Simulation of H2/CH4 mixture permeation through MOF membranes using non-equilibrium molecular dynamics

Metal-Organic Framework Membrane Constructor: A Tool for High-Throughput Construction of Metal-Organic Framework Membrane Models

With the rapid development of metal-organic framework (MOF) membranes for separation applications, computational screening of their separation performance has attracted increasing interest in the design and fabrication of such materials. Although bulk crystal models in MOF databases are often used to represent MOF membrane structures, membrane models in slab geometries are still essential for researchers to simulate the separation performance, particularly to understand the effects of the surface/interface structure, pore sieving, and exposed lattice plane on guest permeability. However, to date, no database or method has been established to provide researchers with numerous membrane models, restricting the further development of related theoretical studies. Herein, we propose an algorithm and develop a tool called the "MOF-membrane constructor" to realize the high-throughput construction of membrane models based on the MOF crystal structures. Using this tool, membrane models can be generated with desired sizes, reasonable surface terminations, and assigned exposed crystal planes. The tool can also deduce the most prominent surface in the Bravais-Friedel-Donnay-Harker morphology or identify the pores in MOF crystals and automatically determine an exposed plane for each membrane model. Thus, an MOF-membrane database can be established rapidly according to user simulation requirements. This study can considerably improve the efficiency of building MOF membrane models and may be beneficial for the future development of simulation studies on MOF membranes.

Realizing high performance gas filters through nano-particle deposition

We have studied the separation of a mixture of hydrogen and methane in equal proportions, using a thin film comprised of 10 layers of nanoparticles deposited layer-wise using our "two-point sticking algorithm" which simulates controlled agglomeration of such nanoparticles. We simulate the process of gas separation using LAMMPS. We have studied the scenario where nanoparticles act like hard spheres, maintaining their shape and size, similar to what has been demonstrated by experiments involving self-assembled nanoparticle thin films. We consider the pressure dependence of the results by working at 3 different initial pressures, 0.1 × P₀, 0.5 × P₀ and P₀, where P₀ is the atmospheric pressure. Three different diameters of the nanoparticles, namely 3 nm, 6 nm and 9 nm, are considered, and therefore the overall thickness of the membranes considered ranges from 30 nm to 90 nm. We obtained perm-selectivity values that are significantly higher than the Robeson line for hydrogen-methane gas separation, indicating the novelty and therefore the significant applications of this work. We find that while the permeance of hydrogen remains more or less steady with a ten-fold increase of pressure, the corresponding fall in methane's permeance is very sharp. The fall in methane's permeance with increasing pressure is more pronounced the smaller the nanoparticles of the membrane being used. This results in an even higher selectivity at higher pressure for smaller nanoparticle based membranes.

Insights and Heuristics for Predicting Diffusion Rates of Chemical Warfare Agents in Zirconium Metal-Organic Frameworks

Designing nanoporous catalysts to destroy chemical warfare agents (CWAs) and environmental contaminants requires consideration of both intrinsic catalytic activity and the mass transfer of molecules in and out of the pores. Polar adsorbates such as CWAs experience a heterogeneous environment in many metal-organic frameworks (MOFs) due to the arrangement of the metal nodes and organic linkers of the MOF. However, quantitative relationships between the pore architecture and the resulting diffusion properties of polar molecules have not been established. We used molecular dynamics simulations to calculate the diffusion coefficients of the CWA simulant dimethyl methyl phosphonate (DMMP) in a diverse set of 776 MOFs with Zr₆ nodes. We developed a 4-parameter machine learning model to predict DMMP diffusivities in Zr₆ MOFs and found the model to be transferable to the CWA sarin. We then developed a simplified heuristic based on the machine learning model that the node-node distance and accessible surface area should be maximized to find MOFs with rapid CWA diffusion.

Molecular dynamics simulation of adsorption and separation of xylene isomers by Cu-HKUST-1

Metal-organic frameworks (MOFs) are widely used in the adsorption separation of various gases. A fundamental understanding of the effective separation of xylene isomers helps improve aromatic products' separation efficiency and reduce industrial separation costs. Grand Canonical Monte Carlo (GCMC) simulations combined with Molecular Science is widely used to predict gas adsorption and diffusion in single crystals with metal-organic frameworks. We performed a GCMC + MD combined approach to study xylene isomers' adsorption and separation in Cu-HKUST-1 to predict the permeability and selectivity of the ternary gas mixture in the MOF with the adsorption and diffusion usage data. Most current studies take into account the computational cost and difficulty. Most recent research models are limited to the adsorption of a single or specific molecule, such as hydrogen, methane, carbon dioxide, etc. For this reason, we report an attempt to study the adsorption separation of aromatic gases (p-xylene/o-xylene/m-xylene) based on Cu-HKUST-1 single-crystal materials based on some previous research methods with an appropriate increase in computational cost. To predict the adsorption selectivity and permeability of the ternary mixture of xylene isomers on the MOF surface, the model simulation calculates key parameters of gas adsorption, including gas adsorption volume (N), the heat of adsorption (Q st), Henry coefficient (K), and diffusion coefficient (D).

Separation of SO2 and NO2 with the Zeolite Membrane: Molecular Simulation Insights into the Advantageous NO2 Dimerization Effect

NO₂ and SO₂, as valuable chemical feedstock, are worth being recycled from flue gases. The separation of NO₂ and SO₂ is a key process step to enable practical deployment. This work proposes SO₂ separation from NO₂ using chabazite zeolite (SSZ-13) membranes and provides insights into the feasibility and advantages of this process using molecular simulation. Grand canonical ensemble Monte Carlo and equilibrium molecular dynamics methods were respectively adopted to simulate the adsorption equilibria and diffusion of SO₂, NO₂, and N₂O₄ on SSZ-13 at varying Si/Al (1, 5, 11, 71, +∞), temperatures (248-348 K), and pressures (0-100 kPa). The adsorption capacity and affinity (SO₂ > N₂O₄ > NO₂) demonstrated strong competitive adsorption of SO₂ based on dual-site interactions and significant reduction in NO₂ adsorption due to dimerization in the ternary gas mixture. The simulated order of diffusivity (NO₂ > SO₂ > N₂O₄) on SSZ-13 demonstrated rapid transport of NO₂, strong temperature dependence of SO₂ diffusion, and the impermeability of SSZ-13 to N₂O₄. The membrane permeability of each component was simulated, rendering a SO₂/NO₂ membrane separation factor of 26.34 which is much higher than adsorption equilibrium (6.9) and kinetic (2.2) counterparts. The key role of NO₂-N₂O₄ dimerization in molecular sieving of SO₂ from NO₂ was addressed, providing a facile membrane separation strategy at room temperature.

Accelerated HKUST-1 Thin-Film Property Optimization Using Active Learning

A flow-coating method termed solution shearing has been shown to grow large-area thin films with no void spaces. Attaining full coverage is one of the key prerequisites for the adoption of any metal-organic framework (MOF) thin film for a variety of practical applications, including separation, membranes and sensors. However, the solution-shearing process has multiple discrete and continuous parameters that can be varied, including the metal ion and linker concentrations, solvents, substrate temperature, coating speed, and the number of coating passes. Optimization of these parameters for full coverage is a time-consuming and daunting process due to vast parameter space. Here, we incorporate an active learning approach into the solution-sheared HKUST-1 thin-film-processing parameters to control the coverage and extend the approach to gain control over the thickness. The understanding of high-quality MOF thin-film formation using solution shearing is improved by correlating the processing parameter sets and their corresponding film coverage. A large area and fully covered HKUST-1 thin film with a minimized thickness of 2.2 μm is fabricated by using guidance from active learning. To confirm full coverage, a redox-active molecule, called 7,7,8,8-tetracyanoquinodimethane (TCNQ), is incorporated along with the HKUST-1 thin film. The TCNQ@HKUST-1 thin film with a minimized thickness has the same order of magnitude of electrical conductivity as that of the TCNQ@HKUST-1 thin film created previously while reducing the film thickness by 60%. We show that active learning has the potential to rapidly navigate the vast processing space in multicomponent systems, especially when experiments are expensive and traditional computational models are not readily available for process optimization.

Nanoconfinement and mass transport in metal-organic frameworks

The ubiquity of metal-organic frameworks in recent scientific literature underscores their highly versatile nature. MOFs have been developed for use in a wide array of applications, including: sensors, catalysis, separations, drug delivery, and electrochemical processes. Often overlooked in the discussion of MOF-based materials is the mass transport of guest molecules within the pores and channels. Given the wide distribution of pore sizes, linker functionalization, and crystal sizes, molecular diffusion within MOFs can be highly dependent on the MOF-guest system. In this review, we discuss the major factors that govern the mass transport of molecules through MOFs at both the intracrystalline and intercrystalline scale; provide an overview of the experimental and computational methods used to measure guest diffusivity within MOFs; and highlight the relevance of mass transfer in the applications of MOFs in electrochemical systems, separations, and heterogeneous catalysis.

Recent advances in simulating gas permeation through MOF membranes

In the last two decades, metal organic frameworks (MOFs) have gained increasing attention in membrane-based gas separations due to their tunable structural properties. Computational methods play a critical role in providing molecular-level information about the membrane properties and identifying the most promising MOF membranes for various gas separations. In this review, we discuss the current state-of-the-art in molecular modeling methods to simulate gas permeation through MOF membranes and review the recent advancements. We finally address current opportunities and challenges of simulating gas permeation through MOF membranes to guide the development of high-performance MOF membranes in the future.

Connecting theory and simulation with experiment for the study of diffusion in nanoporous solids

Nanoporous solids are ubiquitous in chemical, energy, and environmental processes, where controlled transport of molecules through the pores plays a crucial role. They are used as sorbents, chromatographic or membrane materials for separations, and as catalysts and catalyst supports. Defined as materials where confinement effects lead to substantial deviations from bulk diffusion, nanoporous materials include crystalline microporous zeotypes and metal–organic frameworks (MOFs), and a number of semi-crystalline and amorphous mesoporous solids, as well as hierarchically structured materials, containing both nanopores and wider meso- or macropores to facilitate transport over macroscopic distances. The ranges of pore sizes, shapes, and topologies spanned by these materials represent a considerable challenge for predicting molecular diffusivities, but fundamental understanding also provides an opportunity to guide the design of new nanoporous materials to increase the performance of transport limited processes. Remarkable progress in synthesis increasingly allows these designs to be put into practice. Molecular simulation techniques have been used in conjunction with experimental measurements to examine in detail the fundamental diffusion processes within nanoporous solids, to provide insight into the free energy landscape navigated by adsorbates, and to better understand nano-confinement effects. Pore network models, discrete particle models and synthesis-mimicking atomistic models allow to tackle diffusion in mesoporous and hierarchically structured porous materials, where multiscale approaches benefit from ever cheaper parallel computing and higher resolution imaging. Here, we discuss synergistic combinations of simulation and experiment to showcase theoretical progress and computational techniques that have been successful in predicting guest diffusion and providing insights. We also outline where new fundamental developments and experimental techniques are needed to enable more accurate predictions for complex systems.

Understanding CO2/CH4 Separation in Pristine and Defective 2D MOF CuBDC Nanosheets via Nonequilibrium Molecular Dynamics

The separation of CO₂/CH₄ gas mixtures is a key challenge for the energy sector and is essential for the efficient upgrading of natural gas and biogas. A new emerging field, that of metal-organic framework nanosheets (MONs), has shown the potential to outperform conventional separation methods and bulk metal-organic frameworks (MOFs). In this work, we model the CO₂/CH₄ separation in both defect-free and defective 2D CuBDC nanosheets and compare their performance with the bulk CuBDC MOF and experimental data. We report the results of external force nonequilibrium molecular dynamics (EF-NEMD) for pure components and binary mixtures. The EF-NEMD simulations reveal a pore blocking separation mechanism, in which the CO₂ molecules occupy adsorption sites and significantly restrict the diffusion of CH₄. The MON structure achieves a better selectivity of CO₂ over CH₄ compared to the bulk CuBDC MOF which is due to the mass transfer resistance of the methane molecules on the surface of the nanosheet. Our results show that it is essential to consider the real mixture in these systems rather than relying solely on pure component data and ideal selectivity. Furthermore, the separation is shown to be sensitive to the presence of missing linker defects in the nanosheets. Only 10% of missing linkers result in nonselective nanosheets. Hence, the importance of a defect-free synthetic method for CuBDC nanosheets is underlined.

Defining New Limits in Gas Separations Using Modified ZIF Systems

Zeolitic-imidazolate frameworks (ZIFs) are candidate materials for the next generation of membranes for cheaper, "greener" separations. More than a decade after ZIF introduction, the high propylene/propane selectivity of ZIF-8 and ZIF-67 is the only example of ZIF membranes with remarkable selectivity efficiency despite their numerous advantages over other families of materials. Herein, we demonstrate the effectiveness of molecular-scale modification in the design of new ZIF materials useful for the separation of important and highly challenging mixtures such as He/CH₄, H₂/CH₄, O₂/N₂, CO₂/CH₄, and CO₂/N₂. Via computational methods, metal and linker substitutions are employed to produce new ZIF-8 variants with a finely discretized range of aperture sizes, as these govern the kinetic-based selectivity of the material. The permeability and selectivity through the ZIF-8 variants of the gases under study are estimated, and their performance is compared with an extensive number of polymeric, metal-organic framework, covalent-organic framework, and mixed-matrix membranes. The comparison shows that some of the ZIF-8 analogues can be used as membranes of unprecedented high separation performance. The scope of this work is to highlight the effectiveness of the molecular level design as means of membrane development to address the global need for cheaper separation methods and CO₂ emission reduction.

Modeling of Gas Transport through Polymer/MOF Interfaces: A Microsecond-Scale Concentration Gradient-Driven Molecular Dynamics Study

Membrane-based separation technologies offer a cost-effective alternative to many energy-intensive gas separation processes, such as distillation. Mixed matrix membranes (MMMs) composed of polymers and metal-organic frameworks (MOFs) have attracted a great deal of attention for being promising systems to manufacture durable and highly selective membranes with high gas fluxes and high selectivities. Therefore, understanding gas transport through these MMMs is of significant importance. There has been longstanding speculation that the gas diffusion behavior at the interface formed between the polymer matrix and MOF particles would strongly affect the global performance of the MMMs due to the potential presence of nonselective voids or other defects. To shed more light on this paradigm, we have performed microsecond long concentration gradient-driven molecular dynamics (CGD-MD) simulations that deliver an unprecedented microscopic picture of the transport of H₂ and CH₄ as single components and as a mixture in all regions of the PIM-1/ZIF-8 membrane, including the polymer/MOF interface. The fluxes of the permeating gases are computed and the impact of the polymer/MOF interface on the H₂/CH₄ permselectivity of the composite membrane is clearly revealed. Specifically, we show that the poor compatibility between PIM-1 and ZIF-8, which manifests itself by the presence of nonselective void spaces at their interface, results in a decrease of the H₂/CH₄ permselectivity for the corresponding composite membrane as compared to the performances simulated for PIM-1 and ZIF-8 individually. We demonstrate that CGD-MD simulations based on an accurate atomistic description of the polymer/MOF composite is a powerful tool for characterization and understanding of gas transport and separation mechanisms in MMMs.