CAREER: Mechanistic Investigation of Chemical Photodegradation to Aid in Novel Pesticide Design

该职业奖由化学学部环境化学科学项目颁发，支持Jakub Kostal教授及其学生和博士后同事对农药的环境命运进行计算研究。随着全球人口的增长，作物保护变得越来越重要。据估计，每年使用的活性农药成分超过200万吨。这些化学品的环境命运及其使用后的降解能力尚不清楚。环境问题要求改变这些化学品在环境中的使用。本研究旨在利用计算技术促进我们对空气和地表水中农药的光引发分解机制的理解。这项研究将为设计现有商业农药的替代品提供信息，这些农药不会在环境中持续存在。参与本研究的学生和博士后将接受环境化学和计算化学两方面的培训。Kostal教授还领导了由美国化学学会绿色化学与工程会议主办的一年一度的化学学生设计挑战赛。在这个挑战中，化学专业的学生团队将应用计算方法来设计高性能和非持久性的新型商业化学品。光化学反应是农药非生物降解的主要途径。其中，由受激发的天然有机物引发的间接反应最为常见。本工作旨在提高我们对常见农药与天然有机物反应机理的认识。目标是制定有效使用现有农药的准则，并设计使用后不会在环境中持续存在的新型农药。计算方法，特别是时间无关和依赖密度泛函理论，被使用。该项目建立了一个全面的光降解指标数据库，供科学界公众使用。反过来，这些指标可以通过应用机器学习和模式识别方法来更好地理解农药非生物转化的结构-活性关系。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 CAREER award from the Environmental Chemical Sciences Program in the Division of Chemistry supports Professor Jakub Kostal and his students and postdoctoral associates for a computational study of the environmental fate of pesticides. Crop protection is ever more important as global population grows. It is estimated that over two million tons of active pesticide ingredients are used annually. The environmental fate of these chemicals and their ability to degrade after use are not well understood. Environmental concerns require changes to the use of these chemicals in the environment. This research aims to advance our understanding of light-initiated breakdown mechanisms of pesticides in the air and in surface waters using computational techniques. This research will inform the design of alternatives to existing commercial pesticides, which will not persist in the environment. The students and postdocs participating in this research will be trained in both environmental and computational chemistry. Professor Kostal also leads an annual design challenge for chemistry students hosted by the American Chemical Society Green Chemistry & Engineering Conferences. In this challenge, teams of chemistry students will apply computational methods to the design of novel commercial chemicals that are both high performing and non-persistent.Photochemical reactions are the primary route for abiotic degradation of pesticides. Among those, indirect reactions initiated by excited natural organic matter are the most common. This work aims to improve our understanding of the reaction mechanisms between common pesticides and natural organic matter. The goal is to develop guidelines for the effective use of existing pesticides and to design novel pesticides that will not persist in the environment after use. Computational methods, notably time-independent and dependent density functional theory, are used. The project develops a comprehensive database of photodegradation metrics, which are made available to the scientific public. These metrics can, in turn, be used to better understand structure-activity relationships for abiotic transformations of pesticides by applying machine learning and pattern-recognition methods.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.