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Hyperspectral depth-profiling with deep Raman spectroscopy for detecting chemicals in building materials

机译:高光谱深度分析,具有深拉曼光谱,用于检测建筑材料中的化学品

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摘要

Toxic chemicals inside building materials have long-term harmful effects on human bodies. To prevent secondary damage caused by the evaporation of latent chemicals, it is necessary to detect the chemicals inside building materials at an early stage. Deep Raman spectroscopy is a potential candidate for on-site detection because it can provide molecular information about subsurface components. However, it is very difficult to spectrally distinguish the Raman signal of the internal chemicals from the background signal of the surrounding materials and to acquire the geometric information of chemicals. In this study, we developed hyperspectral wide-depth spatially offset Raman spectroscopy coupled with a data processing algorithm to identify toxic chemicals, such as chemical warfare agent (CWA) simulants in building materials. Furthermore, the spatial distribution of the chemicals and the thickness of the building material were also measured from one-dimensional (1D) spectral variation.
机译:建筑材料内有毒化学品对人体具有长期有害影响。 为防止潜伏化学品蒸发引起的二次损害,有必要在早期阶段检测建筑材料内的化学品。 深拉曼光谱是用于现场检测的潜在候选者,因为它可以提供有关地下部件的分子信息。 然而,非常难以从周围材料的背景信号中谱谱区分内部化学物质的拉曼信号,并获取化学物质的几何信息。 在这项研究中,我们开发了高光谱宽深度空间偏移拉曼光谱,其耦合数据处理算法以识别有毒化学品,例如建筑材料中的化学战争剂(CWA)模拟剂。 此外,还从一维(1D)光谱变化测量了化学品的空间分布和建筑物的厚度。

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