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Multivariate classification of pigments and inks using combined Raman spectroscopy and LIBS

机译:结合拉曼光谱和LIBS对颜料和油墨进行多元分类

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摘要

The authenticity of objects and artifacts is often the focus of forensic analytic chemistry. In document fraud cases, the most important objective is to determine the origin of a particular ink. Here, we introduce a new approach which utilizes the combination of two analytical methods, namely Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS). The methods provide complementary information on both molecular and elemental composition of samples. The potential of this hyphenation of spectroscopic methods is demonstrated for ten blue and black ink samples on white paper. LIBS and Raman spectra from different inks were fused into a single data matrix, and the number of different groups of inks was determined through multivariate analysis, i.e., principal component analysis, soft independent modelling of class analogy, partial least-squares discriminant analysis, and support vector machine. In all cases, the results obtained with the combined LIBS and Raman spectra were found to be superior to those obtained with the individual Raman or LIBS data sets.
机译:物体和人工制品的真实性通常是法医分析化学的重点。在文件欺诈案件中,最重要的目标是确定特定墨水的来源。在这里,我们介绍一种利用两种分析方法(拉曼光谱法和激光诱导击穿光谱法(LIBS))相结合的新方法。该方法提供有关样品分子和元素组成的补充信息。对于白纸上的十个蓝色和黑色墨水样品,已证明了这种光谱方法联用的潜力。将来自不同墨水的LIBS和拉曼光谱融合到一个数据矩阵中,并通过多元分析(即主成分分析,类比的软独立建模,偏最小二乘判别分析和支持向量机。在所有情况下,发现结合LIBS和拉曼光谱获得的结果优于单独的拉曼或LIBS数据集获得的结果。

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