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Standoff Detection of Chemical and Biological Threats Using Laser-Induced Breakdown Spectroscopy

机译:使用激光诱导击穿光谱对化学和生物威胁进行僵持检测

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Laser-induced breakdown spectroscopy (LIBS) is a promising technique for real-time chemical and biological warfare agent detection in the field. We have demonstrated the detection and discrimination of the biological warfare agent surrogates Bacillus subtilis (BG) (2% false negatives, 0% false positives) and ovalbumin (0% false negatives, 1% false positives) at 20 meters using standoff laser-induced breakdown spectroscopy (ST-LIBS) and linear correlation. Unknown interferent samples (not included in the model), samples on different substrates, and mixtures of BG and Arizona road dust have been classified with reasonable success using partial least squares discriminant analysis (PLS-DA). A few of the samples tested such as the soot (not included in the model) and the 25% BG:75% dust mixture resulted in a significant number of false positives or false negatives, respectively. Our preliminary results indicate that while LIBS is able to discriminate biomaterials with similar elemental compositions at standoff distances based on differences in key intensity ratios, further work is needed to reduce the number of false positivesegatives by refining the PLS-DA model to include a sufficient range of material classes and carefully selecting a detection threshold. In addition, we have demonstrated that LIBS can distinguish five different organophosphate nerve agent simulants at 20 meters, despite their similar stoichiometric formulas. Finally, a combined PLS-DA model for chemical, biological, and explosives detection using a single ST-LIBS sensor has been developed in order to demonstrate the potential of standoff LIBS for universal hazardous materials detection.
机译:激光诱导击穿光谱法(LIBS)是用于该领域实时化学和生物战剂检测的有前途的技术。我们已经证明了在20米处使用对峙激光诱导的生物战剂替代物枯草芽孢杆菌(BG)(2%假阴性,0%假阳性)和卵清蛋白(0%假阴性,1%假阳性)的检测和区分。击穿光谱法(ST-LIBS)和线性相关。使用偏最小二乘判别分析(PLS-DA)已成功分类了未知干扰物样品(模型中未包括),不同基质上的样品以及BG和Arizona道路扬尘的混合物。测试的一些样品,例如烟灰(模型中未包括)和25%BG:75%的粉尘混合物,分别导致大量假阳性或假阴性。我们的初步结果表明,尽管LIBS能够基于关键强度比的差异在相距距离处区分具有相似元素组成的生物材料,但仍需要进一步的工作,通过完善PLS-DA模型以包括假阳性/阴性的数量来减少假阳性/阴性的数量。足够的材料类别范围,并仔细选择检测阈值。此外,我们已经证明,LIBS可以区分20米处的五种不同的有机磷酸神经药模拟物,尽管它们的化学计量公式相似。最后,已开发出使用单个ST-LIBS传感器的用于化学,生物和爆炸物检测的组合PLS-DA模型,以证明对峙LIBS在通用危险材料检测中的潜力。

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    《Applied Spectroscopy》 |2008年第4期|353-363|共11页
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