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

Area of Science:

• Computational Chemistry
• Materials Science
• Catalysis

Background:

• Predicting catalytic efficiency is crucial for developing new materials.
• Density Functional Theory (DFT) offers quantitative insights but lacks direct efficiency metrics.
• A tool is needed to bridge theoretical calculations and experimental catalyst performance.

Purpose of the Study:

• To develop and validate an Efficiency Conceptualization Model (ECM) for predicting catalyst efficiency.
• To utilize quantum mechanical calculations to determine catalyst efficiency in terms of turnover frequency (TOF).
• To assess the performance of 26 transition metal water oxidation catalysts under standardized conditions.

Main Methods:

• Developed the Efficiency Conceptualization Model (ECM).
• Employed quantum mechanical calculations.
• Evaluated 26 transition metal catalysts under consistent temperature, pressure, and pH.

Main Results:

• The Fe-based catalyst [Fe(OTf)2(Me2Pytacn)] (MWOC-17) showed high activity and stability.
• Ir-based catalysts [Cp*Ir(κ2-N,O)X] (MWOC-23, MWOC-24) exhibited high computed turnover numbers (TONs) of 406 and 490.
• The Co-based catalyst [Co(12-TMC)]2+ (MWOC-19) displayed the lowest TONs (19), aligning with experimental data.

Conclusions:

• The ECM successfully predicts catalyst efficiency using quantum mechanical principles.
• Computational results corroborate previous experimental findings for water oxidation catalysts.
• The study highlights promising Fe and Ir-based catalysts for efficient water oxidation.