AARON: An Automated Reaction Optimizer for New Catalysts

Area of Science:

• Computational Chemistry
• Catalysis
• Organic Chemistry

Background:

• Computational quantum chemistry is vital for understanding asymmetric catalyst performance.
• Predicting reaction selectivity necessitates extensive geometry optimization of transition states and intermediates.
• Manual optimization is time-consuming and limits computational screening of catalysts.

Purpose of the Study:

• To introduce AARON (An Automated Reaction Optimizer for New catalysts), an open-source toolkit.
• To automate quantum mechanical geometry optimization and characterization for asymmetric catalysis.
• To accelerate computational workflows for catalyst screening.

Main Methods:

• Developed AARON, an automated workflow integrating quantum mechanical calculations.
• Utilized object-oriented Perl modules (AaronTools) for molecular structure manipulation.
• Interface with electronic structure packages to perform geometry optimizations and characterizations.

Main Results:

• AARON successfully automates the optimization and characterization of transition states and intermediates.
• Demonstrated accelerated quantum chemical workflows for catalyst screening.
• Presented applications in both organocatalyzed and transition-metal-catalyzed reactions.

Conclusions:

• AARON significantly reduces the manual effort required for computational catalyst design.
• The toolkit enables efficient prediction of catalyst activity and selectivity.
• AARON facilitates broader exploration of potential catalysts for asymmetric reactions.