Toward molecular catalysts by computer.

Area of Science:

• Catalysis
• Computational Chemistry
• Materials Science

Background:

• Rational catalyst design requires precise control over ligand electronic and steric properties.
• Thermodynamic properties (redox potentials, pKa, hydricities) are foundational for catalyst design.
• Computational methods offer accurate predictions of these properties.

Purpose of the Study:

• To present a framework for systematic molecular catalyst design using thermodynamic properties.
• To illustrate the application of this framework for key energy-related reactions.
• To demonstrate the feasibility of computer-aided catalyst design.

Main Methods:

• Utilizing density functional theory (DFT) to calculate thermodynamic properties.
• Developing correlations between thermodynamic properties and electronic structure.
• Employing free energy maps and optimization functionals to predict catalyst performance.

Main Results:

• DFT accurately predicts redox potentials (∼0.06 eV), pKa (∼1 unit), and hydricities (1-2 kcal/mol).
• Correlations were established between thermodynamic properties and metal center electronic configurations.
• A computational approach was developed to predict optimal catalyst design points based on thermodynamic criteria.

Conclusions:

• A systematic, computer-driven framework for molecular catalyst design is established.
• This approach enables a priori distinction between desirable and undesirable catalytic pathways.
• The design of molecular electrocatalysts by computer is imminent, with future work focusing on ligand identification.