1 ALERT DHS Center of Excellence for Explosives Research, University of Puerto Rico, Mayagüez, PR, USA.
2 School of Basic and Biomedical Sciences, Universidad Simón Bolívar, Barranquilla, Colombia.
Appl Spectrosc. 2019 Jan;73(1):17-29. doi: 10.1177/0003702818780414. Epub 2018 Sep 27.
Mid-infrared (MIR) laser spectroscopy was used to detect the presence of residues of high explosives (HEs) on fabrics. The discrimination of the vibrational signals of HEs from a highly MIR-absorbing substrate was achieved by a simple and fast spectral evaluation without preparation of standards using the classical least squares (CLS) algorithm. Classical least squares focuses on minimizing the differences between the spectral features of the actual spectra acquired using MIR spectroscopy and the spectral features of calculated spectra modeled from linear combinations of the spectra of neat components: HEs, fabrics, and bias. Samples in several combinations of cotton fabrics/HEs were used to validate the methodology. Several experiments were performed focusing on binary, ternary, and quaternary mixtures of TNT, RDX, PETN, and fabrics. The parameters obtained from linear combinations of the calculated spectra were used to perform discrimination analyses and to determine the sensitivity and selectivity of HEs with respect to the substrates and to each other. However, discrimination analysis was not necessary to achieve successful detection of HEs on cotton fabric substrates. The RDX signals ( m > 0.02 mg) on cotton were used to calculate the limit of detection (LOD). The signal-to-noise ratios (S/N) calculated from the spectra of cotton dosed with decreasing masses of RDX until S/N ≈ 3 resulted in a LOD of 15-33 µg, depending on the vibrational band used. Linear fits generated by comparing the mass dosed RDX with the fraction predicted were also used to calculate the LOD based on the uncertainty of the blank and the slope. This procedure resulted in a LOD of 58 µg. Probably the most representative value of the method LOD was calculated using an interpolation of a threshold determined using the predicted average value for the blank plus 3.28 times the standard deviations ( p-value threshold) for low surface dosages of RDX (LOD = 40 µg). The contribution demonstrates that to achieve HE detection on fabrics using the proposed algorithm, i.e., determining the presence/absence of HEs on the substrates, the library must contain the spectra of HEs, substrates, and potential interferents or that these spectra be added to the models in the field. If the model does not contain the spectra of the fabric components, there is a high probability of finding false positives for clean samples (no HEs) and a low probability for failed detection in samples with HEs. More work will be required to demonstrate that these new approaches to HE detection work on real-world samples and when contaminating materials are present in the samples.
中红外（MIR）激光光谱用于检测织物上高爆炸药（HE）残留物的存在。通过不准备标准而使用经典最小二乘法（CLS）算法对HE 的振动信号与高 MIR 吸收衬底的振动信号进行快速简单的光谱评估，从而实现了对 HE 的识别。经典最小二乘法侧重于通过线性组合纯组分（HE、织物和偏置）的光谱来计算模型的光谱，从而最小化实际光谱与光谱特征之间的差异。使用几种棉织物/HE 组合的样品验证了该方法。进行了几项实验，重点研究 TNT、RDX、PETN 和织物的二元、三元和四元混合物。从计算光谱的线性组合中获得的参数用于执行判别分析，并确定 HE 相对于衬底和彼此的灵敏度和选择性。然而，进行判别分析对于成功检测棉织物衬底上的 HE 并非必要。使用在棉织物上的 RDX 信号（ m>0.02mg）计算检测限（LOD）。从用递减质量的 RDX 处理的棉织物的光谱中计算出的信噪比（S/N），直到 S/N≈3，得出 LOD 为 15-33µg，具体取决于所使用的振动带。通过比较定量 RDX 的质量与预测分数生成的线性拟合也可用于根据空白的不确定性和斜率计算 LOD。该程序导致 LOD 为 58µg。该方法的 LOD 的最具代表性值可能是通过使用用空白的预测平均值加上 3.28 倍标准偏差（ p 值阈值）确定的阈值进行插值来计算的，用于低表面剂量的 RDX（LOD=40µg）。该研究结果表明，为了使用所提出的算法在织物上检测 HE，即确定衬底上 HE 的存在/不存在，库中必须包含 HE、衬底和潜在干扰物的光谱，或者必须将这些光谱添加到现场模型中。如果模型中不包含织物成分的光谱，则存在对干净样品（无 HE）发现假阳性的高概率，并且对含有 HE 的样品的检测失败的概率较低。还需要做更多的工作来证明这些检测 HE 的新方法在实际样品和存在污染材料的情况下有效。
