(134b) Unraveling Complex Catalytic Chemistries through Automated Mechanism Generation and Reaction Pathway Analysis

Catalytic reactions are often characterized by their complexity and involve hundreds of interacting species in more than thousands of reactions. However, a detailed elucidation of reaction pathways and mechanisms is key in understanding complex catalytic chemistries and developing new catalysts for improved yields and selectivity of the desired products. In this presentation, the application of microkinetic modeling based on a detailed reaction mechanism to understand zeolite-catalyzed conversion is demonstrated. First, plausible elementary reactions were considered and categorized into different types, and the reaction rules for each reaction type were formulated. Complex reaction networks comprising all possible elementary reactions were then constructed based on the reaction rules via an automated reaction network generator. To reduce the computational cost for estimating rate coefficients in Arrhenius form for all the elementary steps, the Evans-Polanyi relationship was used to relate activation energy to heat of reaction for each type of elementary reaction. The mechanistic model was able to capture the yields and selectivities to a wide range of major and minor products.

Based on this basic framework for reaction pathway analysis, the development of a computational discovery platform for identifying and analyzing novel (bio)catalytic pathways to target chemicals will also be discussed. Automated network generation that defines and implements the chemistry of generalized functions based on knowledge compiled in existing (bio)catalytic databases is employed. The output is a set of compounds and the pathways connecting them, both known and novel. To identify the most promising of the thousands of different pathways generated, automated network generation algorithms are linked with pathway evaluation tools. The method for automated generation of pathways creates novel compounds and pathways that have not been reported in biocatalytic or catalytic databases.