Abstract

This paper analyzes the relationship between the type, decoration, and chemical composition of ancient glass objects and their surface weathering in order to gain a deeper understanding and identification of the artifacts. First, the correlation between surface weathering and glass type, decoration, and color is analyzed. For lead-barium glass, a linear programming model was developed to predict the chemical composition content before weathering using a great likelihood function method. For weathered high-potassium glass, this paper found that the color of high-potassium glass was light when the chemical composition contained sodium oxide and dark when it did not contain sodium oxide. For the chemical composition of unweathered high-potassium glass and lead-barium glass, cluster analysis was used to classify the known samples. Then, the chemical composition of glass artifacts of unknown categories was analyzed and identified, using the use of distance function as a test function to give classification for samples of unknown types. Finally, to address the issue of correlation and variability of chemical compositions in different categories of glass artifacts, SPSSPRO was used to analyze the correlation between the chemical compositions contained in the two types of samples, and the results showed that the variability of phosphorus oxide free and sodium oxide between the chemical compositions of high-potassium glass and lead-barium glass was greater.

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