How reliable is DFT for predicting the redox potentials in polypyridine-based hydrogen evolution catalysts?

Area of Science:

• Computational chemistry
• Materials science
• Catalysis

Background:

• Earth-abundant 3d metal polypyridine complexes are promising for hydrogen evolution reaction (HER) catalysis.
• Accurate computational prediction of redox potentials is crucial for discovering new catalysts but is hindered by functional variations.

Purpose of the Study:

• To benchmark various exchange-correlation functionals for accurate redox potential calculations in metal-based HER catalysts.
• To identify reliable computational methodologies for discovering novel and efficient catalytic modules.

Main Methods:

• Systematic evaluation of 10 GGA functionals (pure, hybrid, dispersion-corrected, long-range corrected) with all-electron and ECP-corrected basis sets.
• Applied to a benchmark set of 15 experimentally characterized polypyridine complexes containing Co, Fe, Ni, and Cu ions.
• Calculated redox potentials for the electron transfer process critical to hydrogen generation.

Main Results:

• Identified B3LYP-Def2TZVP, B3LYP-LANL2DZ(f)/6-311++G**, and M06-LANL2DZ(f)/6-311++G** as top-performing methods with low mean average errors (0.24-0.26 V).
• Methodologies showed particular promise for iron-based catalysts, aligning with iron's abundance and low toxicity.
• Demonstrated the effectiveness of the chosen functionals in predicting redox potentials for diverse catalytic complexes.

Conclusions:

• The identified computational methods provide accurate and reliable predictions for redox potentials in polypyridine-based HER catalysts.
• These validated methodologies can accelerate the screening and discovery of novel, efficient, and sustainable catalysts for hydrogen production.
• The findings support the use of computational chemistry in advancing clean energy technologies through catalyst design.