基于多种光谱技术的中国古代壁画混合矿物颜料含量的非破坏性预测

IF 2.2 3区 化学 Q2 INSTRUMENTS & INSTRUMENTATION Applied Spectroscopy Pub Date : 2024-05-01 DOI:10.1177/00037028241248199
Weihan Zou, Sok Yee Yeo
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引用次数: 0

摘要

本研究首次开发了利用多种光谱技术预测中国古代壁画中混合矿物颜料相对含量的非破坏性精确方法。研究采用了比色法、衰减全反射傅立叶变换红外光谱法(ATR FT-IR)、紫外-可见-近红外光谱法(UV-Vis-NIR)和拉曼光谱法。对老化前后的模拟样品(孔雀石-褐铁矿与兔胶混合样品)进行了色差、光谱反射、ATR 傅立叶变换红外光谱和拉曼光谱分析。然后,利用具有比尔-朗伯定律的紫外可见-近红外光谱和 ATR 傅立叶变换红外光谱数据,以及包括主成分分析(PCA)和非线性曲线拟合在内的数学方法,建立了预测样品相对色素含量的模型。其中,PCA 和空建模方法与非负偏最小二乘法相结合,用于预测基于拉曼图谱数据的相对色素含量。结果表明,基于光谱数据的 PCA、数学模型和空建模方法能有效预测相对色素含量。使用基于紫外-可见-近红外光谱的数学模型得出的预测结果误差约为 2%,而基于 ATR 傅立叶变换红外光谱的最佳预测结果在 1041 cm-1 处的误差为 3.6%。基于拉曼图谱数据的 PCA 预测和空模型预测的误差分别为 0.01-9.30% 和 0.28-7.15%。然而,根据 ATR 傅立叶变换红外数据结合比尔-朗伯定律预测的相对色素含量误差较大。该研究结果证实了利用光谱技术定量分析混合矿物颜料的强大可行性。
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Non-Destructive Prediction of the Mixed Mineral Pigment Content of Ancient Chinese Wall Paintings Based on Multiple Spectroscopic Techniques
This study first developed non-destructive and accurate methods to predict the relative contents of mixed mineral pigments in ancient Chinese wall paintings using multiple spectroscopic techniques. The colorimetry, attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR), ultraviolet–visible–near-infrared (UV-Vis-NIR) spectroscopy, and Raman spectroscopy were employed. Analyses were conducted including color difference, spectral reflection, ATR FT-IR spectra, and Raman mapping for simulated samples (malachite–lazurite mixed with rabbit glue samples) before and after aging. Models were then established for predicting the relative pigment contents of samples using UV-Vis-NIR and ATR FT-IR spectral data with Beer–Lambert law, and mathematical methods comprising principal component analysis (PCA) and nonlinear curve fitting. In particular, PCA and empty modeling methods combined with non-negative partial least squares were developed to predict the relative pigment contents based on Raman mapping data. The results demonstrated that approaches comprising PCA, mathematical model, and empty modeling based on the spectral data were effective at predicting the relative pigment contents. The predicted results obtained using the mathematical model based on UV-Vis-NIR spectra had an error of about 2%, and the best prediction based on ATR FT-IR spectra had an error of <3.6% at 1041 cm–1. The errors for the predictions using PCA and empty modeling based on Raman mapping data were 0.01–9.30% and 0.28–7.15%, respectively. However, the predicted relative pigment contents obtained based on ATR FT-IR data combined with the Beer–Lambert law had higher errors. The findings of this study confirm the strong feasibility of using spectroscopic techniques for quantitatively analyzing mixed mineral pigments.
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来源期刊
Applied Spectroscopy
Applied Spectroscopy 工程技术-光谱学
CiteScore
6.60
自引率
5.70%
发文量
139
审稿时长
3.5 months
期刊介绍: Applied Spectroscopy is one of the world''s leading spectroscopy journals, publishing high-quality peer-reviewed articles, both fundamental and applied, covering all aspects of spectroscopy. Established in 1951, the journal is owned by the Society for Applied Spectroscopy and is published monthly. The journal is dedicated to fulfilling the mission of the Society to “…advance and disseminate knowledge and information concerning the art and science of spectroscopy and other allied sciences.”
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