Journal article

CHAL336 Benchmark Set: How Well Do Quantum-Chemical Methods Describe Chalcogen-Bonding Interactions?

Nisha Mehta, Thomas Fellowes, Jonathan M White, Lars Goerigk

JOURNAL OF CHEMICAL THEORY AND COMPUTATION | AMER CHEMICAL SOC | Published : 2021

Abstract

We present the CHAL336 benchmark set-the most comprehensive database for the assessment of chalcogen-bonding (CB) interactions. After careful selection of suitable systems and identification of three high-level reference methods, the set comprises 336 dimers each consisting of up to 49 atoms and covers both σ- and π-hole interactions across four categories: chalcogen-chalcogen, chalcogen-π, chalcogen-halogen, and chalcogen-nitrogen interactions. In a subsequent study of DFT methods, we re-emphasize the need for using proper London dispersion corrections when treating noncovalent interactions. We also point out that the deterioration of results and systematic overestimation of interaction ene..

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Grants

Awarded by Australian Research Council


Awarded by National Computational Infrastructure (NCI) Facility within the National Computational Merit Allocation Scheme


Awarded by Research Platform Services (ResPlat) at The University of Melbourne


Awarded by University of Melbourne


Funding Acknowledgements

We thank Prof. Jan M. L. Martin for an insightful discussion about Dunning basis sets. This work was supported by the Australian Research Council within the Discovery Project scheme (DP180101413). N.M. acknowledges a Melbourne International Engagement Award (MIEA) offered through the Melbourne India Postgraduate Program and a Melbourne Research Scholarship. T.F. acknowledges the Australian Commonwealth Government for a Research Training Program Scholarship. L.G. is grateful for generous allocations of computational resources from the National Computational Infrastructure (NCI) Facility within the National Computational Merit Allocation Scheme (Project fk5) and Research Platform Services (ResPlat) at The University of Melbourne (Project punim0094). This research was also supported by the sustaining and strengthening merit-based access to the NCI LIEF Grant (LE190100021) facilitated by The University of Melbourne.