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Updated: Sep 11, 2025

Synchrotron X-ray Microdiffraction and Fluorescence Imaging of Mineral and Rock Samples
Published on: June 19, 2018
Colorimetry characteristics and color clustering of natural gem-quality spinel from Myanmar (Burma)
Jun Tang1,2, Wenfang Zhu3, Kaichao Liu1
1School of Gemmology, China University of Geosciences (Beijing), Beijing, China.
Abstract:
Color is the most critical factor in determining the value of gem-quality spinel. This paper examines the color mechanism and the colorimetric characteristics of spinel crystals under D65 and A light sources against nine neutral backgrounds. It also explores color clustering for over 400 spinel crystals in yellow, red, purple, and blue hues. Various analytical techniques were employed, including optical absorption spectroscopy, Energy-Dispersive X-ray Fluorescence analysis, a benchtop sphere spectrophotometer, the Munsell neutral value gray scale chart, and a standard illumination box. The study reveals distinct optical absorption peaks corresponding to different spinel colors, with these peaks being assigned to specific mechanisms based on previous research. Color analysis demonstrates that the chroma and hue of orange spinel crystals are primarily influenced by the red tone under both daylight and incandescent light. Additionally, red, and yellow tones significantly enhance the color of red spinel. For purple spinel, chroma shows a strong correlation with the a* value under both D65 and A light sources, while hue is easily influenced by the blue tone. In blue spinel, chroma is controlled by the green tone, and hue is affected by the blue tone. Lightness and chroma of all spinel colors increase significantly with the luminance factor of the Munsell neutral background, following a power function relationship with varying rates. However, the hue angle remains relatively unchanged, as gray backgrounds have minimal effect on hue. The colors of spinel crystals can be effectively predicted using calculated equations based on the luminance factor of the background under different light sources. The K-means clustering method is particularly effective for categorizing each spinel color into three distinct groups, which is crucial for developing a reliable color grading system for spinel.
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