Gas adsorption and framework flexibility of CALF-20 explored via experiments and simulations.

In 2021, Svante, in collaboration with BASF, reported successful scale up of CALF-20 production, a stable MOF with high capacity for post-combustion CO2 capture which exhibits remarkable stability towards water. CALF-20's success story in the MOF commercialisation space provides new thinking about appropriate structural and adsorptive metrics important for CO2 capture. Here, we combine atomistic-level simulations with experiments to study adsorptive properties of CALF-20 and shed light on its flexible crystal structure. We compare measured and predicted CO2 and water adsorption isotherms and explain the role of water-framework interactions and hydrogen bonding networks in CALF-20's hydrophobic behaviour. Furthermore, regular and enhanced sampling molecular dynamics simulations are performed with both density-functional theory (DFT) and machine learning potentials (MLPs) trained to DFT energies and forces. From these simulations, the effects of adsorption-induced flexibility in CALF-20 are uncovered. We envisage this work would encourage development of other MOF materials useful for CO2 capture applications in humid conditions.

Augmented Reality for Enhanced Visualization of MOF Adsorbents.

Augmented reality (AR) is an emerging technique used to improve visualization and comprehension of complex 3D materials. This approach has been applied not only in the field of chemistry but also in real estate, physics, mechanical engineering, and many other areas. Here, we demonstrate the workflow for an app-free AR technique for visualization of metal-organic frameworks (MOFs) and other porous materials to investigate their crystal structures, topology, and gas adsorption sites. We think this workflow will serve as an additional tool for computational and experimental scientists working in the field for both research and educational purposes.

DigiMOF: A Database of Metal-Organic Framework Synthesis Information Generated via Text Mining.

The vastness of materials space, particularly that which is concerned with metal-organic frameworks (MOFs), creates the critical problem of performing efficient identification of promising materials for specific applications. Although high-throughput computational approaches, including the use of machine learning, have been useful in rapid screening and rational design of MOFs, they tend to neglect descriptors related to their synthesis. One way to improve the efficiency of MOF discovery is to data-mine published MOF papers to extract the materials informatics knowledge contained within journal articles. Here, by adapting the chemistry-aware natural language processing tool, ChemDataExtractor (CDE), we generated an open-source database of MOFs focused on their synthetic properties: the DigiMOF database. Using the CDE web scraping package alongside the Cambridge Structural Database (CSD) MOF subset, we automatically downloaded 43,281 unique MOF journal articles, extracted 15,501 unique MOF materials, and text-mined over 52,680 associated properties including the synthesis method, solvent, organic linker, metal precursor, and topology. Additionally, we developed an alternative data extraction technique to obtain and transform the chemical names assigned to each CSD entry in order to determine linker types for each structure in the CSD MOF subset. This data enabled us to match MOFs to a list of known linkers provided by Tokyo Chemical Industry UK Ltd. (TCI) and analyze the cost of these important chemicals. This centralized, structured database reveals the MOF synthetic data embedded within thousands of MOF publications and contains further topology, metal type, accessible surface area, largest cavity diameter, pore limiting diameter, open metal sites, and density calculations for all 3D MOFs in the CSD MOF subset. The DigiMOF database and associated software are publicly available for other researchers to rapidly search for MOFs with specific properties, conduct further analysis of alternative MOF production pathways, and create additional parsers to search for additional desirable properties.

Computational Characterization of Zr-Oxide MOFs for Adsorption Applications.

Zr-oxide secondary building units construct metal-organic framework (MOF) materials with excellent gas adsorption properties and high mechanical, thermal, and chemical stability. These attributes have led Zr-oxide MOFs to be well-recognized for a wide range of applications, including gas storage and separation, catalysis, as well as healthcare domain. Here, we report structure search methods within the Cambridge Structural Database (CSD) to create a curated subset of 102 Zr-oxide MOFs synthesized to date, bringing a unique record for all researchers working in this area. For the identified structures, we manually corrected the proton topology of hydroxyl and water molecules on the Zr-oxide nodes and characterized their textural properties, Brunauer-Emmett-Teller (BET) area, and topology. Importantly, we performed systematic periodic density functional theory (DFT) calculations comparing 25 different combinations of basis sets and functionals to calculate framework partial atomic charges for use in gas adsorption simulations. Through experimental verification of CO2 adsorption in selected Zr-oxide MOFs, we demonstrate the sensitivity of CO2 adsorption predictions at the Henry's regime to the choice of the DFT method for partial charge calculations. We characterized Zr-MOFs for their CO2 adsorption performance via high-throughput grand canonical Monte Carlo (GCMC) simulations and revealed how the chemistry of the Zr-oxide node could have a significant impact on CO2 uptake predictions. We found that the maximum CO2 uptake is obtained for structures with the heat of adsorption values >25 kJ/mol and the largest cavity diameters of ca. 6-7 Å. Finally, we introduced augmented reality (AR) visualizations as a means to bring adsorption phenomena alive in porous adsorbents and to dynamically explore gas adsorption sites in MOFs.

The development of a comprehensive toolbox based on multi-level, high-throughput screening of MOFs for CO/N2 separations.

The separation of CO/N2 mixtures is a challenging problem in the petrochemical sector due to the very similar physical properties of these two molecules, such as size, molecular weight and boiling point. To solve this and other challenging gas separations, one requires a holistic approach. The complexity of a screening exercise for adsorption-based separations arises from the multitude of existing porous materials, including metal-organic frameworks. Besides, the multivariate nature of the performance criteria that needs to be considered when designing an optimal adsorbent and a separation process - i.e. an optimal material requires fulfillment of several criteria simultaneously - makes the screening challenging. To address this, we have developed a multi-scale approach combining high-throughput molecular simulation screening, data mining and advanced visualization, as well as process system modelling, backed up by experimental validation. We have applied our recent advances in the engineering of porous materials' morphology to develop advanced monolithic structures. These conformed, shaped monoliths can be used readily in industrial applications, bringing a valuable strategy for the development of advanced materials. This toolbox is flexible enough to be applied to multiple adsorption-based gas separation applications.

Hydrogen storage in MOFs: Machine learning for finding a needle in a haystack.

In recent years, machine learning (ML) has grown exponentially within the field of structure property predictions in materials science. In this issue of Patterns, Ahmed and Siegel scrutinize several redeveloped ML techniques for systematic investigations of over 900,000 metal-organic framework (MOF) structures, taken from 19 databases, to discover new, potentially record-breaking, hydrogen-storage materials.

Data visualization for Industry 4.0: A stepping-stone toward a digital future, bridging the gap between academia and industry.

Here, we analyze the potential of advanced data-visualization dashboards as an enabling technology for Industry 4.0. High-dimensional, real-time visualization allows the graphical expression of complex process variables at a fraction of the cost of full-scale digitalization. It is therefore a more achievable goal for smaller firms looking to transition to digital manufacturing and poses a realistic stepping-stone approach for Industry 4.0.

Catalyst-Enabled In Situ Linkage Reduction in Imine Covalent Organic Frameworks.

New linkages for covalent organic frameworks (COFs) have been continuously pursued by chemists as they serve as the structure and property foundation for the materials. Developing new reaction types or modifying known linkages have been the only two methods to create new COF linkages. Herein, we report a novel strategy that uses H3PO3 as a bifunctional catalyst to achieve amine-linked COFs from readily available amine and aldehyde linkers. The acidic proton of H3PO3 catalyzes the imine framework formation, which is then in situ reduced to the amine COF by the reductive P-H moiety. The amine-linked COF outperforms its imine analogue in promoting Knoevenagel condensation because of the more basic sites and higher stability.

Pt(II)-Decorated Covalent Organic Framework for Photocatalytic Difluoroalkylation and Oxidative Cyclization Reactions.

A new covalent organic framework (COF) based on imine bonds was assembled from 2-(4-formylphenyl)-5-formylpyridine and 1,3,6,8-tetrakis(4-aminophenyl)pyrene, which showed an interesting dual-pore structure with high crystallinity. Postmetallation of the COF with Pt occurred selectively at the N donor (imine and pyridyl) in the larger pores. The metallated COF served as an excellent recyclable heterogeneous photocatalyst for decarboxylative difluoroalkylation and oxidative cyclization reactions.

Wiz: A Web-Based Tool for Interactive Visualization of Big Data.

In an age of information, visualizing and discerning meaning from data is as important as its collection. Interactive data visualization addresses both fronts by allowing researchers to explore data beyond what static images can offer. Here, we present Wiz, a web-based application for handling and visualizing large amounts of data. Wiz does not require programming or downloadable software for its use and allows scientists and non-scientists to unravel the complexity of data by splitting their relationships through 5D visual analytics, performing multivariate data analysis, such as principal component and linear discriminant analyses, all in vivid, publication-ready figures. With the explosion of high-throughput practices for materials discovery, information streaming capabilities, and the emphasis on industrial digitalization and artificial intelligence, we expect Wiz to serve as an invaluable tool to have a broad impact in our world of big data.

(Thio)urea-Based Covalent Organic Framework as a Hydrogen-Bond-Donating Catalyst.

Two-dimensional urea- and thiourea-containing covalent organic frameworks (COFs) were synthesized at ambient conditions at large scale within 1 h in the absence of an acid catalyst. The site-isolated urea and thiourea in the COF showed enhanced catalytic efficiency as a hydrogen-bond-donating organocatalyst compared to the molecular counterparts in epoxide ring-opening reaction, aldehyde acetalization, and Friedel-Crafts reaction. The COF catalysts also had excellent recyclability.

Targeted classification of metal-organic frameworks in the Cambridge structural database (CSD).

Large-scale targeted exploration of metal-organic frameworks (MOFs) with characteristics such as specific surface chemistry or metal-cluster family has not been investigated so far. These definitions are particularly important because they can define the way MOFs interact with specific molecules (e.g. their hydrophilic/phobic character) or their physicochemical stability. We report here the development of algorithms to break down the overarching family of MOFs into a number of subgroups according to some of their key chemical and physical features. Available within the Cambridge Crystallographic Data Centre's (CCDC) software, we introduce new approaches to allow researchers to browse and efficiently look for targeted MOF families based on some of the most well-known secondary building units. We then classify them in terms of their crystalline properties: metal-cluster, network and pore dimensionality, surface chemistry (i.e. functional groups) and chirality. This dynamic database and family of algorithms allow experimentalists and computational users to benefit from the developed criteria to look for specific classes of MOFs but also enable users - and encourage them - to develop additional MOF queries based on desired chemistries. These tools are backed-up by an interactive web-based data explorer containing all the data obtained. We also demonstrate the usefulness of these tools with a high-throughput screening for hydrogen storage at room temperature. This toolbox, integrated in the CCDC software, will guide future exploration of MOFs and similar materials, as well as their design and development for an ever-increasing range of potential applications.

Core-Shell Gold Nanorod@Zirconium-Based Metal-Organic Framework Composites as in Situ Size-Selective Raman Probes.

Nanoparticle encapsulation inside zirconium-based metal-organic frameworks (NP@MOF) is hard to control, and the resulting materials often have nonuniform morphologies with NPs on the external surface of MOFs and NP aggregates inside the MOFs. In this work, we report the controlled encapsulation of gold nanorods (AuNRs) by a scu-topology Zr-MOF, via a room-temperature MOF assembly. This is achieved by functionalizing the AuNRs with poly(ethylene glycol) surface ligands, allowing them to retain colloidal stability in the precursor solution and to seed the MOF growth. Using this approach, we achieve core-shell yields exceeding 99%, tuning the MOF particle size via the solution concentration of AuNRs. The functionality of AuNR@MOFs is demonstrated by using the AuNRs as embedded probes for selective surface-enhanced Raman spectroscopy (SERS). The AuNR@MOFs are able to both take-up or block molecules from the pores, thereby facilitating highly selective sensing at the AuNR ends. This proof-of-principle study serves to present both the outstanding level of control in the synthesis and the high potential for AuNR@Zr-MOF composites for SERS.

Nitro-functionalized Bis(pyrazolate) Metal-Organic Frameworks as Carbon Dioxide Capture Materials under Ambient Conditions.

The metal-organic frameworks (MOFs) M(BPZNO2 ) (M=Co, Cu, Zn; H2 BPZNO2 =3-nitro-4,4'-bipyrazole) were prepared through solvothermal routes and were fully investigated in the solid state. They showed good thermal stability both under a N2 atmosphere and in air, with decomposition temperatures peaking up to 663 K for Zn(BPZNO2 ). Their crystal structure is characterized by 3D networks with square (M=Co, Zn) or rhombic (M=Cu) channels decorated by polar NO2 groups. As revealed by N2 adsorption at 77 K, they are micro-mesoporous materials with BET specific surface areas ranging from 400 to 900 m2 g-1 . Remarkably, under the mild conditions of 298 K and 1.2 bar, Zn(BPZNO2 ) adsorbs 21.8 wt % CO2 (4.95 mmol g-1 ). It shows a Henry CO2 /N2 selectivity of 15 and an ideal adsorbed solution theory (IAST) selectivity of 12 at p=1 bar. As a CO2 adsorbent, this compound is the best-performing MOF to date among those bearing a nitro group as a unique chemical tag. High-resolution powder X-ray diffraction at 298 K and different CO2 loadings revealed, for the first time in a NO2 -functionalized MOF, the insurgence of primary host-guest interactions involving the C(3)-NO2 moiety of the framework and the oxygen atoms of carbon dioxide, as confirmed by Grand Canonical Monte Carlo simulations. This interaction mode is markedly different from that observed in NH2 -functionalized MOFs, for which the carbon atom of CO2 is involved.

Computer-aided discovery of a metal-organic framework with superior oxygen uptake.

Current advances in materials science have resulted in the rapid emergence of thousands of functional adsorbent materials in recent years. This clearly creates multiple opportunities for their potential application, but it also creates the following challenge: how does one identify the most promising structures, among the thousands of possibilities, for a particular application? Here, we present a case of computer-aided material discovery, in which we complete the full cycle from computational screening of metal-organic framework materials for oxygen storage, to identification, synthesis and measurement of oxygen adsorption in the top-ranked structure. We introduce an interactive visualization concept to analyze over 1000 unique structure-property plots in five dimensions and delimit the relationships between structural properties and oxygen adsorption performance at different pressures for 2932 already-synthesized structures. We also report a world-record holding material for oxygen storage, UMCM-152, which delivers 22.5% more oxygen than the best known material to date, to the best of our knowledge.

A sol-gel monolithic metal-organic framework with enhanced methane uptake.

A critical bottleneck for the use of natural gas as a transportation fuel has been the development of materials capable of storing it in a sufficiently compact form at ambient temperature. Here we report the synthesis of a porous monolithic metal-organic framework (MOF), which after successful packing and densification reaches 259 cm3 (STP) cm-3 capacity. This is the highest value reported to date for conformed shape porous solids, and represents a greater than 50% improvement over any previously reported experimental value. Nanoindentation tests on the monolithic MOF showed robust mechanical properties, with hardness at least 130% greater than that previously measured in its conventional MOF counterparts. Our findings represent a substantial step in the application of mechanically robust conformed and densified MOFs for high volumetric energy storage and other industrial applications.

"Explosive" synthesis of metal-formate frameworks for methane capture: an experimental and computational study.

In this work, we show a solvent-free "explosive" synthesis (SFES) method for the ultrafast and low-cost synthesis of metal-formate frameworks (MFFs). A combination of experiments and in-depth molecular modelling analysis - using grand canonical Monte Carlo (GCMC) simulations - of the adsorption performance of the synthesized nickel-formate framework (Ni-FA) revealed extremely high quality products with permanent porosity, prominent CH4/N2 selectivity (ca. 6.0), and good CH4 adsorption capacity (ca. 0.80 mmol g-1 or 33.97 cm3 cm-3) at 1 bar and 298 K. This performance is superior to those of many other state-of-the-art porous materials.

Temperature Treatment of Highly Porous Zirconium-Containing Metal-Organic Frameworks Extends Drug Delivery Release.

Utilizing metal-organic frameworks (MOFs) as a biological carrier can lower the amount of the active pharmaceutical ingredient (API) required in cancer treatments to provide a more efficacious therapy. In this work, we have developed a temperature treatment process for delaying the release of a model drug compound from the pores of NU-1000 and NU-901, while taking care to utilize these MOFs' large pore volume and size to achieve exceptional model drug loading percentages over 35 wt %. Video-rate super-resolution microscopy reveals movement of MOF particles when located outside of the cell boundary, and their subsequent immobilization when taken up by the cell. Through the use of optical sectioning structured illumination microscopy (SIM), we have captured high-resolution 3D images showing MOF uptake by HeLa cells over a 24 h period. We found that addition of a model drug compound into the MOF and the subsequent temperature treatment process does not affect the rate of MOF uptake by the cell. Endocytosis analysis revealed that MOFs are internalized by active transport and that inhibiting the caveolae-mediated pathway significantly reduced cellular uptake of MOFs. Encapsulation of an anticancer therapeutic, alpha-cyano-4-hydroxycinnamic acid (α-CHC), and subsequent temperature treatment produced loadings of up to 81 wt % and demonstrated efficacy at killing cells beyond the burst release effect.

Adsorption and molecular siting of CO2, water, and other gases in the superhydrophobic, flexible pores of FMOF-1 from experiment and simulation.

FMOF-1 is a flexible, superhydrophobic metal-organic framework with a network of channels and side pockets decorated with -CF3 groups. CO2 adsorption isotherms measured between 278 and 313 K and up to 55 bar reveal a maximum uptake of ca. 6.16 mol kg-1 (11.0 mol L-1) and unusual isotherm shapes at the higher temperatures, suggesting framework expansion. We used neutron diffraction and molecular simulations to investigate the framework expansion behaviour and the accessibility of the small pockets to N2, O2, and CO2. Neutron diffraction in situ experiments on the crystalline powder show that CO2 molecules are favourably adsorbed at three distinct adsorption sites in the large channels of FMOF-1 and cannot access the small pockets in FMOF-1 at 290 K and oversaturated pressure at 61 bar. Stepped adsorption isotherms for N2 and O2 at 77 K can be explained by combining Monte Carlo simulations in several different crystal structures of FMOF-1 obtained from neutron and X-ray diffraction under different conditions. A similar analysis is successful for CO2 adsorption at 278 and 283 K up to ca. 30 bar; however, at 298 K and pressures above 30 bar, the results suggest even more substantial expansion of the FMOF-1 framework. The measured contact angle for water on an FMOF-1 pellet is 158°, demonstrating superhydrophobicity. Simulations and adsorption measurements also show that FMOF-1 is hydrophobic and water is not adsorbed in FMOF-1 at room temperature. Simulated mixture isotherms of CO2 in the presence of 80% relative humidity predict that water does not influence the CO2 adsorption in FMOF-1, suggesting that hydrophobic MOFs could hold promise for CO2 capture from humid gas streams.

Metal-Organic Nanosheets Formed via Defect-Mediated Transformation of a Hafnium Metal-Organic Framework.

We report a hafnium-containing MOF, hcp UiO-67(Hf), which is a ligand-deficient layered analogue of the face-centered cubic fcu UiO-67(Hf). hcp UiO-67 accommodates its lower ligand:metal ratio compared to fcu UiO-67 through a new structural mechanism: the formation of a condensed "double cluster" (Hf12O8(OH)14), analogous to the condensation of coordination polyhedra in oxide frameworks. In oxide frameworks, variable stoichiometry can lead to more complex defect structures, e.g., crystallographic shear planes or modules with differing compositions, which can be the source of further chemical reactivity; likewise, the layered hcp UiO-67 can react further to reversibly form a two-dimensional metal-organic framework, hxl UiO-67. Both three-dimensional hcp UiO-67 and two-dimensional hxl UiO-67 can be delaminated to form metal-organic nanosheets. Delamination of hcp UiO-67 occurs through the cleavage of strong hafnium-carboxylate bonds and is effected under mild conditions, suggesting that defect-ordered MOFs could be a productive route to porous two-dimensional materials.