New academic paper makes front cover of Chemical Science
Why is this paper important?
MOFs are a well-established family of porous materials that are readily tunable through combining metal 'nodes' and organic 'struts' that connect to make a framework. Owing to their chemical diversity and structural variety, they have been intensely explored to target industrial challenges including gas storage and separation, catalysis, chemical sensing as well as drug delivery.
As of January 2020, a staggering ca. 100,000 MOFs exist in the Cambridge Structural Database (2020.0 CSD release) maintained by the Cambridge Crystallographic Data Centre (CCDC). This massive number of structures turns out to be a blessing and a curse. It’s a blessing because their chemical and physical diversity creates tremendous opportunities. It’s a curse because it creates the grand challenge of identifying the top-performing materials for a particular application on reasonable time scales. In this paper, in collaboration with the CCDC, we address this challenge by exploring the enormity of MOFs’ space by classifying them according to their key physical and chemical characteristics.
How did you do this?
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 CCDC’s 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.
What is the potential impact of your paper?
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 will guide future exploration of MOFs, as well as their computer-aided design and discovery for an ever-increasing range of potential applications.
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