光谱学与光谱分析, 2019, 39 (7): 2299, 网络出版: 2019-07-23  

基于ATR-FTIR和PAC微损快速鉴别颜料层中的蛋白质粘合剂

Micro-Destructive and Rapid Chemical Identification of the Protein Binders in Colors Layers of Paintings by ATR-FTIR and Principal Component Analysis
许昆 1,2,3王菊琳 1,2,3,*
作者单位
1 北京化工大学材料电化学过程重点实验室, 北京 100029
2 北京化工大学材料科学与工程学院, 北京 100029
3 文物保护领域科技评价研究国家文物局重点科研基地, 北京 100029
摘要
相较于气相色谱-质谱(GC-MS)和高效液相色谱(HPLC), 衰减全反射傅里叶变换红外光谱(ATR-FTIR)能实现绘画颜料中蛋白质种类的“不分离即分析”, 从而简化分析步骤和减小文物样品的消耗。 这项研究验证了ATR-FTIR用于颜料中蛋白质种类鉴别的可行性。 以石青和白垩为矿物颜料, 牛奶、 明胶和鸡蛋为蛋白质粘合剂制备了新鲜样品和经紫外光老化的模拟文物样品, 运用二阶导数光谱和主成分分析建立了模式识别模型。 结果表明模拟文物样品中蛋白质的种类能通过新鲜样品建立的模型进行识别。 因此, ATR-FTIR在文化遗产领域中蛋白质种类的微损和快速鉴别具有巨大的潜力。
Abstract
Compared with gas chromatography-mass spectroscopy (GC-MS) and high performance liquid chromatography (HPLC), attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy is an “analysis-without-separation” technique so that the analytical procedures can be simplified and the consumption of the art samples can be minimized in the analysis of color layers in paintings. This study examined the feasibility of the ATR-FTIR spectroscopy for identifying the protein binders in color layers. The fresh and accelerated UV light aged reference samples with single protein binders and the mixtures of pigment-protein binders were prepared, by using milk, animal glue, egg white as protein binders, and chalk, azurite as pigments. Second derivative infrared (SD-IR) spectral pattern recognition models were obtained by using principal component analysis (PCA). The protein binders in artificial art samples can be discriminated by the pattern recognition models, which were established based on the analysis of fresh samples. Therefore, the ATR-FTIR spectroscopy has great potential in micro-destructive and rapid chemical identification of protein binders in the field of cultural heritage.

许昆, 王菊琳. 基于ATR-FTIR和PAC微损快速鉴别颜料层中的蛋白质粘合剂[J]. 光谱学与光谱分析, 2019, 39(7): 2299. XU Kun, WANG Ju-lin. Micro-Destructive and Rapid Chemical Identification of the Protein Binders in Colors Layers of Paintings by ATR-FTIR and Principal Component Analysis[J]. Spectroscopy and Spectral Analysis, 2019, 39(7): 2299.

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