Acoustic Levitation-Controlled Droplets for Contactless Enrichment and Sensitive Detection of Volatile Organic Substances Integrated with GC-MS

化学 色谱法 环境化学 代谢物 可替宁 悬浮 挥发性有机化合物 气相色谱法 汽油 质谱法 分析化学(期刊) 尼古丁 有机化学 神经科学 物理 生物 量子力学 生物化学 磁铁
作者
Shanshan Ma,Yake Luo,Bo Sui,Guobi Chai,Yanhao Zhang,Gangfeng Ouyang,Shusheng Zhang,Qidong Zhang,Wuduo Zhao
出处
期刊:Analytical Chemistry [American Chemical Society]
标识
DOI:10.1021/acs.analchem.4c02600
摘要

Analyzing trace-level volatile organic compounds (VOCs) remains challenging due to initial sampling and preconcentration limitations. Inspired by the highly reproducible and constantly renewable electrode surface of dropping mercury electrode (DME), a contactless enrichment process was first reported by using an acoustic levitation device to trap and concentrate VOCs from gas samples onto suspended droplets, which were then directly transferred into gas chromatography-mass spectrometry (GC-MS) for real-time analysis. Compared with traditional methods injection methods, this method achieves a 46-fold increase in nicotine peak area. The detection sensitivity was enhanced significantly, attributed to the high specific surface area of the droplets and the accelerating extraction vibration. Notably, the number of identified VOCs from burning cigarettes significantly increased from 17 to 212, including 22 aromatic compounds with distinct aromas. The remarkable versatility of this method was demonstrated by effectively monitoring the dynamic changes of 16 VOCs in environmental tobacco smoke (ETS) following cigarette burning, revealing the persistence of these compounds, even after 40 min. Moreover, directly analyzing human-exhaled aerosol found that nicotine rapidly decreased while its metabolite cotinine increased, showcasing the potential for tracking human metabolism and behavior in vivo. Furthermore, multivariate data analysis of VOC profiles from six cigarette brands allowed for their visual differentiation. With versatility, sensitivity, and the ability to distinguish trace-level VOCs in realtime, this method offers promising avenues for environmental monitoring, metabolic studies, and various analytical applications.
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