Ultra-fast hybrid method for predicting chemical shifts of ¹³C: hybrid strategy with dynamic internal patterns and linear parameters

Abstract

NMR spectroscopy is an essential tool for molecular characterization and structure elucidation, but the accurate prediction of chemical shifts in complex systems is still a challenge. In this study, we developed an ultrafast predictive model for ¹³C chemical shifts, applied to a phenylpiperazine derivative, combining linear scaling and three internal standards: TMS, methanol and benzene, using the HF/3-21G/MPW1PW91/6-31G(d) method. The proposed computational model, using methanol as the internal standard, reduced the average errors by more than 50%, surpassing the computationally intensive methods described in the literature.