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The best density functional theory functional for the prediction of 1 H and 13 C chemical shifts of protonated alkylpyrroles.

Sarah L V ZahnOle HammerichPoul Erik HansenStephan P A Sauer
Published in: Journal of computational chemistry (2021)
The prediction of 13 C chemical shifts can be challenging with density functional theory (DFT). In this study 39 different functionals and three different basis sets were tested on three neutral alkylpyrroles and their corresponding protonated species. The calculated shielding constants were compared to experimental data and results from previous calculations at the MP2. We find that the meta-hybrid functional TPSSh with either the Pople style basis set 6-311++G(2d,p) or the polarization consistent basis set pcSseg-1 gives the best results for the 13 C chemical shifts, whereas for the 1 H chemical shifts it is the TPSSh functional with either the 6-311++G(2d,p) or pcSseg-2 basis set. Including an explicit solvent molecule hydrogen bonded to NH in the alkylpyrroles improves the results slightly for the 13 C chemical shifts. On the other hand, for 1 H chemical shifts the opposite is true. Compared to calculations at the MP2 level none of the DFT functionals can compete with MP2 for the 13 C chemical shifts but for the 1 H chemical shifts the investigated DFT functionals are shown to give better agreement with experiment than MP2 calculations.
Keyphrases
  • density functional theory
  • molecular dynamics
  • machine learning
  • molecular docking
  • deep learning