Multidimensional Lewis Acidity: a consistent data set of chloride, hydride, methide, water and ammonia affinities for 183 p-block element Lewis Acids
The computed fluoride ion affinity (FIA) is a widely applied descriptor to gauge Lewis acidity. Like every other single-parameter Lewis acidity scale, the FIA metric suffers from the one-dimensionality, that prohibits addressing Lewis acidity by the multidimensionality it inherently requires (i. e.,...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article (Journal) |
| Language: | English |
| Published: |
2021
|
| In: |
ChemPhysChem
Year: 2021, Volume: 22, Issue: 10, Pages: 935-943 |
| ISSN: | 1439-7641 |
| DOI: | 10.1002/cphc.202100150 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1002/cphc.202100150 Verlag, kostenfrei, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/cphc.202100150 
|
| Author Notes: | Philipp Erdmann and Lutz Greb |
| Summary: | The computed fluoride ion affinity (FIA) is a widely applied descriptor to gauge Lewis acidity. Like every other single-parameter Lewis acidity scale, the FIA metric suffers from the one-dimensionality, that prohibits addressing Lewis acidity by the multidimensionality it inherently requires (i. e., reference Lewis base dependency). However, a systematic screening of computed affinities other than the FIA is much less developed. Herein, we extended our CCSD(T)/CBS benchmark of different density functionals and the DLPNO-CCSD(T) method for chloride (CIA), methide (MIA), hydride (HIA), water (WA), and ammonia (AA) affinities. The best performing methods are subsequently applied to yield nearly 800 affinities for 183 p-block element compounds of group 13-16 with an estimated accuracy of <10 kJ mol−1. The study‘s output serves as a consistent library for qualitative analyses and a training set for future statistical approaches. A first holistic correlation analysis underscores the need for a multidimensional description of Lewis acidity. |
|---|---|
| Item Description: | Gesehen am 17.04.2023 |
| Physical Description: | Online Resource |
| ISSN: | 1439-7641 |
| DOI: | 10.1002/cphc.202100150 |