Geochemistry of beryl varieties: comparative analysis and visualization of analytical data by principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE)

Abstract

A study of the trace element composition of beryl varieties (469 SIMS analyses) was carried out. Red beryls are distinguished by a higher content of Ni, Sc, Mn, Fe, Ti, Cs, Rb, K, and B and lower content of Na and water. Pink beryls are characterized by a higher content of Cs, Rb, Na, Li, Cl, and water with lower content of Mg and Fe. Green beryls are defined by the increased content of Cr, V, Mg, Na, and water with reduced Cs. A feature of yellow beryls is the reduced content of Mg, Cs, Rb, K, Na, Li, and Cl. Beryls of various shades of blue and dark blue (aquamarines) are characterized by higher Fe content and lower Cs and Rb content. For white beryls, increased content of Na and Li has been established. Principal Component Analysis (PCA) for the CLR-transformed dataset showed that the first component separates green beryls from other varieties. The second component divides pink and red beryls. The stochastic neighborhood embedding method with t-distribution (t-SNE) with CLR-transformed data demonstrated the contrasting compositions of green beryls relative to other varieties. Red and pink beryls form the most compact clusters.

Keywords

• beryl
• geochemistry of trace elements
• sims method
• principal component analysis (pca)
• t-sne method