Systematic assessment of DFT methods for geometry optimization of mononuclear platinum-containing complexes.

Platinum is used extensively as a catalyst for a wide variety of chemical reactions, though its scarcity and price present limitations to expansions of its use. To understand the origin of platinum's versatility-with the goals of both improving the efficiency of existing catalysts and mimicking its reactivity with more abundant metals-the mechanisms of platinum-catalyzed chemical reactions must be understood structural and spectroscopic characterization of these catalysts under conditions. Such data, typically consisting of complex mixtures of species, often prove challenging to interpret, inviting the aid of chemical theory. DFT calculations in particular have proven successful at predicting structural and spectroscopic parameters of transition metal species, though a thorough investigation of how these methods perform for platinum-based complexes has yet to be undertaken. Herein, we evaluated the performance of geometry optimization for five commonly used functionals (BP86, PBE, B3LYP, PBE0, and TPSSh) in combination with various ligand basis sets, relativistic approximations, and solvation and dispersion models. We applied these DFT methods to a training set of 14 platinum-containing complexes with varying sizes, oxidation states, and number and type of ligands and determined that the best-performing method was the PBE0 functional together with the def2-TZVP basis set for the ligand atoms, the ZORA relativistic approximation, and solvation and dispersion corrections. The ability of this DFT methodology to accurately predict metrical parameters was confirmed using two case studies, most notably by comparing the DFT optimized geometry of a previously uncharacterized complex to newly collected EXAFS data, which showed excellent agreement.