Computational Prediction of ¹H and ¹³C NMR Chemical Shifts for Protonated Alkylpyrroles: Electron Correlation and Not Solvation is the Salvation

Abstract

Prediction of chemical shifts in organic cations is known to be a challenge. In this article we meet this challenge for α‐protonated alkylpyrroles, a class of compounds not yet studied in this context, and present a combined experimental and theoretical study of the 13C and 1H chemical shifts in three selected pyrroles. We have investigated the importance of the solvation model, basis set, and quantum chemical method with the goal of developing a simple computational protocol, which allows prediction of 13C and 1H chemical shifts with sufficient accuracy for identifying such compounds in mixtures. We find that density functional theory with the B3LYP functional is not sufficient for reproducing all 13C chemical shifts, whereas already the simplest correlated wave function model, Møller–Plesset perturbation theory (MP2), leads to almost perfect agreement with the experimental data. Treatment of solvent effects generally improves the agreement with experiment to some extent and can in most cases be accomplished by a simple polarizable continuum model. The only exception is the NH proton, which requires inclusion of explicit solvent molecules in the calculation.

A static and dynamic NMR study of 10‐hydrazino‐BODIPY

“…Table 1 results show the excellent agreement both between chemical shifts (for a similar work on protonated alkylpyrroles, see Lacerda et al [ 41 ] ) and SSCC between experimental data and calculated values (slightly better results those including solvent effects):…”

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

“…The polarizable consistent basis sets were all downloaded from the Basis Set Exchange database. 57,58 In the first study, 10 the cc-pVDZ basis set had been used for the geometry optimizations and the same geometry had been used in shielding calculations with different computational methods. In the present work, on the other hand, we used the more realistic and convenient scenario, that is, that one uses the same functional and type of basis set for the geometry optimization as for the following shielding calculation.…”

“…In the previous study 10 the comparison with experiment (Tables S1-S6) was done by fitting the calculated shielding constants α calc to the experimental chemical shifts δ exp according to Equation ( 1):…”

“…BHandH which is the functional with most HF exchange included however is the worst performing hybrid functional. B3LYP which was the functional tested in the original study 10 is not one of the best performing functionals. Two functionals give better result than the rest, O3LYP and B97-2, but none of them are Statistical data for the six best performing functionals are collected in Figure 6 and Table 1.…”

“…[6][7][8][9] A recent study on protonated alkylpyrroles employing both DFT with the B3LYP functional and MP2 with various different solvent models concluded that B3LYP did not provide results in sufficient agreement with experimental results in contrast to MP2. 10 However, for larger compounds like, for example, oligomers of alkylpyrroles MP2 calculations are still computationally too demanding for routine applications, which makes it necessary to find cheaper alternatives. In the previous work, on the other hand, only the performance of the popular B3LYP exchange-correlation functional was investigated, which did not allow to make a general statement about the performance of DFT in such calculations.…”