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| Application of Non-Destructive Spectroscopic Techniques for Pigment Identification and Painting Skills Study of Large Format Oil Paintings |
| ZHAO Dan-dan1, YANG Qin1, 2, WU Na1, 2, LI Yu3, 4, 5, ZHANG Tuo1, YAN Yu1, HAO Xin-ying6 |
1. National Museum of China, Beijing 100006, China
2. Key Scientific Research Base of Metal Conservation (National Museum of China), National Cultural Heritage Administration, Beijing 100079, China
3. Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
4. Key Scientific Research Base of Nuclear Technology Application and Equipment in the Field of Cultural Heritage (Institute of High Energy Physics, Chinese Academy of Sciences), National Cultural Heritage Administration, Beijing 100049, China
5. Spallation Neutron Source Science Center, China Spallation Neutron Source, Dongguan 523803, China
6. Department of History of Science and Scientific Archaeology, University of Science and Technology of China, Hefei 230026, China
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Abstract Many effective analytical techniques face limitations when applied in the field of cultural heritage conservation due to artifact size and on-site environmental constraints. Large-format oil paintings in museum collections present particular challenges, as they possess both movable and immovable characteristics, making efficient on-site analysis difficult. In this work, we selected the large-format oil painting “Autumn on the Dnieper River” from the collection of the National Museum of China as a case study. Considering the painting's specific attributes and the practical conditions of its conservation setting, a non-destructive multi-technique approach consisting of multispectral imaging (MSI), macro X-ray fluorescence (MA-XRF) mapping, and fiber optic reflectance spectroscopy (FORS), was employed for pigment identification and painting techniques investigation. The results demonstrate that: (1) clustering analysis based on macroscopic spectral imaging provides valuable information regarding artistic techniques and pigment classification; (2) segmentation of multispectral images based on the spatial distribution of surface pigments enables precise mapping of pigment application areas; and (3) in-depth analysis using FORS, combined with digital image extraction, establishes correlations between pigment distribution and material composition, thereby allowing accurate identification of pigment distribution on the painting's surface. The integrated application of these convenient and adaptable methods allows for the rapid and accurate acquisition of critical information about large-format oil paintings, including details of varnish and underdrawing layers, evidence of modifications and hidden information in the painting process, as well as the types and spatial distribution of pigments.
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Received: 2025-03-11
Accepted: 2025-08-22
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