Recent advances, opportunities, and challenges in high-throughput computational screening of MOFs for gas separations

PoreMatMod.jl: Julia Package for in Silico Postsynthetic Modification of Crystal Structure Models

PoreMatMod.jl is a free, open-source, user-friendly, and documented Julia package for modifying crystal structure models of porous materials such as metal-organic frameworks (MOFs). PoreMatMod.jl functions as a find-and-replace algorithm on crystal structures by leveraging (i) Ullmann's algorithm to search for subgraphs of the crystal structure graph that are isomorphic to the graph of a query fragment and (ii) the orthogonal Procrustes algorithm to align a replacement fragment with a targeted substructure of the crystal structure for installation. The prominent application of PoreMatMod.jl is to generate libraries of hypothetical structures for virtual screenings. For example, one can install functional groups on the linkers of a parent MOF, mimicking postsynthetic modification. Other applications of PoreMatMod.jl to modify crystal structure models include introducing defects with precision and correcting artifacts of X-ray structure determination (adding missing hydrogen atoms, resolving disorder, and removing guest molecules). The find-and-replace operations implemented by PoreMatMod.jl can be applied broadly to diverse atomistic systems for various in silico structural modification tasks.

Thermodynamic exploration of xenon/krypton separation based on a high-throughput screening

Nanoporous framework materials are a promising class of materials for energy-efficient technology of xenon/krypton separation by physisorption. Many studies on Xe/Kr separation by adsorption have focused on the determination of structure/property relationships, the description of theoretical limits of performance, and the identification of top-performing materials. Here, we provide a study based on a high-throughput screening of the adsorption of Xe, Kr, and Xe/Kr mixtures in 12 020 experimental MOF materials, to provide a better comprehension of the thermodynamics behind Xe/Kr separation in nanoporous materials and the microscopic origins of Xe/Kr selectivity at both low and ambient pressure.

High-throughput virtual screening for organic electronics: a comparative study of alternative strategies

We present a review of the field of high-throughput virtual screening for organic electronics materials focusing on the sequence of methodological choices that determine each virtual screening protocol. These choices are present in all high-throughput virtual screenings and addressing them systematically will lead to optimised workflows and improve their applicability. We consider the range of properties that can be computed and illustrate how their accuracy can be determined depending on the quality and size of the experimental datasets. The approaches to generate candidates for virtual screening are also extremely varied and their relative strengths and weaknesses are discussed. The analysis of high-throughput virtual screening is almost never limited to the identification of top candidates and often new patterns and structure-property relations are the most interesting findings of such searches. The review reveals a very dynamic field constantly adapting to match an evolving landscape of applications, methodologies and datasets.

Gas adsorption and separation in metal-organic frameworks by PC-SAFT based density functional theory

In this work, we examine the theoretical performance of perturbed-chain statistical associating fluid theory based density functional theory (DFT) in predicting gas adsorption and separation in metal-organic frameworks by using simulation and experimental data as the benchmark. Adsorption isotherms of methane and ethane in pure gas and mixtures and selectivities for ethane/methane mixtures are calculated. The predicted isotherms by DFT are in excellent agreement with simulation and experimental data for pure methane and ethane, whereas for the mixture, DFT is in semi-quantitative accordance with simulation results. For fast and high-throughput screening of material purpose, three algorithms including Picard iteration with line search, Anderson mixing, and Picard-Anderson-hybrid algorithm are proposed to calculate the three dimensional density distribution of confined gases. The advantages and limitations of the three algorithms under various conditions are discussed.

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

Covalent organic frameworks (COFs) are promising materials for gas storage and separation; however, the potential of COFs for separation of CH₄ from industrially relevant gases such as H₂, N₂, and C₂H₆ is yet to be investigated. In this work, we followed a multiscale computational approach to unlock both the adsorption- and membrane-based CH₄/H₂, CH₄/N₂, and C₂H₆/CH₄ separation potentials of 572 COFs by combining grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations and density functional theory (DFT) calculations. Adsorbent performance evaluation metrics of COFs, adsorption selectivity, working capacity, regenerability, and adsorbent performance score were calculated for separation of equimolar CH₄/H₂, CH₄/N₂, and C₂H₆/CH₄ mixtures at vacuum swing adsorption (VSA) and pressure swing adsorption (PSA) conditions to identify the best-performing COFs for each mixture. Results showed that COFs could achieve selectivities of 2-85, 1-7, and 2-23 for PSA-based CH₄/H₂, CH₄/N₂, and C₂H₆/CH₄ separations, respectively, outperforming conventional adsorbents such as zeolites and activated carbons for each mixture. Structure-performance relations revealed that COFs with pore sizes <10 Å are promising adsorbents for all mixtures. We identified the gas adsorption sites in the three top-performing COFs commonly identified for each mixture by DFT calculations and computed the binding strength of gases, which were found to be on the order of C₂H₆ > CH₄ > N₂ > H₂, supporting the GCMC results. Nucleus-independent chemical shift (NICS) indexes of aromaticity for adsorption sites were calculated, and the results revealed that the degree of linker aromaticity could be a measure for the selection or design of highly alkane-selective COF adsorbents over N₂ and H₂. Finally, COF membranes were shown to achieve high H₂ permeabilities, 4.57 × 10³ -1.25 × 10⁶ Barrer, and decent membrane selectivities, as high as 4.3, outperforming polymeric and MOF-based membranes for separation of H₂ from CH₄.

Separation and Purification of Hydrocarbons with Porous Materials

This Minireview focuses on the developments of the adsorptive separation of methane/nitrogen, ethene/ethane, propene/propane mixtures as well as on the separation of C8 aromatics (i.e. xylene isomers) with a wide variety of materials, including carbonaceous materials, zeolites, metal-organic frameworks, and porous organic frameworks. Some recent important developments for these adsorptive separations are also highlighted. The advantages and disadvantages of each material category are discussed and guidelines for the design of improved materials are proposed. Furthermore, challenges and future developments of each material type and separation processes are discussed.

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.

Synergistic Effect of Active Sites and a Multiple-Micropore System for a Metal-Organic Framework Exhibiting High Separation of CO2/CH4 and C2H2/CH4

Efficient gas separation and purification play a vital role in the current advanced development of industry, and the application of MOF adsorbents in this area with highly technical materials shows obvious advantages. On the basis of reticular chemistry, the 4-c lvt MOF adsorbent [CuDTTA]·3DMF·CH₃CN has been constructed (CuDTTA; H₂DTTA = 2,5-bis(1H-1,2,4-triazol-1-yl)terephthalic acid). CuDTTA reveals a multiple-micropore system and high-density active sites decorated on the channel surfaces, which are conducive to its extraordinary selectivity of CO₂/CH₄ and C₂H₂/CH₄ (29 and 166, 1:1). In combination with an analysis of Q_st values, CuDTTA possesses the synergistic effect of size sieving and abundant functional sites, significantly improving the gas adsorption and separation performance. Meanwhile, the results also reveal that functional sites have a stronger binding affinity toward C₂H₂ with respect to CO₂. Such a conclusion renders CuDTTA to be a promising adsorbent material for industrial applications.

Metal Exchange Boosts the CO2 Selectivity of Metal Organic Frameworks Having Zn-Oxide Nodes

A large number of metal organic frameworks (MOFs) synthesized to date have nodes with a Zn metal, and a detailed understanding of their gas separation efficiency upon metal exchange is needed to pave the way for designing the next generation of MOFs. In this work, we implemented a protocol to identify MOFs with Zn nodes out of 10,221 MOFs and classified them into two main groups. Depending on the pore properties and adsorption selectivities, two MOFs from IRMOFs and two MOFs from ZnO-MOFs were selected. The metal atom (Zn) of the selected four MOFs was exchanged with eight different metals (Cd, Co, Cr, Cu, Mn, Ni, Ti, and V), and 32 different metal-exchanged MOFs (M-MOFs) were obtained. By performing grand canonical Monte Carlo simulations, we investigated the influence of the metal type on the CO2/H2 and CO2/CH4 separation performances of these 32 M-MOFs. Physical properties of the MOFs such as the pore size and surface area, and chemical properties such as the partial charges of the atoms in the framework were investigated to understand the effect of metal exchange on the gas adsorption and separation performances of materials. Exchange of Zn with V and Cr led to a remarkable increase in the CO2 uptakes of selected MOFs and these increases were reflected on the adsorption selectivity, working capacity, and the adsorbent performance score of MOFs. The exchange of Zn with V increased the selectivity of one of the MOFs from 119 to 355 and the adsorbent performance score from 70 to 444 mol/kg, while for another MOF, exchange of Zn with Cr increased the selectivity from 161 to 921 and the adsorbent performance score from 162 to 1233 mol/kg under the condition of vacuum swing adsorption. The molecular level insights we provided to explain the improvement in the gas separation performances of M-MOFs will serve as a guide to design materials with exceptional CO2 separation performances.

An upper bound visualization of design trade-offs in adsorbent materials for gas separations: alkene/alkane adsorbents

The last 20 years has seen an explosion in the number of publications investigating porous solids for gas adsorption and separation. The combination of external drivers such as anthropogenic climate change and industrial efficiency has been coupled with discovery of new materials such as synthetic zeolites, metal-organic frameworks, covalent organic frameworks, and non-porous adsorbents. Numerous reviews catalogue these materials and their properties. However, the field lacks a unifying resource to visually compare and analyse materials properties with regard to their utility as a scientific advance and potential for industrial use. In the related field of membrane science, the 'Robeson upper bound' empirically describes the trade-off between gas permeability and selectivity and has become a ubiquitous tool for comparing membrane materials. In this article, we propose upper and lower bounds that empirically correlate the trade-offs encountered when designing adsorbent materials for gas separation, specifically: capacity, selectivity, and heat of adsorption. We apply bound visualizations to adsorbents studied for light alkene/alkane separations and highlight their use in identifying candidate materials for examination within process models and for guiding insights to the most effective materials design strategies. Furthermore, we note the limitations of upper and lower bound visualizations and provide links to a database resource for researchers to produce and download bound visualization plots. We anticipate that introducing bound visualizations to the field of adsorbents for gas separations will allow researchers to provide context for the importance of new materials discoveries, understand trade-offs in adsorbent design, and connect process engineers with candidate materials.

Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation

The acceleration in design of new metal organic frameworks (MOFs) has led scientists to focus on high-throughput computational screening (HTCS) methods to quickly assess the promises of these fascinating materials in various applications. HTCS studies provide a massive amount of structural property and performance data for MOFs, which need to be further analyzed. Recent implementation of machine learning (ML), which is another growing field in research, to HTCS of MOFs has been very fruitful not only for revealing the hidden structure-performance relationships of materials but also for understanding their performance trends in different applications, specifically for gas storage and separation. In this review, we highlight the current state of the art in ML-assisted computational screening of MOFs for gas storage and separation and address both the opportunities and challenges that are emerging in this new field by emphasizing how merging of ML and MOF simulations can be useful.

Effect of Metal-Organic Framework (MOF) Database Selection on the Assessment of Gas Storage and Separation Potentials of MOFs

Development of computation-ready metal-organic framework databases (MOF DBs) has accelerated high-throughput computational screening (HTCS) of materials to identify the best candidates for gas storage and separation. These DBs were constructed using structural curations to make MOFs directly usable for molecular simulations, which caused the same MOF to be reported with different structural features in different DBs. We examined thousands of common materials of the two recently updated, very widely used MOF DBs to reveal how structural discrepancies affect simulated CH4 , H2 , CO2 uptakes and CH4 /H2 separation performances of MOFs. Results showed that DB selection has a significant effect on the calculated gas uptakes and ideal selectivities of materials at low pressure. A detailed analysis on the curated structures was provided to isolate the critical elements of MOFs determining the gas uptakes. Identification of the top-performing materials for gas separation was shown to strongly depend on the DB used in simulations.

Volatile Organic Compound Vapour Measurements Using a Localised Surface Plasmon Resonance Optical Fibre Sensor Decorated with a Metal-Organic Framework

A tip-based fibreoptic localised surface plasmon resonance (LSPR) sensor is reported for the sensing of volatile organic compounds (VOCs). The sensor is developed by coating the tip of a multi-mode optical fibre with gold nanoparticles (size: 40 nm) via a chemisorption process and further functionalisation with the HKUST-1 metal–organic framework (MOF) via a layer-by-layer process. Sensors coated with different cycles of MOFs (40, 80 and 120) corresponding to different crystallisation processes are reported. There is no measurable response to all tested volatile organic compounds (acetone, ethanol and methanol) in the sensor with 40 coating cycles. However, sensors with 80 and 120 coating cycles show a significant redshift of resonance wavelength (up to ~9 nm) to all tested volatile organic compounds as a result of an increase in the local refractive index induced by VOC capture into the HKUST-1 thin film. Sensors gradually saturate as VOC concentration increases (up to 3.41%, 4.30% and 6.18% in acetone, ethanol and methanol measurement, respectively) and show a fully reversible response when the concentration decreases. The sensor with the thickest film exhibits slightly higher sensitivity than the sensor with a thinner film. The sensitivity of the 120-cycle-coated MOF sensor is 13.7 nm/% (R² = 0.951) with a limit of detection (LoD) of 0.005% in the measurement of acetone, 15.5 nm/% (R² = 0.996) with an LoD of 0.003% in the measurement of ethanol and 6.7 nm/% (R² = 0.998) with an LoD of 0.011% in the measurement of methanol. The response and recovery times were calculated as 9.35 and 3.85 min for acetone; 5.35 and 2.12 min for ethanol; and 2.39 and 1.44 min for methanol. The humidity and temperature crosstalk of 120-cycle-coated MOF was measured as 0.5 ± 0.2 nm and 0.5 ± 0.1 nm in the humidity range of 50–75% relative humidity (RH) and temperature range of 20–25 °C, respectively.

Metal–organic frameworks/biopolymer nanocomposites: from fundamentals toward recent applications in modern technology

Bio–nanocomposite compounds based on biopolymers and MOFs have presented great potential in various applications for modern technology.

Bi(iii) MOFs: syntheses, structures and applications

The synthesis methods, structures and applications of Bi(iii)-based MOFs in catalysis, adsorption, fluorescence, etc. are reviewed.

The crystalline sponge method: quantum chemical in silico derivation and analysis of guest binding energies

Computational techniques combined with single-crystal structural data provide a means to further analyse MOF-based crystalline sponge complexes.

MOF/COF-based materials using 3D printing technology: applications in water treatment, gas removal, biomedical, and electronic industries

We have considered the newest outcomes in the uses of 3D-printed COF- and MOF-based materials for diverse applications.

Computational Selection of High-Performing Covalent Organic Frameworks for Adsorption and Membrane-Based CO2/H2 Separation

Covalent organic frameworks (COFs) have high potential in gas separation technologies because of their porous structures, large surface areas, and good stabilities. The number of synthesized COFs already reached several hundreds, but only a handful of materials were tested as adsorbents and/or membranes. We used a high-throughput computational screening approach to uncover adsorption-based and membrane-based CO₂/H₂ separation potentials of 288 COFs, representing the highest number of experimentally synthesized COFs studied to date for precombustion CO₂ capture. Grand canonical Monte Carlo (GCMC) simulations were performed to assess CO₂/H₂ mixture separation performances of COFs for five different cyclic adsorption processes: pressure swing adsorption, vacuum swing adsorption, temperature swing adsorption (TSA), pressure-temperature swing adsorption (PTSA), and vacuum-temperature swing adsorption (VTSA). The results showed that many COFs outperform traditional zeolites in terms of CO₂ selectivities and working capacities and PTSA is the best process leading to the highest adsorbent performance scores. Combining GCMC and molecular dynamics (MD) simulations, CO₂ and H₂ permeabilities and selectivities of COF membranes were calculated. The majority of COF membranes surpass Robeson's upper bound because of their higher H₂ permeabilities compared to polymers, indicating that the usage of COFs has enormous potential to replace current materials in membrane-based H₂/CO₂ separation processes. Performance analysis based on the structural properties showed that COFs with narrow pores [the largest cavity diameter (LCD) < 15 Å] and low porosities (ϕ < 0.75) are the top adsorbents for selective separation of CO₂ from H₂, whereas materials with large pores (LCD > 20 Å) and high porosities (ϕ > 0.85) are generally the best COF membranes for selective separation of H₂ from CO₂. These results will help to speed up the engineering of new COFs with desired structural properties to achieve high-performance CO₂/H₂ separations.