EPR Spectroscopy of Cu(II) Complexes: Prediction of g-Tensors Using Double-Hybrid Density Functional Theory

Computational electron paramagnetic resonance (EPR) spectroscopy is an important field of applied quantum chemistry that contributes greatly to connecting spectroscopic observations with the fundamental description of electronic structure for open-shell molecules. However, not all EPR parameters can be predicted accurately and reliably for all chemical systems. Among transition metal ions, Cu(II) centers in inorganic chemistry and biology, and their associated EPR properties such as hyperfine coupling and g-tensors, pose exceptional difficulties for all levels of quantum chemistry. In the present work, we approach the problem of Cu(II) g-tensor calculations using double-hybrid density functional theory (DHDFT). Using a reference set of 18 structurally and spectroscopically characterized Cu(II) complexes, we evaluate a wide range of modern double-hybrid density functionals (DHDFs) that have not been applied previously to this problem. Our results suggest that the current generation of DHDFs consistently and systematically outperform other computational approaches. The B2GP-PLYP and PBE0-DH functionals are singled out as the best DHDFs on average for the prediction of Cu(II) g-tensors. The performance of the different functionals is discussed and suggestions are made for practical applications and future methodological developments.

Automated summary

Computational electron paramagnetic resonance (EPR) spectroscopy plays an important role in connecting spectroscopic observations with the fundamental description of electronic structure. This study focuses on Cu(II) complexes and investigates the performance of double-hybrid density functionals (DHDFs) for predicting g-tensors. The results show that current DHDFs consistently outperform other computational approaches, with B2GP-PLYP and PBE0-DH identified as the best DHDFs for predicting Cu(II) g-tensors.