Continental hydrothermal sedimentary siliceous rock and genesis of superlarge germanium (Ge) deposit hosted in coal: A study from the Lincang ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2004-11

AUTHORS

Huawen Qi, Ruizhong Hu, Wenchao Su, Liang Qi, Jiayi Feng

ABSTRACT

There are abundant hydrothermal sedimentary structures and plant fragment fossils in the siliceous rocks from the Lincang Ge deposit. The major element compositions of these siliceous rocks are characterized by high content SiO2, low TiO2 and Al2O3 concentrations, and low Al/(Al+Fe+Mn) ratios (0.010 on average). The siliceous rocks are distinctly enriched in Ge, Sb, As, W, and secondly enriched in Cs, U, Mo and Tl. Their total REE content are generally less than 1μg/g, LREE relatively concentrated, and the values of Eu anomaly and Ce anomaly vary from 0.452 to 5.141 and 0.997 to 1.174, respectively. Their NAS-normalized REE patterns are plain or left-inclined. The Oxygen isotope compositions of these siliceous rocks are similar to those of the hydrothermal siliceous sinter. The above characteristics, as well as the geological setting of the deposit, indicate these siliceous rocks formed in continental hydrothermal environment. As the interlayer or cliff of the Ge-rich coal seams, siliceous rocks tightly contacted with ore-body, and the contents of Ge in siliceous rocks vary from 5.6 to 360 μg/g (78 μg/g on average). The Ge content increased in coal which close to the siliceous rocks. With the increase of Ge content, the typical trace element ratios (i.e., Ge/Ga, Nb/Ta and U/Th) and REE patterns of Ge-rich coal are more close to those of the siliceous rocks. The Ge concentrated in coal seams of the Lincang Ge deposit might be transported by the hydrothermal water, which demonstrated by the siliceous rocks, during the coal-forming processes. More... »

PAGES

973

Identifiers

URI

http://scigraph.springernature.com/pub.10.1360/02yc0141

DOI

http://dx.doi.org/10.1360/02yc0141

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1065066446


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