Towards an Accurate Prediction of Nitrogen Chemical Shifts by Density Functional Theory and Gauge‐Including Atomic Orbital. Issue 2 (19th November 2018)

• Record Type: Journal Article
• Authors: Gao, Peng; Wang, Xingyong; Yu, Haibo
• Is Part Of: Advanced theory and simulations. Volume 2:Issue 2(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-11-19
• Subjects: density functional theory -- gauge‐including atomic orbitals -- linear regression -- nitrogen chemical shift -- nuclear magnetic resonance spectroscopy -- solvent effects; Science -- Simulation methods -- Periodicals; Science -- Methodology -- Periodicals; Engineering -- Simulation methods -- Periodicals; Engineering -- Methodology -- Periodicals; 507.21
• DOI: 10.1002/adts.201800148
• Languages: English
• ISSNs: 2513-0390

Abstract

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 CHCl3 and dimethyl sulfoxide (DMSO), respectively. Moreover, another set of scaling factors for –NH2 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. Abstract : Taking advantage of the wide range of the nitrogen chemical shift and its high sensitivity to the environment, an efficient, yet accurate, computational protocol for predicting 15 N chemical shifts based on linear regression is proposed. This protocol together with previous work on 1 H and 13 C chemical shift predictions will serve as a robust tool in structural elucidation.