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Abstract
First-principles crystal structure prediction (CSP) is the most powerful approach for materials discovery, enabling the prediction and evaluation of properties of new solid phases based only on a diagram of their underlying components. Here, we present the first CSP-based discovery of metal–organic frameworks (MOFs), offering a broader alternative to conventional techniques, which rely on geometry, intuition, and experimental screening. Phase landscapes were calculated for three systems involving flexible Cu(II) nodes, which could adopt a potentially limitless number of network topologies and are not amenable to conventional MOF design. The CSP procedure was validated experimentally through the synthesis of materials whose structures perfectly matched those found among the lowest-energy calculated structures and whose relevant properties, such as combustion energies, could immediately be evaluated from CSP-derived structures.
Original language | English |
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Pages (from-to) | 3515-3525 |
Number of pages | 11 |
Journal | Journal of the American Chemical Society |
Volume | 145 |
Issue number | 6 |
Early online date | 31 Jan 2023 |
DOIs | |
Publication status | Published - 15 Feb 2023 |
Bibliographical note
Funding:T.F. would like to acknowledge the support of the Natural Sciences and Engineering Research Council (NSERC) Polanyi Award (JCP 562908–2022), the Discovery Grant (RGPIN-2017-06467), and the Canada Tier-1 Research Chair. T.F. also thanks the Leverhulme Trust for the Leverhulme International Professorship at the University of Birmingham. Y.X. and M.A. thank the National Science Center of Poland (NCN) for grant 2018/31/D/ST5/03619 as well as for access to the Prometheus supercomputer, PLGrid, Poland. Y.X., M.A., and T.F. would like to acknowledge access to Cedar supercomputer in Compute Canada. M.A. and A.J.M. acknowledge the networking support and access to ARCHER and ARCHER2 supercomputers provided through the UKCP consortium and funded by EPSRC, grant EP/P022561/1. A.J.M., M.A., and J.P.D. would like to acknowledge some of the computations performed in this paper using the University of Birmingham’s BlueBEAR HPC service, which provides high-performance computing service to the University’s research community. Finally, A.J.M. and J.P.D. acknowledge the networking support provided by the UK EPSRC’s Collaborative Computational Project (CCP) 9 (EP/T026375/1) and CCP–NMR Crystallography (EP/T026642/1).
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Collaborative Computational Project in NMR Crystallography
Morris, A. (Principal Investigator)
Engineering & Physical Science Research Council
6/05/20 → 5/05/25
Project: Research Councils