D3SC: Data-Driven Modeling and Experimental Investigation for Discovery of Aquatic Chemistry Reaction Kinetics: New Tools for Water Reuse Applications

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This award is supported by the Environmental Chemical Sciences Program in the NSF Chemistry Division. Professors Bryan M. Wong and Haizhou Liu at the University of California-Riverside combine computational techniques with laboratory measurements to understand changes in chemical reactions that occur in wastewater during treatment and reuse. The researchers seek to understand the rate of oxidation reactions of organic compounds in water by reactive species called radicals. The computational tools used include data visualization, data mining, machine learning, and data analytics techniques. Predictive theoretical models and quantum-based methods are developed that are applicable to water reuse applications. With these, the chemical reaction rates for water reuse are calculated. The models are then validated and improved through targeted experiments. This approach advances the basic scientific understanding of reaction dynamics in molecular radicals. This project allows a seamless connection of both theory and experiment to address the efficiency and reaction pathways of radical-organics interactions associated with water purification processes. Professors Wong and Liu engage students at all levels in their research, including community college students. A total of three Hispanic-Serving Institutions are involved in this project. The investigators also reach out to K-12 students and their teachers to promote understanding of the role of computing in environmental science and engineering. By examining wastewater treatments, this project promotes human health and sustainability efforts in industry. This project addresses aquatic reaction kinetics for advanced water treatment and reuse. The combined multidisciplinary approach leads to a systematic understanding of how molecular structure influences thermodynamics and kinetics in complex aqueous environments. This is a significant scientific and technical challenge and critical to providing a guided, rational path for improving water reuse. Furthermore, this project establishes a computational screening effort to identify fundamental physicochemical characteristics that affect aqueous chemical kinetics. Both density functional theory (DFT) and rigorous many-body wave function CCSD(T)-F12 methods are used. The project also establishes a series of guided kinetics and characterization efforts that closely follow the computational screening efforts, including numerical sensitivity analyses. These calculations provide a systematic understanding of electronic structure of organic molecules in aqueous environments. The experiments in turn guide the computational studies and afford the capability to understand the detailed, complex contributions that modulate the reaction dynamics in these aqueous systems. The fundamental knowledge generated by this work has broad societal impact, particularly for regions and industries that critically rely on water treatment and reuse.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.