X-ray Scattering and Chemometrics as Tools to Assist in the Identification of Gunshot Residues by Wavelength Dispersive X-ray Fluorescence Spectrometry

Wavelength dispersion X-ray fluorescence spectrometry (WDXRF) is a non-destructive technique and therefore attractive for gunshot residues (GSR) analysis. It is well known for determination of inorganic constituents of samples. However, X-ray scattering region spectral data is not commonly used, although it may provide information about organic constituents and their interactions. This work employed X-ray scattering region and inorganic elements spectral data for a better characterization of GSR. Swabs containing residues collected from the hand of people who fired (shooters group) and also from the hands of people which did not fire (control group) with guns were analyzed directly by the WDXRF. Brake pad and people who perform activities that favor the accumulation of characteristic elements of GSR on their hands were chosen to compose the control group. Principal components analysis (PCA) discriminated the GSR according to the firearm/cartridge used. However, similar GSR clustering did not occur without X-ray scatter data, showing the importance of X-ray scattering spectrum for GSR evaluation. The k-nearest neighbors (k-NN) method correctly classified all samples from shooters and control groups, employing from 1 to 5 nearest neighbors. No anomalous behavior was detected by PCA and hierarchical cluster analysis (HCA).

波长色散X射线荧光光谱法（Wavelength dispersion X-ray fluorescence spectrometry, WDXRF）是一种无损检测技术，因此在枪支残留物（gunshot residues, GSR）分析中具有显著应用优势。该技术因可精准测定样品中的无机组分而广受认可，然而X射线散射区的光谱数据却未得到广泛应用，尽管其能够提供关于有机组分及其相互作用的相关信息。本研究结合X射线散射区与无机元素光谱数据，以实现对枪支残留物的更全面表征。研究人员直接采用波长色散X射线荧光光谱法，对两类拭子样本开展分析：一类采集自开枪人员的手部（射手组），另一类采集自未开枪人员的手部（对照组）。对照组样本选取自两类人群：刹车片从业者，以及手部易积累枪支残留物特征元素的职业人群。主成分分析（Principal components analysis, PCA）可依据所使用的枪支/弹药型号对枪支残留物进行有效区分，但若未纳入X射线散射数据，则无法实现相似枪支残留物的聚类分析，这一结果凸显了X射线散射光谱在枪支残留物评估中的重要价值。采用k近邻（k-nearest neighbors, k-NN）算法，选取1至5个近邻样本，即可对射手组与对照组的全部样本实现准确分类。主成分分析与系统聚类分析（hierarchical cluster analysis, HCA）均未检测到异常样本行为。