摘要
为了研究多种釉色汝官瓷和钧官瓷的原料来源、成分和分类关系,正确鉴别两窑瓷器,应用质子激发X荧光分析(PIXE)技术测定了一组清凉寺窑汝官瓷片和一组钧台窑钧官瓷片的主量化学组成,应用多元统计分析方法对测试数据进行了分析,结果表明:多数汝官瓷胎、钧官瓷胎样品的原料产地和成分接近但有所不同;汝官瓷釉和钧官瓷釉的原料产地和配方则明显不同;从主量化学组成上可以较好地区分汝官瓷釉和钧官瓷釉样品。分析结果可为深入研究汝官瓷和钩官瓷的原料产地、起源关系、真伪鉴别和提高仿古瓷器的质量等方面提供可借鉴的科学依据。
The Qing Liang Temple Ru Official kiln in Baofeng, Hennan province and the Jun Tat Jun Official kiln in Yuzhou, Hennan province, are two of the famous antique kilns in China. Highly valued, the porcelains from the two kilns are well recognized. The two kilns, close to each other, produced both Ru porcelains and Jun porcelains. The Ru ware and the Jun ware seem very similar, as a proverb said that there is no discrimination between the Jun porcelains and the Ru porcelains＇. But do they have no common in fact？ Can they be classified exactly？ To answer these questions, the chemical composition of some Ru and Jun ware samples and the source of their raw materials were studied. The main chemical composition was determined using proton induced X- ray emission （PIXE） technique, and the data obtained were analyzed by multivariate statistical analysis. The experimental results showed that the sources of the raw materials of the most of Ru and Jun porcelain bodies are close, but different in some aspects, while the sources and the composition of their glaze are highly different. It is a good method to discriminate the Ru ware glaze from Jun ware glaze by comparison of their major chemical compositions. The method could be useful for further research on the source of raw materials, the relationships of the source and the identification of the Ru and the Jun porcelains. Meanwhile, it can also provide some scientific information to improve the quality of the imitation of antique porcelains.
出处
《文物保护与考古科学》
2007年第3期1-5,共5页
Sciences of Conservation and Archaeology
基金
国家自然科学重点基金(50432010)
国家自然科学基金(50572097)
河南省自然科学基金(0611011500)
中国科学院核分析技术重点实验室基金(K-113)
郑州大学历史文化遗产保护中心资助项目资助
关键词
汝官瓷
钧官瓷
PIXE
主量化学组成
多元统计分析
Ru Official ware
Jun Official ware
PIXE
The major chemical composition
Multivariate statistical analysis
