Automated Reaction Exploration of Ozonation Processes for Model Olefins in Water

Comprehensive evaluation of pollutant abatement in chemical oxidation processes and identification of potentially hazardous transformation products is a fundamental challenge in water and wastewater treatment. Here, we demonstrate how high-throughput computational chemistry enables the elucidation of reaction pathways via automated, quantum chemistry-based chemical reaction network (CRN) explorations. We evaluated the predictive capabilities of this computational approach using the Software for Chemical Interaction Networks (SCINE) for studying the reactions of ozone with two model olefins, ethene and tetramethylethene, in aqueous solution. Following a benchmarking of quantum chemical methodology for structure optimization and energy calculations, we generated CRNs containing hundreds of compounds and thousands of reactions, identified reaction mechanisms, and evaluated product formation kinetics through microkinetic modeling. These CRN explorations led to the correct reproduction of experimental evidence for mechanisms and products of olefin ozonolyis for reactions of ozone and ethene based solely on defining the reactants and their initial concentrations. The study of reactions of ozone and tetramethylethene also matched experimental data for the main products, but revealed consequences of limited exploration depth and shortcomings of the implicit solvation model. Our work illustrates that automated CRN explorations offer novel means for predicting transformation pathways of organic compounds in chemical oxidation processes and can support chemical analysis, assess of environmental risks, and design of environmentally benign chemicals.