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Towards an Accurate Prediction of Nitrogen Chemical Shifts by Density Functional Theory and Gauge‐Including Atomic Orbital
Author(s) -
Gao Peng,
Wang Xingyong,
Yu Haibo
Publication year - 2019
Publication title -
advanced theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.068
H-Index - 17
ISSN - 2513-0390
DOI - 10.1002/adts.201800148
Subject(s) - chemical shift , density functional theory , chemistry , scaling , computational chemistry , transferability , tautomer , nitrogen , perturbation theory (quantum mechanics) , protonation , organic chemistry , mathematics , physics , quantum mechanics , statistics , geometry , logit , ion
Abstract An efficient, yet accurate, computational protocol for predicting nitrogen nuclear magnetic resonance (NMR) chemical shifts based on density functional theory and the gauge‐including atomic orbital approach is proposed. A database of small and relatively rigid compounds containing nitrogen atoms is compiled. Scaling factors for the linear correlation between experimental 15 N chemical shifts and calculated isotropic shielding constants are systematically investigated with seven different levels of theory in both chloroform and dimethyl sulfoxide, two commonly used solvents for NMR experiments. The best method yields a root‐mean‐square deviation of about 5.30 and 7.00 ppm in CHCl 3 and dimethyl sulfoxide (DMSO), respectively. Moreover, another set of scaling factors for –NH 2 chemical shifts is also proposed based on a separate database with three levels of theory. Furthermore, it is encouraging that a reasonable transferability for the linear correlation is found between these two solvents. This finding will enable broader applications of the developed empirical scaling factors to other commonly used solvents in NMR experiments. The consistency between theoretical predictions and experimental results for structural elucidations is illustrated for selected examples including regioisomers, tautomers, oxidation states, and protonated structures.