Near-Infrared Spectroscopic Study of Chlorite Minerals
Autor: | Meifang Ye, Haihui Han, Ling Han, Zhuan Zhang, Min Yang, Guangli Ren |
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Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
Materials science
Mineral Article Subject Infrared Near-infrared spectroscopy Analytical chemistry 02 engineering and technology 010502 geochemistry & geophysics 021001 nanoscience & nanotechnology 01 natural sciences Fluorescence Atomic and Molecular Physics and Optics Hydrothermal circulation Analytical Chemistry chemistry.chemical_compound chemistry lcsh:QC350-467 0210 nano-technology Absorption (electromagnetic radiation) Spectroscopy Chlorite lcsh:Optics. Light 0105 earth and related environmental sciences |
Zdroj: | Journal of Spectroscopy, Vol 2018 (2018) |
ISSN: | 2314-4939 2314-4920 |
Popis: | The mineral chemistry of twenty chlorite samples from the United States Geological Survey (USGS) spectral library and two other regions, having a wide range of Fe and Mg contents and relatively constant Al and Si contents, was studied via infrared (IR) spectroscopy, near-infrared (NIR) spectroscopy, and X-ray fluorescence (XRF) analysis. Five absorption features of the twenty samples near 4525, 4440, 4361, 4270, and 4182 cm−1 were observed, and two diagnostic features at 4440 and 4280 cm−1 were recognized. Assignments of the two diagnostic features were made for two combination bands (ν+δAlAlO−OH and ν+δSiAlO−OH) by regression with IR fundamental absorptions. Furthermore, the determinant factors of the NIR band position were found by comparing the band positions with relative components. The results showed that Fe/(Fe + Mg) values are negatively correlated with the two NIR combination bands. The findings provide an interpretation of the NIR band formation and demonstrate a simple way to use NIR spectroscopy to discriminate between chlorites with different components. More importantly, spectroscopic detection of mineral chemical variations in chlorites provides geologists with a tool with which to collect information on hydrothermal alteration zones from hyperspectral-resolution remote sensing data. |
Databáze: | OpenAIRE |
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