From computational high-throughput screenings to the lab: taking metal–organic frameworks out of the computer. Issue 27 (22nd June 2022)

• Record Type: Journal Article
• Authors: Li, Aurelia; Bueno-Perez, Rocio; Madden, David; Fairen-Jimenez, David
• Is Part Of: Chemical science. Volume 13:Issue 27(2022)
• Page Start: 7990
• Page End: 8002
• Publication Date: 2022-06-22
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/d2sc01254e
• Languages: English
• ISSNs: 2041-6520

Abstract

Abstract : Computational high-throughput screenings (HTS) have become a standard method of sieving the vast amount of metal–organic frameworks (MOFs) data. But not many HTS studies have been able to bring MOFs to the lab. Abstract : 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.