Benchmarking Structures and UV-Vis Spectra of Iron Complexes Against Experimental Data.

Area of Science:

• Computational Chemistry
• Inorganic Chemistry
• Spectroscopy

Background:

• Accurate prediction of molecular geometry and UV-vis spectra is crucial for understanding transition metal complexes.
• Iron coordination complexes are vital in catalysis and biological systems, necessitating reliable theoretical models.

Purpose of the Study:

• To evaluate and rank various theoretical methods for predicting the ground-state geometry of mononuclear iron coordination complexes.
• To assess the performance of different density functionals in time-dependent density functional theory (TD-DFT) for UV-vis spectral prediction of these complexes.

Main Methods:

• Evaluated 17 computational approaches for geometry optimization using experimentally characterized iron complexes.
• Performed TD-DFT calculations on optimized structures with 13 density functionals to predict UV-vis spectra.
• Ranked methods based on accuracy of excitation energies and spectral shape reproduction.

Main Results:

• The meta-hybrid functional TPSSh(D4) showed the best performance for geometry optimization.
• For UV-vis spectra, O3LYP yielded the most accurate excitation energies.
• The meta-GGA functional revM06-L demonstrated superior performance in reproducing the experimental spectral shape.

Conclusions:

• TPSSh(D4) is recommended for geometry optimizations of iron coordination complexes.
• A combination of O3LYP for excitation energies and revM06-L for spectral shape is suggested for accurate UV-vis spectral prediction.
• This benchmark provides essential guidance for computational chemists studying iron complexes.