Bioaerosol detection using potentiometric tomography in flames
Bioaerosol detection using potentiometric tomography in flames
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DOI：
10.1039/c2sc20304a
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发表时间：
2012-06
期刊：
影响因子：
8.4
通讯作者：
D. Sarantaridis;C. Hennig;D. Caruana
中科院分区：
文献类型：
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作者：
D. Sarantaridis;C. Hennig;D. Caruana
描述了一种基于火焰中的气态等离子体电化学的生物气溶胶的检测和识别方法。这种方法涉及进入层流氢/氧火焰的单个生物气溶胶颗粒的燃烧，产生富含电离物质的羽流。当羽流膨胀并穿过火焰时，可以通过八个可单独寻址的电极阵列轻松地检测到它。在每个电极处同时记录的零电流电位测量提供了燃烧羽流的空间分布，这取决于颗粒的尺寸、密度和化学组成。我们使用统计分类分析从单个颗粒燃烧事件中提取电压迹线的特定特征，以区分四种模型生物气溶胶（百慕大草花粉、百慕大黑穗病孢子、约翰逊黑穗病孢子和黑胡桃花粉）。从一组 120 个单独的燃烧事件（每个生物气溶胶 30 个）中，百慕大草花粉的最佳识别情况为 30 个事件中的 29 个，最差的是约翰逊黑穗病孢子的 30 个事件中的 19 个。我们提出了一种有前途且稳健的实时生物气溶胶检测分析方法。
A method of detection and identification of bioaerosols is described, based on gaseous plasma electrochemistry in a flame. This approach involves the combustion of individual bioaerosol particles entering a laminar hydrogen/oxygen flame, producing a plume rich in ionised species. As the plume expands and moves through the flame it can be comfortably detected at an array of eight individually addressable electrodes. Zero current potentiometric measurements, simultaneously recorded at each electrode, provide spatial distribution of the combustion plume, which depends on the particle's size, density and chemical make-up. We used a statistical classification analysis extracting specific features of the voltage traces from individual particle combustion events to differentiate between four model bioaerosols (Bermuda grass pollen, Bermuda smut spores, Johnson smut spores and Black walnut pollen). From a set of 120 individual combustion events (30 for each bioaerosol) the best case of identification was correct 29 out of 30 events for Bermuda grass pollen, and the worst being 19 out of 30 for Johnson smut spores. We propose a promising and robust analytical methodology for real-time bioaerosol detection.