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

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Geochemistry of beryl varieties: comparative analysis and visualization of analytical data by principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE). / Skublov, Sergey G.; Gavrilchik, Aleksandra K.; Berezin, Aleksey V.

в: Journal of Mining Institute, Том 255, № 3, 26.07.2022, стр. 455-469.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

BibTeX

@article{94badff844c64e92a8ee5c330561fcab,

title = "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, Principal Component Analysis (PCA), SIMS method, t-SNE method",

author = "Skublov, {Sergey G.} and Gavrilchik, {Aleksandra K.} and Berezin, {Aleksey V.}",

year = "2022",

month = jul,

day = "26",

doi = "10.31897/PMI.2022.40",

language = "English",

volume = "255",

pages = "455--469",

journal = "Journal of Mining Institute",

issn = "2411-3336",

publisher = "Национальный минерально-сырьевой университет «Горный»",

number = "3",

}

RIS

TY - JOUR

T1 - Geochemistry of beryl varieties: comparative analysis and visualization of analytical data by principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE)

AU - Skublov, Sergey G.

AU - Gavrilchik, Aleksandra K.

AU - Berezin, Aleksey V.

PY - 2022/7/26

Y1 - 2022/7/26

N2 - 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.

AB - 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.

KW - beryl

KW - geochemistry of trace elements

KW - Principal Component Analysis (PCA)

KW - SIMS method

KW - t-SNE method

UR - http://www.scopus.com/inward/record.url?scp=85134849323&partnerID=8YFLogxK

U2 - 10.31897/PMI.2022.40

DO - 10.31897/PMI.2022.40

M3 - Article

AN - SCOPUS:85134849323

VL - 255

SP - 455

EP - 469

JO - Journal of Mining Institute

JF - Journal of Mining Institute

SN - 2411-3336

IS - 3

ER -

ID: 113709431