10th International Aerosol Conference
September 2 - September 7, 2018
America's Center Convention Complex
St. Louis, Missouri, USA

Abstract View


Investigating Effects of Ambient Gas on the Ionization of Compounds by Secondary Electrospray Ionization Using Ultrahigh Resolution Mass Spectrometry

JIAFA ZENG, Kai Wu, Rui Du, Yuling Zhang, Dandan Huang, Zhen Zhou, Xue Li, Jinan University

     Abstract Number: 1246
     Working Group: Instrumentation

Abstract
Secondary electrospray ionization (SESI) is a soft ionization technique, which occurs under ambient conditions; samples can be directly ionized without pre-treatment. A wide variety of organic compounds, such as fatty acids, aldehydes, ketones, alcohols and alkenes, have been successfully detected by using SESI mass spectrometry (SESI-MS) based methods. The ambient gas in the SESI source can affect the ionization efficiency of target compounds and interfering chemicals (e.g., plasticizers), which is closely related to the sensitivity of the method. In this study, volatile organic compound (VOC)-free dry-air and pure nitrogen gas (N2, purity 99.999%) were selected as the ambient gases in the SESI source, and the effects of different ambient gases on the detection of typical exhaled VOCs (indole and acetone) in human breath and interfering compounds (dibutyl phthalate and polysiloxane) were systematically studied by using ultrahigh resolution mass spectrometry. The preliminary results indicate that the signal intensity of indole and acetone were enhanced at the presence of dry-air and N2, and the enhancing effects were higher when N2 was used. In contrast, the signal intensity of dibutyl phthalate and polysiloxane were greatly decreased, especially when N2 was present in the source. Effects of dry-air on the detection of other exhaled endogenous compounds and interfering chemicals are still under investigation and the flow rate of the ambient gas delivered into the source is also tested in the present study. The study will provide helpful information on the optimization of SESI source and benefit a better understanding of SESI process, which is essential for improving method sensitivity.