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Raman Spectroscopic Analysis of Gunshot Residue Offering Great Potential for Caliber Differentiation

机译:枪支残留物的拉曼光谱分析为口径分化提供了巨大潜力

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Near-infrared (NIR) Raman microspectroscopy combined with advanced statistics was used to differentiate gunshot residue (GSR) particles originating from different caliber ammunition. The firearm discharge process is analogous to a complex chemical reaction. The reagents of this process are represented by the chemical composition of the ammunition, firearm, and cartridge case. The specific firearm parameters determine the conditions of the reaction and thus the subsequent product, GSR. We found that Raman spectra collected from these products are characteristic for different caliber ammunition. GSR particles from 9 mm and 0.38 caliber ammunition, collected under identical discharge conditions, were used to demonstrate the capability of confocal Raman microspectroscopy for the discrimination and identification of GSR particles. The caliber differentiation algorithm is based on support vector machines (SVM) and partial least squares (PLS) discriminant analyses, validated by a leave-one-out cross-validation method. This study demonstrates for the first time that NIR Raman microspectroscopy has the potential for the reagentless differentiation of GSR based upon forensically relevant parameters, such as caliber size. When fully developed, this method should have a significant impact on the efficiency of crime scene investigations.
机译:近红外(NIR)拉曼光谱技术与先进的统计技术结合使用,可区分源自不同口径弹药的枪击残留物(GSR)颗粒。枪支放电过程类似于复杂的化学反应。该过程的试剂由弹药,枪支和弹药盒的化学成分表示。特定的枪支参数决定了反应的条件,因此决定了随后的产物GSR。我们发现从这些产品收集的拉曼光谱是不同口径弹药的特征。在相同的放电条件下收集了9毫米口径和0.38口径弹药的GSR颗粒,以证明共聚焦拉曼光谱法对GSR颗粒的辨别和鉴定能力。口径区分算法基于支持向量机(SVM)和偏最小二乘(PLS)判别分析,并通过留一法交叉验证方法进行了验证。这项研究首次证明,基于法医相关参数(例如口径大小),NIR拉曼显微光谱技术具有对GSR进行无试剂区分的潜力。如果完全发展起来,这种方法应该对犯罪现场调查的效率产生重大影响。

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