Adsorption- and Membrane-Based CH4/N2 Separation Performances of MOFs

Evaluating CH4/N2 Separation Performances of Hundreds of Thousands of Real and Hypothetical MOFs by Harnessing Molecular Modeling and Machine Learning

Considering the large abundance and diversity of metal-organic frameworks (MOFs), evaluating the gas adsorption and separation performance of the entire MOF material space using solely experimental techniques or brute-force computer simulations is impractical. In this study, we integrated high-throughput molecular simulations with machine learning (ML) to explore the potential of both synthesized, the real MOFs, and computer-generated, the hypothetical MOFs (hypoMOFs), for adsorption-based CH4/N2 separation. CH4/N2 mixture adsorption data obtained from molecular simulations were used to train the ML models that could accurately predict gas uptakes of 4612 real MOFs. These models were then transferred to two distinct databases consisting of 98 601 hypoMOFs and 587 anion-pillared hypoMOFs to examine their CH4/N2 mixture separation performances using various adsorbent evaluation metrics. The top adsorbents were identified for vacuum swing adsorption (VSA) and pressure swing adsorption (PSA) conditions and examined in detail to gain molecular insights into their structural and chemical properties. Results revealed that the hypoMOFs offered high CH4 selectivities, up to 14.8 and 13.6, and high working capacities, up to 3.1 and 5.8 mol/kg, at VSA and PSA conditions, respectively, and many of the hypoMOFs could outperform the real MOFs. Our approach offers a rapid and accurate assessment of the mixture adsorption and separation properties of MOFs without the need for computationally demanding simulations. Our results for the best adsorbents will be useful in accelerating the experimental efforts for the design of novel MOFs that can achieve high-performance CH4/N2 separation.

Microporous Adsorbents for CH4 Capture and Separation from Coalbed Methane with Low CH4 Concentration: Review

A rapid increase in natural gas consumption has resulted in a shortage of conventional natural gas resources, while an increasing concentration of CH4 in the atmosphere has intensified the greenhouse effect. The exploration and utilization of coalbed methane (CBM) resources not only has the potential to fill the gap in natural gas supply and promote the development of green energy, but could also reduce CH4 emissions into the atmosphere and alleviate global warming. However, the efficient separation of CH4 and N2 has become a significant challenge in the utilization of CBM, which has attracted significant attention from researchers in recent years. The development of efficient CH4/N2 separation technologies is crucial for enhancing the exploitation and utilization of low-concentration CBM and is of great significance for sustainable development. In this paper, we provide an overview of the current methods for CH4/N2 separation, summarizing their respective advantages and limitations. Subsequently, we focus on reviewing research advancements in adsorbents for CH4/N2 separation, including zeolites, metal-organic frameworks (MOFs), and porous carbon materials. We also analyze the relationship between the pore structure and surface properties of these adsorbents and their adsorption separation performances, and summarize the challenges and difficulties that different types of adsorbents face in their future development. In addition, we also highlight that matching the properties of adsorbents and adsorbates, controlling pore structures, and tuning surface properties on an atomic scale will significantly increase the potential of adsorbents for CH4 capture and separation from CBM.

Two-Dimensional Nanoporous Cross-linked Polymer Networks as Emerging Candidates for Gas Adsorption

This paper illustrates the gas adsorption properties of newly synthesized nanoporous cross-linked polymer networks (CPNs). All synthesized CPNs possess N-rich functional groups and are used for the utilization of carbon dioxide and methane. Good gas adsorption and selectivities are obtained for all of the samples. Among the materials, HEREON2 outperforms better selectivity for methane separation from nitrogen rather than zeolites, activated carbons, molecular sieves, covalent organic frameworks, and metal-organic frameworks (MOFs). The accessibility of the N-rich functionalities makes these materials potential candidates for the separation of hydrocarbons via increased polarizabilities. High-pressure adsorption experiments showed that the synthesized two-dimensional nanoporous materials also have a high affinity toward carbon dioxide. HEREON2 powders showed an increased experimental CO2/N2 selectivity of ∼25,000 at 50 bar due to the presence of nitrogen groups in the structure. Fourier-transform infrared spectroscopy (FTIR), solid-state NMR, X-ray diffraction, thermogravimetric analysis, energy-dispersive X-ray spectroscopy (EDX), transmission electron microscopy (TEM), and scanning electron microscopy (SEM) were applied for the characterization of the synthesized nanoporous CPNs. The results show a potential new pathway for future CPN membrane development.

High-throughput computational screening of MOF adsorbents for efficient propane capture from air and natural gas mixtures

In this study, we used a high-throughput computational screening approach to examine the potential of metal-organic frameworks (MOFs) for capturing propane (C3H8) from different gas mixtures. We focused on Quantum MOF (QMOF) database composed of both synthesized and hypothetical MOFs and performed Grand Canonical Monte Carlo (GCMC) simulations to compute C3H8/N2/O2/Ar and C3H8/C2H6/CH4 mixture adsorption properties of MOFs. The separation of C3H8 from air mixture and the simultaneous separation of C3H8 and C2H6 from CH4 were studied for six different adsorption-based processes at various temperatures and pressures, including vacuum-swing adsorption (VSA), pressure-swing adsorption (PSA), vacuum-temperature swing adsorption (VTSA), and pressure-temperature swing adsorption (PTSA). The results of molecular simulations were used to evaluate the MOF adsorbents and the type of separation processes based on selectivity, working capacity, adsorbent performance score, and regenerability. Our results showed that VTSA is the most effective process since many MOFs offer high regenerability (>90%) combined with high C3H8 selectivity (>7 × 103) and high C2H6 + C3H8 selectivity (>100) for C3H8 capture from air and natural gas mixtures, respectively. Analysis of the top MOFs revealed that materials with narrow pores (<10 Å) and low porosities (<0.7), having aromatic ring linkers, alumina or zinc metal nodes, typically exhibit a superior C3H8 separation performance. The top MOFs were shown to outperform commercial zeolite, MFI for C3H8 capture from air, and several well-known MOFs for C3H8 capture from natural gas stream. These results will direct the experimental efforts to the most efficient C3H8 capture processes by providing key molecular insights into selecting the most useful adsorbents.

Non-CO2 greenhouse gas separation using advanced porous materials

Global warming has become a growing concern over decades, prompting numerous research endeavours to reduce the carbon dioxide (CO2) emission, the major greenhouse gas (GHG). However, the contribution of other non-CO2 GHGs including methane (CH4), nitrous oxide (N2O), fluorocarbons, perfluorinated gases, etc. should not be overlooked, due to their high global warming potential and environmental hazards. In order to reduce the emission of non-CO2 GHGs, advanced separation technologies with high efficiency and low energy consumption such as adsorptive separation or membrane separation are highly desirable. Advanced porous materials (APMs) including metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs), porous organic polymers (POPs), etc. have been developed to boost the adsorptive and membrane separation, due to their tunable pore structure and surface functionality. This review summarizes the progress of APM adsorbents and membranes for non-CO2 GHG separation. The material design and fabrication strategies, along with the molecular-level separation mechanisms are discussed. Besides, the state-of-the-art separation performance and challenges of various APM materials towards each type of non-CO2 GHG are analyzed, offering insightful guidance for future research. Moreover, practical industrial challenges and opportunities from the aspect of engineering are also discussed, to facilitate the industrial implementation of APMs for non-CO2 GHG separation.

MOF-GRU: A MOFid-Aided Deep Learning Model for Predicting the Gas Separation Performance of Metal-Organic Frameworks

The remarkable versatility of metal-organic frameworks (MOFs) stems from their rich chemical information, leading to numerous successful applications. However, identifying optimal MOFs for specific tasks necessitates a thorough assessment of their chemical attributes. Conventional machine learning approaches for MOF prediction have relied on intricate chemical and structural details, hampering rapid evaluations. Drawing inspiration from recent advancements exemplified by Snurr et al., wherein a text string was used to represent a MOF (MOFid), we introduce a MOFid-aided deep learning model, named the MOF-GRU model. This model, founded on natural language processing principles and utilizing the gated recurrent unit architecture, leverages the serialized text string representation of metal-organic frameworks (MOFs) to forecast gas separation performance. Through a focused study on CH4/N2 separation, we substantiate the efficacy of this approach. Comparative assessments against traditional machine learning techniques underscore our model's superior predictive accuracy and its capacity to handle extensive data sets adeptly. The MOF-GRU model remarkably uncovers latent structure-performance relationships with only MOF sequences, obviating the necessity for intricate three-dimensional (3D) structural information. Overall, this model's judicious design empowers efficient data utilization, thereby hastening the discovery of high-performance materials tailored for gas separation applications.

Computational Investigation of Dual Filler-Incorporated Polymer Membranes for Efficient CO2 and H2 Separation: MOF/COF/Polymer Mixed Matrix Membranes

Mixed matrix membranes (MMMs) composed of two different fillers such as metal-organic frameworks (MOFs) and covalent-organic frameworks (COFs) embedded into polymers provide enhanced gas separation performance. Since it is not possible to experimentally consider all possible combinations of MOFs, COFs, and polymers, developing computational methods is urgent to identify the best performing MOF-COF pairs to be used as dual fillers in polymer membranes for target gas separations. With this motivation, we combined molecular simulations of gas adsorption and diffusion in MOFs and COFs with theoretical permeation models to calculate H2, N2, CH4, and CO2 permeabilities of almost a million types of MOF/COF/polymer MMMs. We focused on COF/polymer MMMs located below the upper bound due to their low gas selectivity for five industrially important gas separations, CO2/N2, CO2/CH4, H2/N2, H2/CH4, and H2/CO2. We further investigated whether these MMMs could exceed the upper bound when a second type of filler, a MOF, was introduced into the polymer. Many MOF/COF/polymer MMMs were found to exceed the upper bounds showing the promise of using two different fillers in polymers. Results showed that for polymers having a relatively high gas permeability (≥104 barrer) but low selectivity (≤2.5) such as PTMSP, addition of the MOF as the second filler can have a dramatic effect on the final gas permeability and selectivity of the MMM. Property-performance relations were analyzed to understand how the structural and chemical properties of the fillers affect the permeability of the resulting MMMs, and MOFs having Zn, Cu, and Cd metals were found to lead to the highest increase in gas permeability of MMMs. This work highlights the significant potential of using COF and MOF fillers in MMMs to achieve better gas separation performances than MMMs with one type of filler, especially for H2 purification and CO2 capture applications.

Computational investigation of multifunctional MOFs for adsorption and membrane-based separation of CF4/CH4, CH4/H2, CH4/N2, and N2/H2 mixtures

The ease of functionalization of metal-organic frameworks (MOFs) can unlock unprecedented opportunities for gas adsorption and separation applications as the functional groups can impart favorable/unfavorable regions/interactions for the desired/undesired adsorbates. In this study, the effects of the presence of multiple functional groups in MOFs on their CF₄/CH₄, CH₄/H₂, CH₄/N₂, and N₂/H₂ separation performances were computationally investigated combining grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations. The most promising adsorbents showing the best combinations of selectivity, working capacity, and regenerability were identified for each gas separation. 15, 13, and 16 out of the top 20 MOFs identified for the CH₄/H₂, CH₄/N₂, and N₂/H₂ adsorption-based separation, respectively, were found to have -OCH₃ groups as one of the functional groups. The biggest improvements in CF₄/CH₄, CH₄/H₂, CH₄/N₂, and N₂/H₂ selectivities were found to be induced by the presence of -OCH₃-OCH₃ groups in MOFs. For CH₄/H₂ separation, MOFs with two and three functionalized linkers were the best adsorbent candidates while for N₂/H₂ separation, all the top 20 materials involve two functional groups. Membrane performances of the MOFs were also studied for CH₄/H₂ and CH₄/N₂ separation and the results showed that MOFs having -F-NH₂ and -F-OCH₃ functional groups present the highest separation performances considering both the membrane selectivity and permeability.

Combining Computational Screening and Machine Learning to Predict Metal-Organic Framework Adsorbents and Membranes for Removing CH4 or H2 from Air

Separating and capturing small amounts of CH4 or H2 from a mixture of gases, such as coal mine spent air, at a large scale remains a great challenge. We used large-scale computational screening and machine learning (ML) to simulate and explore the adsorption, diffusion, and permeation properties of 6013 computation-ready experimental metal-organic framework (MOF) adsorbents and MOF membranes (MOFMs) for capturing clean energy gases (CH4 and H2) in air. First, we modeled the relationships between the adsorption and the MOF membrane performance indicators and their characteristic descriptors. Among three ML algorithms, the random forest was found to have the best prediction efficiency for two systems (CH4/(O2 + N2) and H2/(O2 + N2)). Then, the algorithm was further applied to quantitatively analyze the relative importance values of seven MOF descriptors for five performance metrics of the two systems. Furthermore, the 20 best MOFs were also selected. Finally, the commonalities between the high-performance MOFs were analyzed, leading to three types of material design principles: tuned topology, alternative metal nodes, and organic linkers. As a result, this study provides microscopic insights into the capture of trace amounts of CH4 or H2 from air for applications involving coal mine spent air and hydrogen leakage.

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.

Zr-MOFs for CF4/CH4, CH4/H2, and CH4/N2 separation: towards the goal of discovering stable and effective adsorbents

Zirconium metal-organic frameworks (MOFs) can be promising adsorbents for various applications as they are highly stable in different chemical environments. In this work, a collection of Zr-MOFs comprised of more than 100 materials is screened for CF₄/CH₄, CH₄/H₂, and CH₄/N₂ separations using atomistic-level simulations. The top three MOFs for the CF₄/CH₄ separation are identified as PCN-700-BPDC-TPDC, LIFM-90, and BUT-67 exhibiting CF₄/CH₄ adsorption selectivities of 4.8, 4.6, and 4.7, CF₄ working capacities of 2.0, 2.0, and 2.1 mol kg^-1, and regenerabilities of 85.1, 84.2, and 75.7%, respectively. For the CH₄/H₂ separation, MOF-812, BUT-67, and BUT-66 are determined to be the top performing MOFs demonstrating CH₄/H₂ selectivities of 61.6, 36.7, and 46.2, CH₄ working capacities of 3.0, 4.1, and 3.4 mol kg^-1, and CH₄ regenerabilities of 70.7, 82.7, and 74.7%, respectively. Regarding the CH₄/N₂ separation, BUT-67, Zr-AbBA, and PCN-702 achieving CH₄/N₂ selectivities of 4.5, 3.4, and 3.8, CH₄ working capacities of 3.6, 3.9, and 3.5 mol kg^-1, and CH₄ regenerabilities of 81.1, 84.0, and 84.5%, in successive order, show the best overall separation performances. To further elucidate the adsorption in top performing adsorbents, the adsorption sites in these materials are analyzed using radial distribution functions and adsorbate density profiles. Finally, the water affinities of Zr-MOFs are explored to comment on their practical use in real gas separation applications. Our findings may inspire future studies probing the adsorption/separation mechanisms and performances of Zr-MOFs for different gases.

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.

Chiral Metal-Organic Framework d-His-ZIF-8@SiO2 Core-Shell Microspheres Used for HPLC Enantioseparations

Chiral metal-organic frameworks (MOFs) have aroused great attention in the chiral separation field based on their excellent characteristics, including abundant topological structures, large surface area, adjustable pore/channel sizes, multiple active sites, and good chemical stability. However, the irregular morphology and nonuniformity of the synthesized MOF particles cause low column efficiency and high column backpressure for MOF-packed columns, which significantly affects their separation performance. Herein, we prepared a homochiral d-his-ZIF-8@SiO₂ composite by growing of d-his-ZIF-8 on the carboxylic-functionalized SiO₂ microspheres via a simple one-pot synthesis approach. The d-his-ZIF-8@SiO₂ core-shell microspheres with uniform particles and narrow size distribution were applied as the chiral stationary phase (CSP) for enantioseparations in HPLC. Various racemates were separated on the d-his-ZIF-8@SiO₂-packed columns with n-hexane/isopropanol as the mobile phase. Eighteen racemates including alcohol, phenol, amine, ketone, and organic acid were well resolved on the homochiral d-his-ZIF-8@SiO₂ CSP. The d-his-ZIF-8@SiO₂ core-shell microspheres' CSP possesses an excellent chiral resolution ability toward various racemic compounds with good reproducibility and stability. Hence, the fabrication of chiral MOF@SiO₂ core-shell microspheres is an effective strategy to improve the application of homochiral MOFs as CSPs in the field of chromatography.

Preparation and characterization of metal–organic frameworks and their composite Eu2O3@[Zn2(bdc)2dabco] (ZBDh) via pulsed laser ablation in a flowing liquid

The nanocomposites Eu₂O₃@[Zn₂(bdc)₂dabco] (ZBDh) synthesized by PLA in a flowing liquid can be used for the detection of methanol in fluorescence sensing.

Metal Organic Framework Based Polymer Mixed Matrix Membranes: Review on Applications in Water Purification

Polymeric membranes have been widely employed for water purification applications. However, the trade-off issue between the selectivity and permeability has limited its use in various applications. Mixed matrix membranes (MMMs) were introduced to overcome this limitation and to enhance the properties and performance of polymeric membranes by incorporation of fillers such as silica and zeolites. Metal-organic frameworks (MOFs) are a new class of hybrid inorganic-organic materials that are introduced as novel fillers for incorporation in polymeric matrix to form composite membranes for different applications especially water desalination. A major advantage of MOFs over other inorganic fillers is the possibility of preparing different structures with different pore sizes and functionalities, which are designed especially for a targeted application. Different MMMs fabrication techniques have also been investigated to fabricate MMMs with pronounced properties for a specific application. Synthesis techniques include blending, layer-by-layer (LBL), gelatin-assisted seed growth and in situ growth that proved to give the most homogenous dispersion of MOFs within the organic matrix. It was found that the ideal filler loading of MOFs in different polymeric matrices is 10%, increasing the filler loading beyond this value led to formation of aggregates that significantly decreased the MOFs-MMMs performance. Despite the many merits of MOFs-MMMs, the main challenge facing the upscaling and wide commercial application of MOFs-MMMs is the difficult synthesis conditions of the MOFs itself and the stability and sustainability of MOFs-MMMs performance. Investigation of new MOFs and MOFs-MMMs synthesis techniques should be carried out for further industrial applications. Among these new synthesis methods, green MOFs synthesis has been highlighted as low cost, renewable, environmentally friendly and recyclable starting materials for MOFs-MMMs. This paper will focus on the investigation of the effect of different recently introduced MOFs on the performance of MOFs-MMMs in water purification applications.

Large-Scale Computational Screening of Metal Organic Framework (MOF) Membranes and MOF-Based Polymer Membranes for H2/N2 Separations

Several thousands of metal organic frameworks (MOFs) have been reported to date, but the information on H₂/N₂ separation performances of MOF membranes is currently very limited in the literature. We report the first large-scale computational screening study that combines state-of-the-art molecular simulations, grand canonical Monte Carlo (GCMC) and molecular dynamics (MD), to predict H₂ permeability and H₂/N₂ selectivity of 3765 different types of MOF membranes. Results showed that MOF membranes offer very high H₂ permeabilities, 2.5 × 10³ to 1.7 × 10⁶ Barrer, and moderate H₂/N₂ membrane selectivities up to 7. The top 20 MOF membranes that exceed the polymeric membranes' upper bound for H₂/N₂ separation were identified based on the results of initial screening performed at infinite dilution condition. Molecular simulations were then carried out considering binary H₂/N₂ and quaternary H₂/N₂/CO₂/CO mixtures to evaluate the separation performance of MOF membranes under industrial operating conditions. Lower H₂ permeabilities and higher N₂ permeabilities were obtained at binary mixture conditions compared to the ones obtained at infinite dilution due to the absence of multicomponent mixture effects in the latter. Structure-performance relations of MOFs were also explored to provide molecular-level insights into the development of new MOF membranes that can offer both high H₂ permeability and high H₂/N₂ selectivity. Results showed that the most promising MOF membranes generally have large pore sizes (>6 Å) as well as high surface areas (>3500 m²/g) and high pore volumes (>1 cm³/g). We finally examined H₂/N₂ separation potentials of the mixed matrix membranes (MMMs) in which the best MOF materials identified from our high-throughput screening were used as fillers in various polymers. Results showed that incorporation of MOFs into polymers almost doubles H₂ permeabilities and slightly enhances H₂/N₂ selectivities of polymer membranes, which can advance the current membrane technology for efficient H₂ purification.

Selective Adsorption of CH₄/N₂ on Ni-based MOF/SBA-15 Composite Materials

Spherical SBA-15-based metal–organic framework (MOF) composite materials were prepared, with nickel as the metal center of MOFs. The materials were characterized via scanning electron microscopy, X-ray fluorescence analysis, X-ray powder diffraction, Fourier-transform infrared spectroscopy, and nitrogen (N₂) adsorption–desorption. The methane (CH₄) or N₂ high-pressure adsorption isotherms of the samples were measured and compared. The specific surface area and adsorption capacity of the composite materials were generally higher than the pristine MOFs, but were much lower than the synthesized SBA-15. The selectivity of the samples toward a binary gas mixture was determined from the Langmuir adsorption equation. The results revealed that, of all the samples, the MOF-2/SBA-15 sample had the best CH₄/N₂ adsorption selectivity, with an adsorption selection parameter (S) of 11.1. However, the adsorption of MOF-2/SBA-15 was less than that of spherical SBA-15, due to partial plugging of the pores during the synthesis process. Further research is essential for improving the performance of spherical SBA-15-based MOF materials and (in turn) the enrichment of CH₄ from the CH₄/N₂ mixture.