整合多模态拉曼显微镜和光致发光显微镜,通过多元分析增强洞察力

Alessia Di Benedetto, Paolo Pozzi, Gianluca Valentini, D. Comelli
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引用次数: 0

摘要

本文介绍了一种新型多模态光学显微镜,该显微镜集成了拉曼光谱和激光诱导光致发光光谱,用于分析与文物科学相关的微观样本。从绘画等艺术品中提取的微观样本显示出错综复杂的材料构成,具有高度复杂性和空间异质性,其特点是有多层颜料,这些颜料也可能受到降解现象的影响。要全面了解其材料成分和状况,采用多模态策略势在必行。拉曼光谱仪和激光诱导光致发光光谱仪的协同作用使所建议的装置更加有效。通过使用多种激发波长和两种不同的激发通量,后一种技术识别各种化学物质的能力得到了增强。这两种互补技术的结合使仪器能够通过光栅扫描方法有效地实现对样品的全面化学映射。为了缩短整体测量时间,我们对每个测量点都采用了较短的积分时间。我们进一步提出了一种基于多元方法的分析方案。具体来说,我们采用非负矩阵因式分解作为光谱分解方法。这样就能识别与样品中特定化合物有效相关的光谱内含物。为了证明该方法在遗产科学中的有效性,我们举例说明了颜料粉末分散体和绘画作品的地层微观样本。通过这些例子,我们展示了多模态方法如何加强材料鉴定,更重要的是,如何促进补充信息的提取。这一点至关重要,因为两种光学技术对不同材料的敏感性各不相同。展望未来,我们的方法有望应用于材料科学和生物学等多个研究领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating multimodal raman and photoluminescence microscopy with enhanced insights through multivariate analysis
This paper introduces a novel multimodal optical microscope, integrating Raman and laser-induced photoluminescence spectroscopy for the analysis of micro-samples relevant in Heritage Science. Micro-samples extracted from artworks, such as paintings, exhibit intricate material compositions characterized by high complexity and spatial heterogeneity, featuring multiple layers of paint that may be also affected by degradation phenomena. Employing a multimodal strategy becomes imperative for a comprehensive understanding of their material composition and condition. The effectiveness of the proposed setup derives from synergistically harnessing the distinct strengths of Raman and laser-induced photoluminescence spectroscopy. The capacity to identify various chemical species through the latter technique is enhanced by using multiple excitation wavelengths and two distinct excitation fluence regimes. The combination of the two complementary techniques allows the setup to effectively achieve comprehensive chemical mapping of sample through a raster scanning approach. To attain a competitive overall measurement time, we employ a short integration time for each measurement point. We further propose an analysis protocol rooted in a multivariate approach. Specifically, we employ Non-Negative Matrix Factorization as the spectral decomposition method. This enables the identification of spectral endmembers, effectively correlated with specific chemical compounds present in samples. To demonstrate its efficacy in Heritage Science, we present examples involving pigment powder dispersions and stratigraphic micro-samples from paintings. Through these examples, we show how the multimodal approach reinforces material identification and, more importantly, facilitates the extraction of complementary information. This is pivotal as the two optical techniques exhibit sensitivity to different materials. Looking ahead, our method holds potential applications in diverse research fields, including material science and biology.
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