Theoretical Investigation and Prediction of Carbon-13 and Proton Nuclear Magnetic Resonance Chemical Shifts in Aromatic and new Organometallic Sandwich Systems

Abstract

This study establishes and validates a densitiy functional theory (DFT)-based protocol for reliable prediction of ¹³C and ¹H nuclear magnetic resonance (NMR) chemical shifts. Aromatic benchmark systems (benzene, toluene, nitrobenzene, aniline and phenol) were investigated using the B3LYP/TZVP level of theory combined with the Gauge-Including Atomic Orbital (GIAO) method to verify the accuracy of the computational approach against experimental and literature data. The results show excellent linear correlation (R² > 0.98) and low mean absolute errors, with systematic deviations effectively corrected through linear regression-based scaling. After validation with aromatics, the method was applied to three recently synthesized organometallic organometallic compounds – pentaisopropylcyclopentadienyl-lithium (⁵Cp*Li), -aluminium (⁵Cp*Al) and a Li-Al heterobimetallic dimetallocene – for which no experimental NMR data are currently available. Independent calculations using Gaussian 09 and ORCA 6.0.1 yielded near-perfect agreement for all organometallics (R² > 0.99), confirming the reproducibility and robustness of the approach. A comparative test with a larger basis set (QZVP) for the aromatic references revealed no improvement in accuracy but significantly higher computational cost, supporting the efficiency of TZVP for this type of NMR prediction. Overall, the study demonstrates that the validated DFT protocol is well suited for predicting and interpreting NMR chemical shifts in novel heterobimetallic sandwich systems.