多方法检测古代珍贵彩绘文物颜料及胶结材料的研究

发布时间：2018-01-16 07:36

本文关键词：多方法检测古代珍贵彩绘文物颜料及胶结材料的研究　出处：《浙江大学》2017年硕士论文　论文类型：学位论文

【摘要】：中华文化历史悠久,留存下大量精美珍贵的物质遗存,有洞窟和墓葬壁画、木构建筑的油饰彩画、陶器彩绘等等。这些文物除了文化和艺术价值,同时也是研究古代文明和探索历史进程的重要物证。研究彩绘文物的颜料和胶结材料等原始材料,是研究古代文物制作工艺的基础,同时对现阶段文物的加固保护有十分重要的指导意义。然而对我国彩绘文物颜料和胶结物的种类以及制作工艺进行系统性研究报道还比较少,尤其是对颜料和胶结物检测技术的集成研究很少。本文在查阅国内外文献和总结前人工作的基础上,提出了一套颜料和胶结物的集成检测方法。首先,通过微损取样、横截面制作的方法,展开对彩绘文物剖面结构、颜料和胶结物组成的分析研究。在颜料检测方面,在完善中国古代颜料的元素组成以及拉曼光谱特征峰资料库的基础上,用扫描电子显微镜的背散射功能以及能谱联用技术分析样品中颜料的元素组成,最后用拉曼光谱获取颜料的结构信息。在胶结物检测方面,首先制作多片横截面切片,然后使用染色法确定剖面各层中是否含有油脂和蛋白质,最后使用免疫法鉴定蛋清和动物胶。本文用上述系列方法检测了天水麦积山壁画和泥塑彩画、北京故宫燕喜堂油饰彩画的样品。实验结果表明,通过样品横截面方法分析彩绘文物比较直观、位置信息明确；能谱和拉曼光谱法能从元素组成和物质结构两方面鉴定颜料和填料的成分,可信度高；通过染色法与免疫法在样品的横截面切片上检测有机胶结物,可以准确判断彩绘文物各层中掺加的有机胶结物信息。该颜料和胶结物的集成检测方法可靠、简便、实用。免疫法如酶联免疫法、免疫荧光法和化学发光免疫法等,应用于文物中胶结物的检测特异性和灵敏度高。鉴于目前该方法只局限于动物性蛋白质的检测,比如蛋清、蛋黄、I型胶原蛋白等,而古代很多胶结物属于植物性胶结物,比如大漆、桃胶、松香等。本文以桃胶为例,首先分离提纯植物性胶结物,用纯化的植物性蛋白培养多克隆抗体,将培养成功的抗体进行效价和特异性检测之后,应用于免疫法检测。
[Abstract]:Chinese culture has a long history, leaving a large number of exquisite and precious material remains, including caves and tomb murals, wood architecture oil decorative painting, pottery painting, and so on. These cultural and artistic values. At the same time, it is also an important material evidence to study ancient civilization and explore the historical process. At the same time, it is very important to guide the reinforcement and protection of cultural relics at this stage. However, there are few systematic research reports on the types of pigments and cemented objects of painted cultural relics and the production process in our country. Especially, there is little research on the integrated detection technology of pigment and cement. Based on the review of domestic and foreign literature and the summary of previous work, a set of integrated detection method of pigment and cement is put forward. First of all. Through the method of micro-loss sampling and cross-section making, the structure, pigment and cement composition of the section of painted cultural relics are analyzed and studied. On the basis of perfecting the elemental composition and Raman spectrum characteristic peak database of Chinese ancient pigments, the backscattering function of scanning electron microscope and the spectroscopic technique were used to analyze the elemental composition of pigments in the samples. Finally, the structure information of pigment was obtained by Raman spectroscopy. In the detection of cement, we first made a number of cross-section sections, and then used the staining method to determine whether oil and protein are in each layer of the section. Finally, the egg white and animal glue were identified by immunological method. The samples of mural paintings and clay paintings of Maiji Mountain in Tianshui and oil ornaments of Yanxitang in The Imperial Palace, Beijing were detected by the series of methods mentioned above. The method of cross section of the sample is used to analyze the painted cultural relics directly and the location information is clear. The composition of pigments and fillers can be identified by energy dispersive spectroscopy and Raman spectroscopy in terms of element composition and material structure. The information of organic binders mixed in each layer of painted cultural relics can be accurately judged by staining and immunoassay in the cross-section sections of samples. The integrated detection method of pigment and cement is reliable. Simple and practical. Immunoassay such as enzyme-linked immunosorbent assay, immunofluorescence method and chemiluminescence immunoassay. This method is limited to the detection of animal proteins, such as egg white, yolk type I collagen and so on. In ancient times, a lot of cement belong to plant cementation, such as big lacquer, peach gum, rosin, etc. In this paper, we take peach gum as an example, first isolate and purify plant cement, and culture polyclonal antibody with purified plant protein. After the titer and specificity of the successfully cultured antibody were tested, the antibody was applied to the immunoassay.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：K854.2;O652

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