We report the generation and characterization of the most complete collection of metal–organic frameworks (MOFs) maintained and updated, for the first time, by the Cambridge Crystallographic Data ...Centre (CCDC). To set up this subset, we asked the question “what is a MOF?” and implemented a number of “look-for-MOF” criteria embedded within a bespoke Cambridge Structural Database (CSD) Python API workflow to identify and extract information on 69 666 MOF materials. The CSD MOF subset is updated regularly with subsequent MOF additions to the CSD, bringing a unique record for all researchers working in the area of porous materials around the world, whether to perform high-throughput computational screening for materials discovery or to have a global view over the existing structures in a single resource. Using this resource, we then developed and used an array of computational tools to remove residual solvent molecules from the framework pores of all the MOFs identified and went on to analyze geometrical and physical properties of nondisordered structures.
The synthetic flexibility of metal–organic frameworks (MOFs) with high loading capacities and biocompatibility makes them ideal candidates as drug delivery systems (DDSs). Here, we report the use of ...CAU-7, a biocompatible bismuth-based MOF, for the delivery of two cancer drugs, sodium dichloroacetate (DCA) and α-cyano-4-hydroxycinnamic acid (α-CHC). We achieved loadings of 33 and 9 wt % for DCA and α-CHC, respectively. Interestingly, CAU-7 showed a gradual release of the drugs, achieving a release time of up to 17 days for DCA and 31 days for α-CHC. We then performed mechanical and thermal amorphization processes to attempt to delay the delivery of guest molecules even more. With the thermal treatment, we were able to achieve an outstanding 32% slower release of α-CHC from the thermally treated CAU-7. Using in vitro studies and endocytosis inhibitors, confocal microscopy, and fluorescence-activated cell sorting, we also demonstrated that CAU-7 was successfully internalized by cancer cells, partially avoiding lysosome degradation. Finally, we showed that CAU-7 loaded either with DCA or α-CHC had a higher therapeutic efficiency compared with the free drug approach, making CAU-7 a great option for biomedical application.
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.
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.
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.
Chemical warfare agents (CWAs) are regarded as a critical challenge in our society. Here, we use a high-throughput computational screening strategy backed up by experimental validation to identify ...and synthesize a promising porous material for CWA removal under humid conditions. Starting with a database of 2,932 existing metal–organic framework (MOF) structures, we selected those possessing cavities big enough to adsorb well-known CWAs such as sarin, soman, and mustard gas as well as their nontoxic simulants. We used Widom method to reduce significantly the simulation time of water adsorption, allowing us to shortlist 156 hydrophobic MOFs where water will not compete with the CWAs to get adsorbed. We then moved to grand canonical Monte Carlo (GCMC) simulations to assess the removal capacity of CWAs. We selected the best candidates in terms of performance but also in terms of chemical stability and moved to synthesis and experimental breakthrough adsorption to probe the predicted, excellent performance. This computational-experimental work represents a fast and efficient approach to screen porous materials in applications that involve the presence of moisture.
Abstract
Stimuli-responsive behaviors of flexible metal–organic frameworks (MOFs) make these materials promising in a wide variety of applications such as gas separation, drug delivery, and molecular ...sensing. Considerable efforts have been made over the last decade to understand the structural changes of flexible MOFs in response to external stimuli. Uniform pore deformation has been used as the general description. However, recent advances in synthesizing MOFs with non-uniform porous structures, i.e. with multiple types of pores which vary in size, shape, and environment, challenge the adequacy of this description. Here, we demonstrate that the CO
2
-adsorption-stimulated structural change of a flexible MOF, ZIF-7, is induced by CO
2
migration in its non-uniform porous structure rather than by the proactive opening of one type of its guest-hosting pores. Structural dynamics induced by guest migration in non-uniform porous structures is rare among the enormous number of MOFs discovered and detailed characterization is very limited in the literature. The concept presented in this work provides new insights into MOF flexibility.
Metal–organic frameworks (MOFs) are one of the most researched designer materials today, as their high tunability offers scientists a wide space to imagine all kinds of possible structures. Their ...uniquely flexible customisability spurred the creation of hypothetical datasets and the syntheses of more than 100 000 MOFs officially reported in the Cambridge Structural Database. To scan such large numbers of MOFs, computational high-throughput screenings (HTS) have become the customary method to identify the most promising structure for a given application, and/or to spot useful structure–property relationships. However, despite all these data-mining efforts, only a fraction of HTS studies have identified synthesisable top-performing MOFs that were then further investigated in the lab. In this perspective, we review these specific cases and suggest possible steps to push future HTS more systematically towards synthesisable structures.
As rationally designable materials, the variety and number of synthesised metal-organic cages (MOCs) and organic cages (OCs) are expected to grow in the Cambridge Structural Database (CSD). In this ...regard, two of the most important questions are, which structures are already present in the CSD and how can they be identified? Here, we present a cage mining methodology based on topological data analysis and a combination of supervised and unsupervised learning that led to the derivation of - to the best of our knowledge - the first and only MOC dataset of 1839 structures and the largest experimental OC dataset of 7736 cages, as of March 2022. We illustrate the use of such datasets with a high-throughput screening of MOCs and OCs for xenon/krypton separation, important gases in multiple industries, including healthcare.
We mined the Cambridge Structural Database for porous cages using topological data analysis, which resulted in the first and only dataset of metal-organic cages and the largest dataset of organic cages.
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