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从灰烬中提取的染料:从矿化纺织品中发现和鉴定天然染料。

Dyes from the Ashes: Discovering and Characterizing Natural Dyes from Mineralized Textiles.

机构信息

Chemistry Department, "Sapienza" "Sapienza" University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy.

Department Physics, "Sapienza" University of Rome, Piazzale Aldo Moro 5, 00174 Rome, Italy.

出版信息

Molecules. 2020 Mar 20;25(6):1417. doi: 10.3390/molecules25061417.

Abstract

Vesuvius eruption that destroyed Pompeii in AD 79 represents one of the most important events in history. The cataclysm left behind an abundance of archeological evidence representing a fundamental source of the knowledge we have about ancient Roman material culture and technology. A great number of textiles have been preserved, rarely maintaining traces of their original color, since they are mainly in the mineralized and carbonized state. However, one outstanding textile sample displays a brilliant purple color and traces of gold strips. Since the purple was one of the most exclusive dyes in antiquity, its presence in an important commercial site like Pompeii induces us to deepen the knowledge of such artifacts and provide further information on their history. For this reason, the characterization of the purple color was the main scope of this research, and to deepen the knowledge of such artifacts, the SERS (Surface Enhanced Raman Scattering) in solution approach was applied. Then, these data were enriched by HPLC-HRMS analyses, which confirmed SERS-based hypotheses and also allowed to hypothesize the species of the origin mollusk. In this context, a step-by-step integrated approach resulted fundamental to maximize the information content and to provide new data on textile manufacturing and trade in antiquity.

摘要

公元 79 年维苏威火山爆发摧毁了庞贝城,这是历史上最重要的事件之一。这场大灾难留下了丰富的考古证据,为我们了解古罗马物质文化和技术提供了重要的来源。大量的纺织品得以保存,但由于它们主要处于矿化和碳化状态,很少保留其原始颜色的痕迹。然而,有一个杰出的纺织品样本显示出鲜艳的紫色和金色条纹的痕迹。由于紫色在古代是最独特的染料之一,因此在庞贝这样的重要商业遗址中发现它,促使我们深入了解这些文物,并提供有关其历史的进一步信息。出于这个原因,对紫色的特征分析是这项研究的主要内容,为了深入了解这些文物,采用了溶液中 SERS(表面增强拉曼散射)的方法。然后,通过 HPLC-HRMS 分析丰富了这些数据,这些分析证实了基于 SERS 的假设,并允许推测出贝类的物种。在这种情况下,逐步集成的方法对于最大限度地提高信息量和提供有关古代纺织品制造和贸易的新数据至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c26/7144399/743637160aeb/molecules-25-01417-g001.jpg

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