Resolving Relationships: Determining the Impacts of Environmental Matrices on the Ionization Efficiencies of Per and Polyfluoroalkyl Substances (PFAS) for the Development of a Semi-Quantitation Model

摘要： 一些分析挑战阻碍了准确识别和量化 环境中的PER和多氟烷基物质(PFAS)。这些挑战包括缺乏 以及由于基质干扰引起的电离可变性。 电喷雾电离。在这次外展中，我计划通过评估来应对这些挑战 环境水样的主要基质特征及其与电离的关系 效率。观察到的关系将被用来开发一个初步的统计模型 没有参考物质的全氟辛烷磺酸的半定量。通过与联合航空的合作 州环境保护局，我将从导师Sobus博士和Dr Sobus那里获得专业知识。 利用化学信息学解决分析问题。半定量模型 由于外力的发展，可以用来对PFAS的转化产物进行量化 退化研究，例如在母公司NIH下设计的纳米生物修复技术 格兰特，R01ES032717。

Abstract: A number of analytical challenges hinder the accurate identification and quantification of per and polyfluoroalkyl substances (PFAS) in the environment. These challenges include the lack of reference materials for PFAS as well as the ionization variability due to matrix interferences in electrospray ionization. In this externship, I plan on addressing these challenges by evaluating major matrix characteristics of environmental water samples and their relationship to the ionization efficiency. The observed relationships will be used to develop a preliminary statistical model for the semi-quantitation of PFAS without reference materials. Through collaboration with the United States Environmental Protection Agency, I will gain expertise from mentors, Dr. Sobus and Dr. McCord, in using cheminformatics for solving analytical problems. The semi-quantitation model developed as a result of the externship can be used to quantify transformation products of PFAS degradation studies, such as the nano bio-remediation techniques designed under the parent NIH grant, R01ES032717.