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Accurate and efficient polymorph energy ranking with XDM-corrected hybrid DFT
Accurate and efficient computation of relative energies of molecular crystal polymorphs is of central importance for solid-state pharmaceuticals and in other technologically relevant fields. In recent years, dispersion-corrected density-functional theory (DFT) has emerged as the pre-eminent energy r...
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Published in: | CrystEngComm 2023-02, Vol.25 (6), p.953-96 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Accurate and efficient computation of relative energies of molecular crystal polymorphs is of central importance for solid-state pharmaceuticals and in other technologically relevant fields. In recent years, dispersion-corrected density-functional theory (DFT) has emerged as the pre-eminent energy ranking method for crystal structure prediction (CSP). However, planewave implementations of these methods are hindered by poor scaling for large unit cells and are limited to semi-local functionals that suffer from delocalisation error. In this work, we demonstrate that a recent implementation of the exchange-hole dipole moment (XDM) dispersion correction in the Fritz Haber Institute
ab initio
materials simulation (FHI-aims) package provides excellent performance for the energy ranking step of CSP. Thanks to its use of highly optimized numerical atom-centred orbitals, FHI-aims provides effectively linear scaling with system size and allows efficient use of hybrid density functionals with minimal basis-set incompleteness errors. We assess the performance of this methodology for the 26 compounds that formed the first 6 CSP blind tests. The hybrid results show significant improvements for 4/26 compounds, where delocalisation error affects the quality of predicted crystal energy landscapes.
Pairing the XDM dispersion model with hybrid density functionals shows significant improvements in the computed crystal energy landscapes for 4 of the 26 compounds appearing in the first six blind tests of crystal structure prediction. |
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ISSN: | 1466-8033 1466-8033 |
DOI: | 10.1039/d2ce01594c |