Efficiency Conceptualization Model: A Theoretical Method for Predicting the Turnover of Catalysts

In recent times, the theoretical prediction of catalytic efficiency is of utmost urgency. With the advent of density functional theory (DFT), reliable computations can delineate a quantitative aspect of the study. To this state-of-the-art approach, valuable incorporation would be a tool that can acknowledge the efficiency of a catalyst. In the current work, we developed the efficiency conceptualization model (ECM) that utilizes the quantum mechanical tool to achieve efficiency in terms of turnover frequency (TOF). Twenty-six experimentally designed transition metal (TM) water oxidation catalysts were chosen under similar experimental conditions of temperature, pressure, and pH to execute the same. The computations conclude that the Fe-based [Fe(OTf)₂(Me₂Pytacn)] (MWOC-17) is a highly active catalyst and, therefore, can endure for more time in the catalytic cycle. Our results conclude that the Ir-based catalysts [Cp^*Ir(κ²-N,O)X] with MWOC-23: X=Cl; and MWOC-24: X=NO₃ report the highest computed turnover numbers (TONs), $$ of 406 and 490 against the highest experimental TONs, $$ of 1200 and 2000 respectively, whereas the Co-based [Co(12-TMC)]²⁺ (MWOC-19) has the lowest TONs ( $$ =19, τ_{experimental TON}=16) among the chosen catalysts and thereby successful in corroborating the previous experimental results.