Department Environmental Chemistry

Chemical oxidants such as ozone are key for eliminating waterborne diseases as well as for the abatement of micropollutants during water treatment. Reactions of chemical oxidants with pollutants and other constituents of the water matrix, however, can also give rise to unintended, sometimes toxic disinfection byproducts. Because comprehensive experimental characterizations of the reaction networks pertinent to oxidative water treatment are extremely laborious and inherently incomplete, autonomous and unsupervised computational approaches offer novel and complementary avenues to infer probable byproduct formation pathways systematically.

In this project, we explore the utility of autonomous quantum chemical reaction network (CRN) explorations for the elucidation of oxidative water treatment chemistry by studying the fundamentally important reactions of ozone with olefins using the software for chemical interaction networks (SCINE)

Given the lack of ab initio CRN explorations for the aqueous chemistry of chemical oxidants and their many reactive intermediates, we evaluate quantum chemical methodologies to balance computational efficiency and chemical accuracy and identify reliable benchmarks for the evaluation of computational simulations against experimental data. Extensive previous electronic structure calculations and experimental kinetic data for ozonation reactions of various structurally similar olefins are currently used as reliable basis for the evaluation of the CRN exploration outcomes. We envision that this project can close the gap between environmental and computational chemistry, creating a synergy between both fields which ultimately fosters the identification of key intermediates in ozone chemistry.