Since its introduction, gas chromatography (GC) coupled to vacuum ultraviolet spectrophotometry (VUV) has been shown to complement mass spectrometry (MS) for materials such as petrochemicals, explosives, pesticides, and drugs. In forensic chemistry, opioids are commonly encountered but rarely are the samples pure. This work focuses on GC-VUV analysis applied to naturally occurring (e.g., morphine), semi-synthetic (e.g., heroin), and synthetic (fentanyl) opioids as well as common adulterants and diluents (e.g., lidocaine and quinine). The specificity of the VUV spectra were examined visually as well as via descriptive statistical methods (e.g., correlation coefficients and sums of square residuals). Multivariate pattern recognition techniques (principal component analysis and discriminant analysis (DA)) were used to prove the opioid spectra can be reliably differentiated. The accuracy of the DA model was 100% for a test set of VUV spectra. Finally, three "street" heroin samples were analyzed to show "real-world" performance for forensic analyses. These samples contained adulterants such as caffeine, as well as by-products of heroin manufacture.

中文翻译：

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通过气相色谱-真空紫外分光光度法（GC-VUV）对鸦片剂进行仪器和化学计量分析。

自从引入以来，气相色谱（GC）与真空紫外分光光度法（VUV）结合已被证明是对石油化工，炸药，农药和药物等材料的质谱（MS）的补充。在法医化学中，通常会遇到阿片类药物，但样品很少是纯净的。这项工作的重点是将GC-VUV分析应用于天然存在的（例如吗啡），半合成的（例如海洛因）和合成的（芬太尼）阿片类药物以及常见的掺杂剂和稀释剂（例如利多卡因和奎宁）。目测以及通过描述性统计方法（例如，相关系数和平方残差之和）检查VUV光谱的特异性。多变量模式识别技术（主要成分分析和判别分析（DA））被用来证明阿片样物质光谱可以可靠地区分。对于VUV光谱测试集，DA模型的准确性为100％。最后，对三个“街头”海洛因样品进行了分析，以显示法医分析的“真实”性能。这些样品中含有诸如咖啡因等掺假物，以及海洛因生产过程中的副产品。