The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials

Efficient Removal of Greenhouse Gases: Machine Learning-Assisted Exploration of Metal-Organic Framework Space

Global warming is a crisis that humanity must face together. With greenhouse gases (GHGs) as the main factor causing global warming, the adoption of relevant processes to eliminate them is essential. With the advantages of high specific surface area, large pore volume, and tunable synthesis, metal-organic frameworks (MOFs) have attracted much attention in GHG storage, adsorption, separation, and catalysis. However, as the pool of MOFs expands rapidly with new syntheses and discoveries, finding a suitable MOF for a particular application is highly challenging. In this regard, high-throughput computational screening is considered the most effective research method for screening a large number of materials to discover high-performance target MOFs. Typically, high-throughput computational screening generates voluminous and multidimensional data, which is well suited for machine learning (ML) training to improve the screening efficiency and explore the relationships between the multidimensional data in depth. This Review summarizes the general process and common methods for using ML to screen MOFs in the field of GHG removal. It also addresses the challenges faced by ML in exploring the MOF space and potential directions for the future development of ML for MOF screening. This aims to enhance the understanding of the integration of ML and MOFs in various fields and broaden the application and development ideas of MOFs.

Systematic exploration of accessible topologies of cage molecules via minimalistic models

Cages are macrocyclic structures with an intrinsic internal cavity that support applications in separations, sensing and catalysis. These materials can be synthesised via self-assembly of organic or metal-organic building blocks. Their bottom-up synthesis and the diversity in building block chemistry allows for fine-tuning of their shape and properties towards a target property. However, it is not straightforward to predict the outcome of self-assembly, and, thus, the structures that are practically accessible during synthesis. Indeed, such a prediction becomes more difficult as problems related to the flexibility of the building blocks or increased combinatorics lead to a higher level of complexity and increased computational costs. Molecular models, and their coarse-graining into simplified representations, may be very useful to this end. Here, we develop a minimalistic toy model of cage-like molecules to explore the stable space of different cage topologies based on a few fundamental geometric building block parameters. Our results capture, despite the simplifications of the model, known geometrical design rules in synthetic cage molecules and uncover the role of building block coordination number and flexibility on the stability of cage topologies. This leads to a large-scale and systematic exploration of design principles, generating data that we expect could be analysed through expandable approaches towards the rational design of self-assembled porous architectures.

Rapid adsorption enthalpy surface sampling (RAESS) to characterize nanoporous materials

Molecular adsorption in nanoporous materials has many large-scale industrial applications ranging from separation to storage. To design the best materials, computational simulations are key to guiding the experimentation and engineering processes. Because nanoporous materials exist in a plethora of forms, we need to speed up the existing simulation tools to be able to screen databases of hundreds of thousands of structures. Here, we describe a new algorithm that quickly calculates adsorption enthalpies by sampling the surface of the material instead of the whole porous space. This surface sampling has been tested on the CoRE MOF 2019 database and has been proven to be more than 2 orders of magnitude faster than the gold standard method (Widom insertion), with an acceptable level of error on an enthalpy value of 0.34 kJ mol^-1, and is therefore proposed as a valuable addition to the high-throughput screening toolbox.

Democratizing the Assessment of Thermal Robustness of Metal-Organic Frameworks

With the pressing need of having reliable materials for carbon dioxide capture, metal-organic frameworks (MOFs) have shown promising performance due to their flexible sign and tunable functionality by applying reticular chemistry principles. One of the main characteristics of practical MOFs is to design thermally robust candidates for sustainable functionality. Here, we introduce a comprehensive methodology for examining the thermal stability of MOFs by combining theoretical calculations and affordable experimental methods to fully describe their performance under thermal variations. We chose the prototypical MOF, HKUST-1, to assess the methodology by performing density functional theory and classical molecular dynamics simulations and validating with experiments such as in situ powder X-ray diffraction, differential scanning calorimetry, and thermogravimetric analysis. HKUST-1 shows thermal robustness until a temperature of 240 °C at different atmospheric gases with a reversible breathing trend with temperature. This methodology is affordable as it uses minimal experimental testing and can be applied to any MOF materials to explore its suitability for practical applications.

Machine Learning in the Development of Adsorbents for Clean Energy Application and Greenhouse Gas Capture

Addressing climate change challenges by reducing greenhouse gas levels requires innovative adsorbent materials for clean energy applications. Recent progress in machine learning has stimulated technological breakthroughs in the discovery, design, and deployment of materials with potential for high-performance and low-cost clean energy applications. This review summarizes basic machine learning methods-data collection, featurization, model generation, and model evaluation-and reviews their use in the development of robust adsorbent materials. Key case studies are provided where these methods are used to accelerate adsorbent materials design and discovery, optimize synthesis conditions, and understand complex feature-property relationships. The review provides a concise resource for researchers wishing to use machine learning methods to rapidly develop effective adsorbent materials with a positive impact on the environment.

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.

Shell-like Xenon Nano-Traps within Angular Anion-Pillared Layered Porous Materials for Boosting Xe/Kr Separation

Adsorptive separation of xenon (Xe) and krypton (Kr) is a promising technique but remains a daunting challenge since they are atomic gases without dipole or quadruple moments. Herein we report a strategy for fabricating angular anion-pillared materials featuring shell-like Xe nano-traps, which provide a cooperative effect conferred by the pore confinement and multiple specific interactions. The perfect permanent pore channel (4-5 Å) of Ni(4-DPDS)₂ MO₄ (M=Cr, Mo, W) can host Xe atoms efficiently even at ultra-low concentration (400 ppm Xe), showing the second-highest selectivity of 30.2 in Ni(4-DPDS)₂ WO₄ and excellent Xe adsorption capacity in Ni(4-DPDS)₂ CrO₄ (15.0 mmol kg^-1 ). Crystallography studies and DFT-D calculations revealed the energy favorable binding sites and angular anions enable the synergism between optimal pore size and polar porosity for boosting Xe affinity. Dynamic breakthrough experiments demonstrated three MOFs as efficient adsorbents for Xe/Kr separation.

Incorporating Flexibility Effects into Metal-Organic Framework Adsorption Simulations Using Different Models

High-throughput calculations based on molecular simulations to predict the adsorption of molecules inside metal-organic frameworks (MOFs) have become a useful complement to experimental efforts to identify promising adsorbents for chemical separations and storage. For computational convenience, all existing efforts of this kind have relied on simulations in which the MOF is approximated as rigid. In this paper, we use extensive adsorption-relaxation simulations that fully include MOF flexibility effects to explore the validity of the rigid framework approximation. We also examine the accuracy of several approximate methods to incorporate framework flexibility that are more computationally efficient than adsorption-relaxation calculations. We first benchmark various models of MOF flexibility for four MOFs with well-established CO₂ experimental consensus isotherms. We then consider a range of adsorption properties, including Henry's constants, nondilute loadings, and adsorption selectivity, for seven adsorbates in 15 MOFs randomly selected from the CoRE MOF database. Our results indicate that in many MOFs adsorption-relaxation simulations are necessary to make quantitative predictions of adsorption, particularly for adsorption at dilute concentrations, although more standard calculations based on rigid structures can provide useful information. Finally, we investigate whether a correlation exists between the elastic properties of empty MOFs and the importance of including framework flexibility in making accurate predictions of molecular adsorption. Our results did not identify a simple correlation of this type.

Performance-Based Screening of Porous Materials for Carbon Capture

Computational screening methods have changed the way new materials and processes are discovered and designed. For adsorption-based gas separations and carbon capture, recent efforts have been directed toward the development of multiscale and performance-based screening workflows where we can go from the atomistic structure of an adsorbent to its equilibrium and transport properties at different scales, and eventually to its separation performance at the process level. The objective of this work is to review the current status of this new approach, discuss its potential and impact on the field of materials screening, and highlight the challenges that limit its application. We compile and introduce all the elements required for the development, implementation, and operation of multiscale workflows, hence providing a useful practical guide and a comprehensive source of reference to the scientific communities who work in this area. Our review includes information about available materials databases, state-of-the-art molecular simulation and process modeling tools, and a complete catalogue of data and parameters that are required at each stage of the multiscale screening. We thoroughly discuss the challenges associated with data availability, consistency of the models, and reproducibility of the data and, finally, propose new directions for the future of the field.

Emergence of Coupled Rotor Dynamics in Metal-Organic Frameworks via Tuned Steric Interactions

The organic components in metal–organic frameworks (MOFs) are unique: they are embedded in a crystalline lattice, yet, as they are separated from each other by tunable free space, a large variety of dynamic behavior can emerge. These rotational dynamics of the organic linkers are especially important due to their influence over properties such as gas adsorption and kinetics of guest release. To fully exploit linker rotation, such as in the form of molecular machines, it is necessary to engineer correlated linker dynamics to achieve their cooperative functional motion. Here, we show that for MIL-53, a topology with closely spaced rotors, the phenylene functionalization allows researchers to tune the rotors’ steric environment, shifting linker rotation from completely static to rapid motions at frequencies above 100 MHz. For steric interactions that start to inhibit independent rotor motion, we identify for the first time the emergence of coupled rotation modes in linker dynamics. These findings pave the way for function-specific engineering of gear-like cooperative motion in MOFs.

Tunable Metal-Organic Frameworks Based on 8-Connected Metal Trimers for High Ethane Uptake

Metal trimers [M₃ (O/OH)](OOCR)₆ are among the most important structural building blocks. From these trimers, a great success has been achieved in the design of 6- or 9-connected framework materials with various topological features and outstanding gas-sorption properties. In comparison, 8-connected trimer-based metal-organic frameworks (MOFs) are rare. Given multiple competitive pathways for the formation of 6- or 9-connected frameworks, it remains challenging to identify synthetic or structural parameters that can be used to direct the self-assembly process toward trimer-based 8-connected materials. Here, a viable strategy called angle bending modulation is revealed for creating a prototypical MOF type based on 8-connected M₃ (OH)(OOCR)₅ (Py-R)₃ trimers (M = Zn, Co, Fe). As a proof of concept, six members in this family are synthesized using three types of ligands (CPM-80, -81, and -82). These materials do not possess open-metal sites and show excellent uptake capacity for various hydrocarbon gas molecules and inverse C₂ H₆ /C₂ H₄ selectivity. CPM-81-Co, made from 2,5-furandicarboxylate and isonicotinate, features selectivity of 1.80 with high uptake capacity for ethane (123 cm³ g^-1 ) and ethylene (113 cm³ g^-1 ) at 298 K and 1 bar.

Computational Screening of Trillions of Metal-Organic Frameworks for High-Performance Methane Storage

In the past decade, there has been an increasing number of computational screening works to facilitate finding optimal materials for a variety of different applications. Unfortunately, most of these screening studies are limited to their initial set of materials and result in a brute-force type of screening approach. In this work, we present a systematic strategy that can find metal-organic frameworks (MOFs) with the desired properties from an extremely diverse and large set of over 100 trillion possible MOFs using machine learning and evolutionary algorithm. It is demonstrated that our algorithm can discover 964 MOFs with methane working capacity over 200 cm³ cm^-3 and 96 MOFs with methane working capacity over the current world record of 208 cm³ cm^-3. We believe that this methodology can take advantage of the modular nature of MOFs and can readily be extended to other important applications as well.

What Lies beneath a Metal-Organic Framework Crystal Structure? New Design Principles from Unexpected Behaviors

The rational design principles established for metal-organic frameworks (MOFs) allow clear structure-property relationships, fueling expansive growth for energy storage and conversion, catalysis, and beyond. However, these design principles are based on the assumption of compositional and structural rigidity, as measured crystallographically. Such idealization of MOF structures overlooks subtle chemical aspects that can lead to departures from structure-based chemical intuition. In this Perspective, we identify unexpected behavior of MOFs through literature examples. Based on this analysis, we conclude that departures from ideality are not uncommon. Whereas linker topology and metal coordination geometry are useful starting points for understanding MOF properties, we anticipate that deviations from the idealized crystal representation will be necessary to explain important and unexpected behaviors. Although this realization reinforces the notion that MOFs are highly complex materials, it should also stimulate a broader reexamination of the literature to identify corollaries to existing design rules and reveal new structure-property relationships.

Kinetic Barriers and Microscopic Mechanisms of Noble Gas Adsorption by Nanoporous γ-Mg(BH4 )2 Obtained by Means of Sub-Second X-Ray Diffraction

Gas adsorption by porous frameworks sometimes results in structure "breathing", "pores opening/closing", "negative gas adsorption", and other phenomena. Time-dependent diffraction can address both kinetics of the guest uptake and structural response of the host framework. Using sub-second in situ powder X-ray diffraction, three intracrystalline diffusion scenarios have been evaluated from the isothermal kinetics of Ar, Kr, and Xe adsorption by nanoporous γ-Mg(BH₄ )₂ . These scenarios are dictated by two possible simultaneous transport mechanisms: diffusion through the intra- (i) and interchannel apertures (ii) of γ-Mg(BH₄ )₂ crystal structure. The contribution of (i) and (ii) changes depending on the kinetic diameter of the noble gas molecule and temperature regime. The lowest single activation barrier for the smallest Ar suggests equal diffusion of the atoms trough both pathways. Contrary, for the medium sized Kr we resolve the contributions of two parallel transport mechanisms, which tentatively can be attributed to the smaller barrier of the migration paths via the channel like pores and the higher barrier for the diffusion via narrow aperture between these channels. The largest Xe atoms diffuse only along 1D channels and show the highest single activation barrier.

Adsorption-Based Separation of Near-Azeotropic Mixtures-A Challenging Example for High-Throughput Development of Adsorbents

Adsorption of gas mixtures is central to adsorption-based gas separations, and the number of adsorbate mixture/adsorbent systems that exist is staggering. Because examples of machine learning (ML) models predicting single-component adsorption of arbitrary molecules in large libraries of crystalline adsorbents have been developed, it is interesting to determine whether these models can accurately predict mixture adsorption. Here, we use molecular simulations to generate mixture adsorption data with a set of 12 near-azeotropic molecules in a diverse set of MOFs. These data provide a challenging example for any method to rapidly predict mixture adsorption in MOFs. We combine a previous ML single-component isotherm model with ideal adsorbed solution theory (IAST) to make predictions that can be compared directly with molecular simulation data for these adsorbed mixtures. This combination of ML and IAST illustrates the scope that is available with these methods, but the accuracy of the resulting predictions is disappointing. By examining the same examples with IAST based on minimal molecular simulation data for single-component isotherms, we show that having an accurate description of adsorption in the dilute loading limit is critical to being able to accurately predict mixture adsorption. This observation points to a useful direction for future work developing robust ML models of adsorption isotherms for diverse collections of molecules and adsorbents.

In-silico identification of adsorbent for separation of ethane/ethylene mixture

We present here a high-throughput computational screening of 4,821 real metal-organic framework (MOF) structures that do not contain any open metal sites to isolate the best performing candidate for separation of ethane/ethylene mixture at ambient conditions. The MOF structures were assessed on the basis of several adsorption-based separation performance metrics. Some of these metrics were found to correlate strongly among themselves. We have presented various structures-property correlations which unfold useful insights. MOF ATAGEJ is found to be the top performing MOF with highest adsorbent performance score 12.38 mol/kg and regenerability 93.88%. Several other MOFs OTOLIU (MIL-167), UMUMOG (UBMOF-8), and TOVGES (PCN-230) containing tetravalent metal cations such as Zr⁴⁺ and Ti⁴⁺ are found to be potential structures that are thermally, mechanically, and chemically stable and performs better than zeolites. Adsorption selectivity shows exponential correlation with difference of heat of adsorption of ethane and ethene at 0.1 bar and 298 K. We have also presented how various performance metrics correlate among themselves. These correlations unfold useful insights. Graphical abstract.

High Throughput Methods in the Synthesis, Characterization, and Optimization of Porous Materials

Porous materials are widely employed in a large range of applications, in particular, for storage, separation, and catalysis of fine chemicals. Synthesis, characterization, and pre- and post-synthetic computer simulations are mostly carried out in a piecemeal and ad hoc manner. Whilst high throughput approaches have been used for more than 30 years in the porous material fields, routine integration of experimental and computational processes is only now becoming more established. Herein, important developments are highlighted and emerging challenges for the community identified, including the need to work toward more integrated workflows.

High-throughput screening of metal-organic frameworks for kinetic separation of propane and propene

We apply molecular simulations to screen a database of reported metal-organic framework structures from the computation-ready, experimental (CoRE) MOF database to identify materials potentially capable of separating propane and propene by diffusion. We report a screening workflow that uses descriptor analysis, conventional molecular dynamics (MD), and Nudged Elastic Band (NEB) energy barrier calculations at both classical force field and Density Functional Theory (DFT) levels. For the first time, the effects of framework flexibility on guest transport properties were fully considered in a screening process and led to the identification of candidate MOFs. The hits identified by this proof-of-concept workflow include ZIF-8 and ZIF-67 previously shown to have large differences in propane and propene diffusivities as well as two other materials that have not been tested experimentally yet. This work emphasises the importance of taking into account framework flexibility when studying guest transport in porous materials, demonstrates the potential of the data-driven identification of high-performance materials and highlights the ways of improving the predictive power of the screening workflow.

MOF-Based Membranes for Gas Separations

Metal-organic frameworks (MOFs) represent the largest known class of porous crystalline materials ever synthesized. Their narrow pore windows and nearly unlimited structural and chemical features have made these materials of significant interest for membrane-based gas separations. In this comprehensive review, we discuss opportunities and challenges related to the formation of pure MOF films and mixed-matrix membranes (MMMs). Common and emerging separation applications are identified, and membrane transport theory for MOFs is described and contextualized relative to the governing principles that describe transport in polymers. Additionally, cross-cutting research opportunities using advanced metrologies and computational techniques are reviewed. To quantify membrane performance, we introduce a simple membrane performance score that has been tabulated for all of the literature data compiled in this review. These data are reported on upper bound plots, revealing classes of MOF materials that consistently demonstrate promising separation performance. Recommendations are provided with the intent of identifying the most promising materials and directions for the field in terms of fundamental science and eventual deployment of MOF materials for commercial membrane-based gas separations.

CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.

Non-Isothermal Kinetics of Kr Adsorption by Nanoporous γ-Mg(BH4)2 from in Situ Synchrotron Powder Diffraction

Crystalline materials with pore dimensions comparable to the kinetic diameters of the guest molecules are attractive for their potential use in adsorption and separation applications. The nanoporous γ-Mg(BH₄)₂ features one-dimensional channels matching this criterion for Kr uptake, which has been probed using synchrotron powder diffraction at various pressures and temperatures. It results in two coexisting crystalline phases with the limiting composition Mg(BH₄)₂·0.66Kr expecting the highest Kr content (50.7 wt % in the crystalline phase) reported for porous materials. Quasi-equilibrium isobars built from Rietveld refinements of Kr site occupancies were rationalized with a noncooperative lattice gas model, yielding the values of the thermodynamic parameters. The latter were independently confirmed from Kr fluorescence. We have also parameterized the pronounced kinetic hysteresis with a modified mean-field model adopted for the Arrhenius kinetics.

Impact of intrinsic framework flexibility for selective adsorption of sarin in non-aqueous solvents using metal–organic frameworks

We assess the nontrivial deviation in predicting the adsorption selectivity from bulk mixtures of complex molecules using nanoporous adsorbents approximated as rigid and intrinsically flexible.

Adsorptive Separation of Acetylene from Ethylene in Isostructural Gallate-Based Metal-Organic Frameworks

The separation of acetylene from ethylene is of paramount importance in the purification of chemical feedstocks for industrial manufacturing. Herein, an isostructural series of gallate-based metal-organic frameworks (MOFs), M-gallate (M=Ni, Mg, Co), featuring three-dimensionally interconnected zigzag channels, the aperture size of which can be finely tuned within 0.3 Å by metal replacement. Controlling the aperture size of M-gallate materials slightly from 3.69 down to 3.47 Å could result in a dramatic enhancement of C₂ H₂ /C₂ H₄ separation performance. As the smallest radius among the studied metal ions, Ni-gallate exhibits the best C₂ H₂ /C₂ H₄ adsorption separation performance owing to the strongest confinement effect, ranking after the state-of-the-art UTSA-200a with a C₂ H₄ productivity of 85.6 mol L^-1 from 1:99 C₂ H₂ /C₂ H₄ mixture. The isostructural gallate-based MOFs, readily synthesized from inexpensive gallic acid, are demonstrated to be a new top-performing porous material for highly efficient adsorption of C₂ H₂ from C₂ H₄ .

Simulating Enhanced Methane Deliverable Capacity of Guest Responsive Pores in Intrinsically Flexible MOFs

A novel computational procedure, based on the principles of flat-histogram Monte Carlo, is developed for facile prediction of the adsorption thermodynamics of intrinsically flexible adsorbents. We then demonstrate how an accurate prediction of methane deliverable capacity in a metal-organic framework (MOF) with significant intrinsic flexibility requires use of such a method. Dynamic side chains in the framework respond to methane adsorbates and reorganize to exhibit a more conducive pore space at high adsorbate densities while simultaneously providing a less conducive pore space at low adsorbate densities. This "responsive pore" MOF achieves ∼20% higher deliverable capacity than if the framework were rigid and elucidates a strategy for designing high deliverable capacity MOFs in the future.

Effects of Intrinsic Flexibility on Adsorption Properties of Metal-Organic Frameworks at Dilute and Nondilute Loadings

Molecular simulation of adsorption in nanoporous materials has become a valuable complement to experimental studies of these materials. In almost all cases, these simulations treat the adsorbing material as rigid. We use molecular simulations to examine the validity of this approximation for the adsorption in metal-organic frameworks (MOFs) that have framework flexibility without change in their unit cells because of thermal vibrations. All nanoporous materials are subject to this kind of framework flexibility. We examine the adsorption of nine molecules (CO₂, CH₄, ethane, ethene, propane, propene, butane, Xe, and Kr) and four molecular mixtures (CO₂/CH₄, ethane/ethene, propane/propene/butane, and Xe/Kr) in 100 MOFs at dilute and nondilute adsorption conditions. Our results show that single-component adsorption uptakes at nondilute conditions are only weakly affected by framework flexibility, but adsorption selectivities at both dilute and nondilute conditions can be significantly affected by flexibility. The most dramatic impacts of framework flexibility occur for adsorption uptake in the limit of dilute adsorption. These results suggest that the importance of including framework flexibility when attempting to make quantitative predictions of adsorption selectivity in MOFs and similar materials may have been underestimated in the past.

Implementing Metal-Organic Frameworks for Natural Gas Storage

Methane can be stored by metal-organic frameworks (MOFs). However, there remain challenges in the implementation of MOFs for adsorbed natural gas (ANG) systems. These challenges include thermal management, storage capacity losses due to MOF packing and densification, and natural gas impurities. In this review, we discuss discoveries about how MOFs can be designed to address these three challenges. For example, Fe(bdp) (bdp2− = 1,4-benzenedipyrazolate) was discovered to have intrinsic thermal management and released 41% less heat than HKUST-1 (HKUST = Hong Kong University of Science and Technology) during adsorption. Monolithic HKUST-1 was discovered to have a working capacity 259 cm3 (STP) cm−3 (STP = standard temperature and pressure equivalent volume of methane per volume of the adsorbent material: T = 273.15 K, P = 101.325 kPa), which is a 50% improvement over any other previously reported experimental value and virtually matches the 2012 Department of Energy (Department of Energy = DOE) target of 263 cm3 (STP) cm−3 after successful packing and densification. In the case of natural gas impurities, higher hydrocarbons and other molecules may poison or block active sites in MOFs, resulting in up to a 50% reduction of the deliverable energy. This reduction can be mitigated by pore engineering.

Ab Initio Flexible Force Field for Metal-Organic Frameworks Using Dummy Model Coordination Bonds

We present force fields developed from periodic density functional theory (DFT) calculations that can be used in classical molecular simulations to model M-MOF-74 (M = Co, Fe, Mg, Mn, Ni, Zn) and its extended linker analogs. Our force fields are based on cationic dummy models (CDMs). These dummy models simplify the methodology required to tune the parameters and improve the accuracy of the force fields. We used our force fields to compare mechanical properties across the M-MOF-74 series and determine that increasing the size of the linker decreases the framework rigidity. In addition, we applied our force fields to an extended linker analog of Mg-MOF-74 and characterized the free energy of a previously reported deformation pattern in which the one-dimensional hexagonal channels of the framework become irregular. The free energy profiles confirm that the deformation is adsorbate induced and impossible to access solely by a pressure stimulus. On the basis of our results, we conclude that the force fields presented here and others that may be developed using our methodology are transferable across metal-organic framework series that share a metal center topology. Finally, we believe that these force fields have the potential to be adapted for the study of complex problems in MOF chemistry, including defects and crystal growth, that have thus far been beyond the scope of classical molecular simulations.

Computational Analysis of Linker Defective Metal-Organic Frameworks for Membrane Separation Applications

Intracrystalline defects in metal-organic frameworks (MOFs) are known to have crucial roles in dictating their material properties. In this work, computational simulations were used to induce linker vacancy defects in MOF membranes and to investigate their influence on H₂/CH₄ separation. Linker defective structures were created for the 228 candidate MOFs, and their separation performances were compared between the defective and the nondefective structures. Our results show that the existence of linker vacancy defects can lead to significant performance changes in the MOF membranes, and more importantly, the ranking of the best materials can differ with the defects present. This suggests the importance of taking into account the potential for defects when it comes to materials design for various membrane separation applications.

Phonons in deformable microporous crystalline solids

Phonons are quantum elastic excitations of crystalline solids. Classically, they correspond to the collective vibrations of atoms in ordered periodic structures. They determine the thermodynamic properties of solids and their stability in the case of structural transformations. Here we review for the first time the existing examples of the phonon analysis of adsorption-induced transformations occurring in microporous crystalline materials. We discuss the role of phonons in determining the mechanism of the deformations. We point out that phonon-based methodology may be used as a predictive tool in characterization of flexible microporous structures; therefore, relevant numerical tools must be developed.

An In-Situ Neutron Diffraction and DFT Study of Hydrogen Adsorption in a Sodalite-Type Metal-Organic Framework, Cu-BTTri

Herein we present a detailed study of the hydrogen adsorption properties of Cu-BTTri, a robust crystalline metal-organic framework containing open metal-coordination sites. Diffraction techniques, carried out on the activated framework, reveal a structure that is different from what was previously reported. Further, combining standard hydrogen adsorption measurements with in-situ neutron diffraction techniques provides molecular level insight into the hydrogen adsorption process. The diffraction experiments unveil the location of four D2 adsorption sites in Cu-BTTri and shed light on the structural features that promote hydrogen adsorption in this material. Density functional theory (DFT), used to predict the location and strength of binding sites, corroborate the experimental findings. By decomposing binding energies in different sites in various energetic contributions, we show that van der Waals interactions play a crucial role, suggesting a possible route to enhancing the binding energy around open metal coordination sites.

The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation

Metal-organic frameworks (MOFs) are highly tuneable, extended-network, crystalline, nanoporous materials with applications in gas storage, separations, and sensing. We review how molecular models and simulations of gas adsorption in MOFs have informed the discovery of performant MOFs for methane, hydrogen, and oxygen storage, xenon, carbon dioxide, and chemical warfare agent capture, and xylene enrichment. Particularly, we highlight how large, open databases of MOF crystal structures, post-processed to enable molecular simulations, are a platform for computational materials discovery. We discuss how to orient research efforts to routinise the computational discovery of MOFs for adsorption-based engineering applications.

Eigencages: Learning a Latent Space of Porous Cage Molecules

Porous organic cage molecules harbor nanosized cavities that can selectively adsorb gas molecules, lending them applications in separations and sensing. The geometry of the cavity strongly influences their adsorptive selectivity. For comparing cages and predicting their adsorption properties, we embed/encode a set of 74 porous organic cage molecules into a low-dimensional, latent "cage space" on the basis of their intrinsic porosity. We first computationally scan each cage to generate a three-dimensional (3D) image of its porosity. Leveraging the singular value decomposition, in an unsupervised manner, we then learn across all cages an approximate, lower-dimensional subspace in which the 3D porosity images congregate. The "eigencages" are the set of orthogonal, characteristic 3D porosity images that span this lower-dimensional subspace, ordered in terms of importance. A latent representation/encoding of each cage follows by approximately expressing it as a combination of the eigencages. We show that the learned encoding captures salient features of the cavities of porous cages and is predictive of properties of the cages that arise from cavity shape. Our methods could be applied to learn latent representations of cavities within other classes of porous materials and of shapes of molecules in general.

Biporous Metal-Organic Framework with Tunable CO2/CH4 Separation Performance Facilitated by Intrinsic Flexibility

In this work, we report the synthesis of SION-8, a novel metal-organic framework (MOF) based on Ca(II) and a tetracarboxylate ligand TBAPy^4- endowed with two chemically distinct types of pores characterized by their hydrophobic and hydrophilic properties. By altering the activation conditions, we gained access to two bulk materials: the fully activated SION-8F and the partially activated SION-8P with exclusively the hydrophobic pores activated. SION-8P shows high affinity for both CO₂ ( Q_st = 28.4 kJ/mol) and CH₄ ( Q_st = 21.4 kJ/mol), while upon full activation, the difference in affinity for CO₂ ( Q_st = 23.4 kJ/mol) and CH₄ ( Q_st = 16.0 kJ/mol) is more pronounced. The intrinsic flexibility of both materials results in complex adsorption behavior and greater adsorption of gas molecules than if the materials were rigid. Their CO₂/CH₄ separation performance was tested in fixed-bed breakthrough experiments using binary gas mixtures of different compositions and rationalized in terms of molecular interactions. SION-8F showed a 40-160% increase (depending on the temperature and the gas mixture composition probed) of the CO₂/CH₄ dynamic breakthrough selectivity compared to SION-8P, demonstrating the possibility to rationally tune the separation performance of a single MOF by manipulating the stepwise activation made possible by the MOF's biporous nature.

Guest-Induced Switchable Breathing Behavior in a Flexible Metal-Organic Framework with Pronounced Negative Gas Pressure

Flexible metal-organic frameworks (MOFs) have attracted great interest for their dynamically structural transformability in response to external stimuli. Herein, we report a switchable "breathing" or "gate-opening" behavior associated with the phase transformation between a narrow pore (np) and a large pore (lp) in a flexible pillared-layered MOF, denoted as MOF-1 as, which is also confirmed by SCXRD and PXRD. The desolvated phase (MOF-1 des) features a unique stepwise adsorption isotherm for N₂ coupled with a pronounced negative gas adsorption pressure. For comparison, however, no appreciable CO₂ adsorption and gate-opening phenomenon with stepwise sorption can be observed. Furthermore, the polar micropore walls decorated with thiophene groups in MOF-1 des reveals the selective sorption of toluene over benzene and p-xylene associated with self-structural adjustment in spite of the markedly similar physicochemical properties of these vapor molecules.

Extension of the QuickFF force field protocol for an improved accuracy of structural, vibrational, mechanical and thermal properties of metal-organic frameworks

QuickFF was originally launched in 2015 to derive accurate force fields for isolated and complex molecular systems in a quick and easy way. Apart from the general applicability, the functionality was especially tested for metal-organic frameworks (MOFs), a class of hybrid materials consisting of organic and inorganic building blocks. Herein, we launch a new release of the QuickFF protocol which includes new major features to predict structural, vibrational, mechanical and thermal properties with greater accuracy, without compromising its robustness and transparent workflow. First, the ab initio data necessary for the fitting procedure may now also be derived from periodic models for the molecular system, as opposed to the earlier cluster-based models. This is essential for an accurate description of MOFs with one-dimensional metal-oxide chains. Second, cross terms that couple internal coordinates (ICs) and anharmonic contributions for bond and bend terms are implemented. These features are essential for a proper description of vibrational and thermal properties. Third, the fitting scheme was modified to improve robustness and accuracy. The new features are tested on MIL-53(Al), MOF-5, CAU-13 and NOTT-300. As expected, periodic input data are proven to be essential for a correct description of structural, vibrational and thermodynamic properties of MIL-53(Al). Bulk moduli and thermal expansion coefficients of MOF-5 are very accurately reproduced by static and dynamic simulations using the newly derived force fields which include cross terms and anharmonic corrections. For the flexible materials CAU-13 and NOTT-300, the transition pressure is accurately predicted provided cross terms are taken into account. © 2018 Wiley Periodicals, Inc.