Artificial photosynthesis requires efficient catalysts or electrocatalysts to reduce carbon dioxide into fuels as the counter reaction to water oxidation. Our group has chosen a classic model-system known to produce CO from electrocatalytic CO2 reduction in acetonitrile - M(4-Ar-tpy)22+, where 4-aryl-tpy is 4-aryl-2,2':6',2''-terpyridine and M is a first-row metals, to investigate how slight changes in the 4-aryl ligand impact the reduction potentials of the complexes to which they are attached. While their ease of synthesis is major practical advantage, more importantly, our recent studies revealed a strong correlation between the Hammett parameters of the 4-aryl group and all of the multiple metal/ligand reduction potentials. Ultimately, we are able to fine-tune the CO2 electrocatalytic reduction onset potential simply by modifying the 4-aryl group of the terpyridine ligand over a range of several hundred mV. Inspired by these results, we sought to develop a rapid computational model to predict the reduction potential of M(4-Ar-tpy)22+, or related complexes, as they could be advantageous, especially in those cases where experimentally tabulated Hammett parameters are not available and where synthesis may not be economically feasible or rapid. Herein, we will report our initial findings exploring some low computational cost model systems as well as those of new ligands using ORCA and their correlation to experimentally determined reduction potentials.

Low cost computational model for estimating homoleptic metal-terpyridine complex reduction potentials

ACS Spring Meeting 2021

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