Constructing and interpreting volcano plots and activity maps to navigate homogeneous catalyst landscapes

Area of Science:

• Catalysis
• Computational Chemistry
• Materials Science

Background:

• Volcano plots and activity maps are established tools in catalysis.
• Their application to homogeneous catalysis has been limited but shows great potential.
• Predicting catalyst performance is crucial for developing new catalytic systems.

Purpose of the Study:

• To provide a protocol for constructing volcano plots and activity maps for homogeneous catalysis.
• To introduce a Python code, volcanic, that automates the process.
• To enable a holistic assessment of homogeneous catalyst performance.

Main Methods:

• Utilizing density functional theory (DFT) computations to model catalytic reaction profiles.
• Building volcano plots and activity maps from linear free energy scaling relationships.
• Employing the automated Python code 'volcanic' for data postprocessing.

Main Results:

• A step-by-step protocol for generating volcano plots and activity maps from DFT data.
• Demonstration of how these tools can estimate and predict catalyst performance.
• Successful automation of the plot/map generation process using the 'volcanic' code.

Conclusions:

• Volcano plots and activity maps offer a powerful, holistic approach to understanding homogeneous catalysis.
• The provided protocol and code facilitate the application of these tools for both explanatory and screening purposes.
• This methodology aids in the rational design and optimization of homogeneous catalysts.