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

该奖项由美国国家科学基金会化学部的环境化学科学项目资助。加州大学河滨分校的Bryan M. Wong教授和刘海洲教授将计算技术与实验室测量相结合，以了解废水在处理和再利用过程中发生的化学反应的变化。研究人员试图了解有机化合物在水中被称为自由基的活性物质氧化反应的速率。使用的计算工具包括数据可视化、数据挖掘、机器学习和数据分析技术。开发了适用于水回用应用的预测理论模型和基于量子的方法。利用这些，计算了水回用的化学反应速率。然后通过有针对性的实验对模型进行验证和改进。这种方法促进了对分子自由基反应动力学的基本科学认识。该项目允许理论和实验的无缝连接，以解决与水净化过程相关的自由基-有机物相互作用的效率和反应途径。黄教授和刘教授让各个层次的学生参与他们的研究，包括社区大学的学生。共有三个拉美裔服务机构参与了这个项目。研究人员还接触到K-12学生和他们的老师，以促进对计算在环境科学和工程中的作用的理解。通过研究废水处理，该项目促进了人类健康和工业可持续性的努力。该项目研究了水处理和回用的水生反应动力学。结合多学科的方法导致分子结构如何影响热力学和动力学在复杂的水环境系统的理解。这是一项重大的科学和技术挑战，对于为改善水的再利用提供有指导的、合理的途径至关重要。此外，该项目建立了一个计算筛选工作，以确定影响水化学动力学的基本物理化学特性。采用密度泛函理论（DFT）和严格多体波函数CCSD(T)-F12方法。该项目还建立了一系列指导动力学和表征工作，密切关注计算筛选工作，包括数值敏感性分析。这些计算提供了对水环境中有机分子电子结构的系统理解。这些实验反过来又指导了计算研究，并提供了理解这些水系统中调节反应动力学的详细、复杂贡献的能力。这项工作产生的基础知识具有广泛的社会影响，特别是对严重依赖水处理和再利用的地区和行业。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.