of C2H6 and to accelerate the development of new MOFs with high C2H6 selectivities.

Structural and water diffusion of poly(acryl amide)/poly(vinyl alcohol) blend films: Experiment and molecular dynamics simulations

To study the effects of composition ratios and temperature on the diffusion of water molecules in PVA/PAM blend films, five simulation models of PVA/PAM with ten water molecules at different composition ratios (4/0, 3/1, 2/2, 1/3, 0/4) were constructed and simulated by using a molecular dynamics (MD) simulation. The diffusion behavior of water molecules in blends were investigated from the aspects of the diffusion coefficient, free volume, pair correlation function (PCF) and trajectories of water molecules, respectively. And the hydrophilicity of blend composite was studied based on the contact angle and equilibrium water content (EWC) of the blend films. The simulation results show that the diffusion coefficient of water molecules and fractional free volume (FFV) of blend membranes increase with the addition of PAM, and a higher temperature can also improve the diffusion of water molecules. Additionally, the analysis of PCFs reveals the main reason why the diffusion coefficient of water in blend system increases with the addition of PAM. The measurement results of contact angle and EWC of blend films indicate that the hydrophilicity of blend films decreases with the addition of PAM, but the EWC of blends increases with the addition of PAM.

A comprehensive study of methane/carbon dioxide adsorptive selectivity in different bundle nanotubes

We have investigated methane/carbon dioxide adsorptive selectivity in carbon nanotube (CNT) and silicon carbide nanotube (SiCNT) bundlesviaMD simulations.

Development of 3-dimensional time-dependent density functional theory and its application to gas diffusion in nanoporous materials

An entropy scaling based TDDFT has been proposed and applied to diffusion in a nanoporous material.

Heterogeneous Diffusion of Alkanes in the Hierarchical Metal-Organic Framework NU-1000

The metal-organic framework (MOF) NU-1000 is a hierarchical material that comprises both micropores and mesopores in its crystalline structure. Because the pore structure is perfectly defined, NU-1000 is an interesting material for improving our understanding of diffusion in hierarchically structured materials. Here, we present molecular dynamics simulations aimed at probing the transport properties of n-alkanes in NU-1000 and introduce methods from the microrheology literature for analyzing the mean-squared displacements and their spatial heterogeneity. Adsorption occurs initially in the smaller channels, and diffusion at low loading is limited by interaction between adsorbate and framework atoms. The larger channels provide a region of low density where molecules are able to diffuse at higher rates predominantly along the channel axes. The disparate size of the channels gives rise to heterogeneity in the diffusivity of the guest molecules, whereas the asymmetry of the channels leads to anisotropic diffusion. Together, the channels form a network of "highways" and "side streets" that provide enhanced diffusion in one dimension.

Glucose recovery from aqueous solutions by adsorption in metal-organic framework MIL-101: a molecular simulation study

A molecular simulation study is reported on glucose recovery from aqueous solutions by adsorption in metal-organic framework MIL-101. The F atom of MIL-101 is identified to be the most favorable adsorption site. Among three MIL-101-X (X = H, NH₂ or CH₃), the parent MIL-101 exhibits the highest adsorption capacity and recovery efficacy. Upon functionalization by -NH₂ or -CH₃ group, the steric hindrance in MIL-101 increases; consequently, the interactions between glucose and framework become less attractive, thus reducing the capacity and mobility of glucose. The presence of ionic liquid, 1-ethyl-3-methyl-imidazolium acetate, as an impurity reduces the strength of hydrogen-bonding between glucose and MIL-101, and leads to lower capacity and mobility. Upon adding anti-solvent (ethanol or acetone), a similar adverse effect is observed. The simulation study provides useful structural and dynamic properties of glucose in MIL-101, and it suggests that MIL-101 might be a potential candidate for glucose recovery.

Wide Carbon Nanopores as Efficient Sites for the Separation of SF6 from N2

SF₆ and SF₆-N₂ mixed gases are used widely as insulators, but such gases have high greenhouse gas potential. The separation of SF₆ from SF₆-N₂ mixed gases is an inevitable result of their use. Single-walled carbon nanohorns (CNHs) were used here for a fundamental study of the separation of SF₆ and N₂. The diameters of the interstitial and internal nanopores of the CNHs were 0.7 and 2.9 nm, respectively. The high selectivity of SF₆ over N₂ was observed only in the low-pressure regime in the interstitial 0.7 nm nanopores; the selectively was significantly decreased at higher pressures. In contrast, the high selectivity was maintained over the entire pressure range in the internal 2.9-nm nanopores. These results showed that the wide carbon nanopores were efficient for the separation of SF₆ from the mixed gas.

Transferable force fields for adsorption of small gases in zeolites

We provide transferable force fields for oxygen, nitrogen, and carbon monoxide that are able to reproduce experimental adsorption in both pure silica and alumino-substituted zeolites at cryogenic and high temperatures.

The thinnest molecular separation sheet by graphene gates of single-walled carbon nanohorns

Graphene is possibly the thinnest membrane that could be used as a molecular separation gate. Several techniques including absorption, cryogenic distillation, adsorption, and membrane separation have been adopted for constructing separation systems. Molecular separation using graphene as the membrane has been studied because large area synthesis of graphene is possible by chemical vapor deposition. Control of the gate sizes is necessary to achieve high separation performances in graphene membranes. The separation of molecules and ions using graphene and graphene oxide layers could be achieved by the intrinsic defects and defect donation of graphene. However, the controllability of the graphene gates is still under debate because gate size control at the picometer level is inevitable for the fabrication of the thinnest graphene membranes. In this paper, the controlled gate size in the graphene sheets in single-walled carbon nanohorns (NHs) is studied and the molecular separation ability of the graphene sheets is assessed by molecular probing with CO2, O2, N2, CH4, and SF6. Graphene sheets in NHs with different sized gates of 310, 370, and >500 pm were prepared and assessed by molecular probing. The 310 pm-gates in the graphene sheets could separate the molecules tested, whereas weak separation properties were observed for 370 pm-gates. The amount of CO2 that penetrated the 310 pm-gates was more than 35 times larger than that of CH4. These results were supported by molecular dynamics simulations of the penetration of molecules through 300, 400, and 700 pm-gates in graphene sheets. Therefore, a gas separation membrane using a 340-pm-thick graphene sheet has high potential. These findings provide unambiguous evidence of the importance of graphene gates on the picometer level. Control of the gates is the primary challenge for high-performance separation membranes made of graphene.