Recent advances in simulating gas permeation through MOF membranes

Computational and Machine Learning Methods for CO2 Capture Using Metal-Organic Frameworks

Machine learning (ML) using data sets of atomic and molecular force fields (FFs) has made significant progress and provided benefits in the fields of chemistry and material science. This work examines the interactions between chemistry and materials computational science at the atomic and molecular scales for metal-organic framework (MOF) adsorbent development toward carbon dioxide (CO2) capture. Herein, a connection will be drawn between atomic forces predicted by ML algorithms and the structures of MOFs for CO2 adsorption. Our study also takes into account the successes of atomic computational screening in the field of materials science, especially quantum ML, and its relationship to ML algorithms that clarify advancements in the area of CO2 adsorption by MOFs. Additionally, we reviewed the processes for supplying data to ML algorithms for algorithm training, including text mining from scientific articles, and MOF's formula processing linked to the chemical properties of MOFs. To create ML algorithms for future research, we recommend that the digitization of scientific records can help efficiently synthesize advanced MOFs. Finally, a future vision for developing pioneer MOF synthesis routes for CO2 capture is presented in this review article.

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.

Preparation of core-shell MOF@MOF nanoparticle as matrix for the analysis of rhubarb anthraquinones in plasma by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

A core-shell structure UiO-66-(OH)₂@UiO-66-NH₂ (MOF@MOF) nanoparticle was synthesized through a simple hydrothermal method and employed as an adsorbent and laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) matrix for the quantitative analysis of rhubarb anthraquinones (RAs). The properties of the materials were characterized by field emission scanning electron microscopy, transmission electron microscopy, energy-dispersive X-ray spectroscopy, X-ray powder diffraction, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, thermogravimetric analysis, and Brunauer-Emmett-Teller. The results indicate that MOF@MOF is regular octahedral structure with a size distribution of about 100 nm, having large BET specific surface area (920 m²/g). Using the MOF@MOF as a matrix shows lower background interference, higher sensitivity, and better storage stability than that of traditional matrices. The MOF@MOF matrix exhibits excellent salt tolerance even under a NaCl concentration of 150 mM. Then, the enrichment conditions were optimized, and the adsorption time of 10 min, adsorption temperature of 40 °C and adsorbent amount of 100 μg were selected. In addition, the possible mechanism of MOF@MOF as an adsorbent and matrix was discussed. Finally, the MOF@MOF nanoparticle was employed as a matrix for the sensitive MALDI-TOF-MS analysis of RAs in spiked rabbit plasma, and the recoveries are in the range of 88.3-101.5% with RSD ≤9.9%. In short, the novel MOF@MOF matrix has demonstrated its potential in the analysis of small-molecule compounds in biological samples.

Metal-organic frameworks for high performance desalination through thickness control and structural fine-tuning

Two-dimensional nanoporous membranes hold great promise for the design of state-of-the-art desalination architectures to alleviate the increasing global water scarcity. Herein, by employing molecular dynamics simulations, we demonstrate the great potential of two recently reported metal-organic frameworks (MOF) membranes, namely NiIT and NiAT, as efficient desalination membranes that reach super high water flux and high salt rejection. The desalination performance of the MOF membrane is highly tunable through controlling the membrane thickness from one layer to five layers. Double layer NiIT membrane exhibits excellent salt rejection of 100% for NaCl, and meanwhile achieving high water permeability of ∼45 L/cm²/MPa/day. While for the convertible double-layer NiAT, it effectively rejects ∼96% ions with an improved water permeation of over 70 L/cm²/MPa/day. Quantitative analysis of water distribution reveals a denser water solvation shell around NiAT membrane than NiIT and a higher water velocity through the nanopore of NiAT than that of NiIT, contributing to the enhanced water permeability. Through calculating free energy for water/ions translocating through two membranes, a clear energy barrier is observed for ions to penetrate through the sub-nanosized pores in both membranes, leading to the high salt rejection. The present study suggests that these two MOF membranes can serve as a promising semipermeable membrane for energy-efficient desalination which is highly prospective in industrial applications.

In Silico Screening of Metal-Organic Frameworks and Zeolites for He/N2 Separation

In silico screening of 10,143 metal-organic frameworks (MOFs) and 218 all-silica zeolites for adsorption-based and membrane-based He and N₂ separation was performed. As a result of geometry-based prescreening, structures having zero accessible surface area (ASA) and pore limiting diameter (PLD) less than 3.75 Å were eliminated. So, both gases can be adsorbed and pass-through MOF and zeolite pores. The Grand canonical Monte Carlo (GCMC) and equilibrium molecular dynamics (EMD) methods were used to estimate the Henry's constants and self-diffusion coefficients at infinite dilution conditions, as well as the adsorption capacity of an equimolar mixture of helium and nitrogen at various pressures. Based on the obtained results, adsorption, diffusion and membrane selectivities as well as membrane permeabilities were calculated. The separation potential of zeolites and MOFs was evaluated in the vacuum and pressure swing adsorption processes. In the case of membrane-based separation, we focused on the screening of nitrogen-selective membranes. MOFs were demonstrated to be more efficient than zeolites for both adsorption-based and membrane-based separation. The analysis of structure-performance relationships for using these materials for adsorption-based and membrane-based separation of He and N₂ made it possible to determine the ranges of structural parameters, such as pore-limiting diameter, largest cavity diameter, surface area, porosity, accessible surface area and pore volume corresponding to the most promising MOFs for each separation model discussed in this study. The top 10 most promising MOFs were determined for membrane-based, vacuum swing adsorption and pressure swing adsorption separation methods. The effect of the electrostatic interaction between the quadrupole moment of nitrogen molecules and MOF atoms on the main adsorption and diffusion characteristics was studied. The obtained results can be used as a guide for selection of frameworks for He/N₂ separation.

Combining Machine Learning and Molecular Simulations to Unlock Gas Separation Potentials of MOF Membranes and MOF/Polymer MMMs

Due to the enormous increase in the number of metal-organic frameworks (MOFs), combining molecular simulations with machine learning (ML) would be a very useful approach for the accurate and rapid assessment of the separation performances of thousands of materials. In this work, we combined these two powerful approaches, molecular simulations and ML, to evaluate MOF membranes and MOF/polymer mixed matrix membranes (MMMs) for six different gas separations: He/H₂, He/N₂, He/CH₄, H₂/N₂, H₂/CH₄, and N₂/CH₄. Single-component gas uptakes and diffusivities were computed by grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations, respectively, and these simulation results were used to assess gas permeabilities and selectivities of MOF membranes. Physical, chemical, and energetic features of MOFs were used as descriptors, and eight different ML models were developed to predict gas adsorption and diffusion properties of MOFs. Gas permeabilities and membrane selectivities of 5249 MOFs and 31,494 MOF/polymer MMMs were predicted using these ML models. To examine the transferability of the ML models, we also focused on computer-generated, hypothetical MOFs (hMOFs) and predicted the gas permeability and selectivity of 1000 hMOF/polymer MMMs. The ML models that we developed accurately predict the uptake and diffusion properties of He, H₂, N₂, and CH₄ gases in MOFs and will significantly accelerate the assessment of separation performances of MOF membranes and MOF/polymer MMMs. These models will also be useful to direct the extensive experimental efforts and computationally demanding molecular simulations to the fabrication and analysis of membrane materials offering high performance for a target gas separation.

Recent Advances in Catalysts and Membranes for MCH Dehydrogenation: A Mini Review

Methylcyclohexane (MCH), one of the liquid organic hydrogen carriers (LOHCs), offers a convenient way to store, transport, and supply hydrogen. Some features of MCH such as its liquid state at ambient temperature and pressure, large hydrogen storage capacity, its well-known catalytic endothermic dehydrogenation reaction and ease at which its dehydrogenated counterpart (toluene) can be hydrogenated back to MCH and make it one of the serious contenders for the development of hydrogen storage and transportation system of the future. In addition to advances on catalysts for MCH dehydrogenation and inorganic membrane for selective and efficient separation of hydrogen, there are increasing research interests on catalytic membrane reactors (CMR) that combine a catalyst and hydrogen separation membrane together in a compact system for improved efficiency because of the shift of the equilibrium dehydrogenation reaction forwarded by the continuous removal of hydrogen from the reaction mixture. Development of efficient CMRs can serve as an important step toward commercially viable hydrogen production systems. The recently demonstrated commercial MCH-TOL based hydrogen storage plant, international transportation network and compact hydrogen producing plants by Chiyoda and some other companies serves as initial successful steps toward the development of full-fledged operation of manufacturing, transportation and storage of zero carbon emission hydrogen in the future. There have been initiatives by industries in the development of compact on-board dehydrogenation plants to fuel hydrogen-powered locomotives. This review mainly focuses on recent advances in different technical aspects of catalytic dehydrogenation of MCH and some significant achievements in the commercial development of MCH-TOL based hydrogen storage, transportation and supply systems, along with the challenges and future prospects.