Combined GCMC, MD, and DFT Approach for Unlocking the Performances of COFs for Methane Purification

Probing Self-Diffusion of Guest Molecules in a Covalent Organic Framework: Simulation and Experiment

Covalent organic frameworks (COFs) are a class of porous materials whose sorption properties have so far been studied primarily by physisorption. Quantifying the self-diffusion of guest molecules inside their nanometer-sized pores allows for a better understanding of confinement effects or transport limitations and is thus essential for various applications ranging from molecular separation to catalysis. Using a combination of pulsed field gradient nuclear magnetic resonance measurements and molecular dynamics simulations, we have studied the self-diffusion of acetonitrile and chloroform in the 1D pore channels of two imine-linked COFs (PI-3-COF) with different levels of crystallinity and porosity. The higher crystallinity and porosity sample exhibited anisotropic diffusion for MeCN parallel to the pore direction, with a diffusion coefficient of Dpar = 6.1(3) × 10-10 m2 s-1 at 300 K, indicating 1D transport and a 7.4-fold reduction in self-diffusion compared to the bulk liquid. This finding aligns with molecular dynamics simulations predicting 5.4-fold reduction, assuming an offset-stacked COF layer arrangement. In the low-porosity sample, more frequent diffusion barriers result in isotropic, yet significantly reduced diffusivities (DB = 1.4(1) × 10-11 m2 s-1). Diffusion coefficients for chloroform at 300 K in the pores of the high- (Dpar = 1.1(2) × 10-10 m2 s-1) and low-porosity (DB = 4.5(1) × 10-12 m2 s-1) samples reproduce these trends. Our multimodal study thus highlights the significant influence of real structure effects such as stacking faults and grain boundaries on the long-range diffusivity of molecular guest species while suggesting efficient intracrystalline transport at short diffusion times.

Rapid and Accurate Screening of the COF Space for Natural Gas Purification: COFInformatics

In this work, we introduced COFInformatics, a computational approach merging molecular simulations and machine learning (ML) algorithms, to evaluate all synthesized and hypothetical covalent organic frameworks (COFs) for the CO2/CH4 mixture separation under four different adsorption-based processes: pressure swing adsorption (PSA), vacuum swing adsorption (VSA), temperature swing adsorption (TSA), and pressure-temperature swing adsorption (PTSA). We first extracted structural, chemical, energy-based, and graph-based molecular fingerprint features of every single COF structure in the very large COF space, consisting of nearly 70,000 materials, and then performed grand canonical Monte Carlo simulations to calculate the CO2/CH4 mixture adsorption properties of 7540 COFs. These features and simulation results were used to develop ML models that accurately and rapidly predict CO2/CH4 mixture adsorption and separation properties of all 68,614 COFs. The most efficient separation process and the best adsorbent candidates among the entire COF spectrum were identified and analyzed in detail to reveal the most important molecular features that lead to high-performance adsorbents. Our results showed that (i) many hypoCOFs outperform synthesized COFs by achieving higher CO2/CH4 selectivities; (ii) the top COF adsorbents consist of narrow pores and linkers comprising aromatic, triazine, and halogen groups; and (iii) PTSA is the most efficient process to use COF adsorbents for natural gas purification. We believe that COFInformatics promises to expedite the evaluation of COF adsorbents for CO2/CH4 separation, thereby circumventing the extensive, time- and resource-intensive molecular simulations.

Effect of interlayer slipping on the geometric, thermal and adsorption properties of 2D covalent organic frameworks: a comprehensive review based on computational modelling studies

Two-dimensional covalent organic frameworks (2D-COFs) are a class of crystalline porous organic polymers, consisting of 2D-planar sheets stacked together perpendicularly via noncovalent forces. Since their discovery, 2D-COFs have attracted extensive attention for optoelectronic and adsorption applications. Owing to the layer stacking nature of 2D COFs, various new slipped structures that are energetically favourable can be designed. These interlayer slipped structures are actively responsible for tuning (mostly enhancing) the optoelectronic properties, thermal properties, and mechanical strength of 2D COFs. This review summarizes the effect of interlayer slipping on the energetic stability, electronic behaviour and gas adsorption properties of 2D layered COFs, which is explained through computational modelling simulations. Since computational modelling offers a deep insight into electronic behaviour at the atomic scale, which is potentially impossible through experimental techniques, the introduction and role of computational techniques in such studies have also been described.

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.

Silicone oils aided fabrication of paraffin wax coated super-hydrophobic sand: A spectroscopic study

To address the global alarm of desertification and boost plant progress in arid and desert environments, super-hydrophobic sand has been suggested and fabricated in numerous researches. In the present work, sand was hydrophobized by coating with a mixture of paraffin wax and silicone oils. The contact angle (CA) of sand with 4.5 w% silicone oils increased from 143.2° to 154.2° with decreasing the chain size of silicone oil, and the further addition of 13.5 w% of paraffin wax produced a super hydrophobic sand with a CA value up to 160° comparing to 154.2° without added paraffin wax. The Fourier Transform Infrared spectra suggested the development of inter molecular forces between silicone oil and sand as well as between paraffin and silicone oil, the driving force of which was the variation in viscosity of silicone oils. The later was higher in the case of lower molecular weight silicone oil. In particular, analyzing the characteristic bands of -(CH2)n-in paraffin wax, i.e. the corresponding bands at 720, 730, 1460 and 1470 cm-1 and the two bands at 1020 and 1095 cm-1 of silicone oil revealed that two roles of paraffin were taking place. While paraffin was placed between sand and silicone oil, it coated the sand particles when lower molecular weight silicone oil was used in the first procedures, whereas it coated the higher molecular weight silicone oil in the second procedures. Molecular dynamic calculation has been performed and confirmed the previous reached conclusions and showed that paraffin molecules were encapsulated in a silicone oil shell. The average adsorption energy of paraffin and silicon oil molecules on sand particles were 29.5 and 38.9 kcal mol-1 respectively.

Advancing CH4/H2 separation with covalent organic frameworks by combining molecular simulations and machine learning

A high-throughput computational screening approach combined with machine learning (ML) was introduced to unlock the potential of both synthesized and hypothetical COFs (hypoCOFs) for adsorption-based CH₄/H₂ separation. We studied 597 synthesized COFs for adsorption of a CH₄/H₂ mixture using Grand Canonical Monte Carlo (GCMC) simulations under pressure-swing adsorption (PSA) and vacuum-swing adsorption (VSA) conditions. Based on the simulation results, the CH₄/H₂ selectivities, CH₄ working capacities, adsorbent performance scores, and regenerabilities of the synthesized COFs were assessed and the structural properties of the top-performing COFs were identified. The hypoCOF database composed of 69 840 materials was then filtered to identify 7737 hypothetical materials having similar structural properties to the top synthesized COFs. These hypothetical COFs were then examined for CH₄/H₂ separation using molecular simulations and the results showed that the top hypoCOFs have CH₄ selectivities and working capacities in the ranges of 21.9-28.7 (64.7-128.6) and 5.8-7.6 (1.3-3.1) mol kg^-1 under PSA (VSA) conditions, respectively, outperforming the synthesized COFs and metal-organic frameworks (MOFs). ML models were then developed based on the hypoCOF simulation results to accurately predict the CH₄/H₂ mixture adsorption properties of all remaining hypothetical materials when their structural and chemical properties are fed into the models. These models accurately assessed the CH₄/H₂ mixture separation performances of any hypoCOF within seconds without performing computationally demanding molecular simulations. The computational approach that we have proposed in this study will provide an accurate and efficient assessment of COF materials for CH₄/H₂ separation and significantly accelerate the experimental efforts towards the design and discovery of new high-performing COF adsorbents.

Advanced Polymeric Nanocomposite Membranes for Water and Wastewater Treatment: A Comprehensive Review

Nanomaterials have been extensively used in polymer nanocomposite membranes due to the inclusion of unique features that enhance water and wastewater treatment performance. Compared to the pristine membranes, the incorporation of nanomodifiers not only improves membrane performance (water permeability, salt rejection, contaminant removal, selectivity), but also the intrinsic properties (hydrophilicity, porosity, antifouling properties, antimicrobial properties, mechanical, thermal, and chemical stability) of these membranes. This review focuses on applications of different types of nanomaterials: zero-dimensional (metal/metal oxide nanoparticles), one-dimensional (carbon nanotubes), two-dimensional (graphene and associated structures), and three-dimensional (zeolites and associated frameworks) nanomaterials combined with polymers towards novel polymeric nanocomposites for water and wastewater treatment applications. This review will show that combinations of nanomaterials and polymers impart enhanced features into the pristine membrane; however, the underlying issues associated with the modification processes and environmental impact of these membranes are less obvious. This review also highlights the utility of computational methods toward understanding the structural and functional properties of the membranes. Here, we highlight the fabrication methods, advantages, challenges, environmental impact, and future scope of these advanced polymeric nanocomposite membrane based systems for water and wastewater treatment 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.

High-Throughput Screening of COF Membranes and COF/Polymer MMMs for Helium Separation and Hydrogen Purification

Hundreds of covalent organic frameworks (COFs) have been synthesized, and thousands of them have been computationally designed. However, it is impractical to experimentally test each material as a membrane for gas separations. In this work, we focused on the membrane-based gas separation performances of experimentally synthesized COFs and hypothetical COFs (hypoCOFs). Gas permeabilities of COFs were computed by combining the results of grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations, and many COF membranes were found to overcome the upper bound of polymeric membranes for He/H₂, N₂/CH₄, H₂/N₂, He/CH₄, H₂/CH₄, and He/N₂ separations. We then examined the structure-permeability relations of the COF membranes that are above the upper bound for each of the six gas separations, and based on these relations, we proposed an efficient approach for the selection of the best hypoCOFs from a very large database. Molecular simulations showed that 120 hypoCOFs that we identified to be promising based on these structure-performance relations exceed the upper bound for He/CH₄, He/N₂, H₂/CH₄, and H₂/N₂ separations. Both real and hypothetical COFs were then studied as fillers in 25 different polymers, leading to a total of 29 020 COF/polymer and hypoCOF/polymer mixed matrix membranes (MMMs), representing the largest number of COF-based MMMs investigated to date. Permeabilities and selectivities of COF/polymer MMMs were computed for six different gas separations, and results revealed that 18 of the 25 polymers can be carried above the upper bound when COFs were used as fillers. The comprehensive analysis of COFs provided in this work will fully unlock the potential of COF membranes and COF/polymer MMMs for helium separation and hydrogen purification.