| 光谱学与光谱分析 |
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| Study on Vibrational Spectra Characteristics of Gem-Quality Natrolite |
| LIU Xian-yu1, 2, 3, SHEN Xi-tian2, LU Ren2, ZHAO Shan-rong4 |
1. Hubei Subsurface Multi-scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074，China
2. Gemological Institute, China University of Geosciences, Wuhan 430074, China
3. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, China
4. Faculty of Earth Sciences, China University of Geosciences, Wuhan 430074, China |
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Abstract Recently, there is a batch of colorless faceted gem-quality natrolite appear in the international jewelry market. In order to provide some information that can help us to distinguish them from the imitations. The infrared spectrometer and Raman spectrometer were employed to study the characteristics of the vibrational spectrum of three natrolite samples in this article. The typical infrared spectra shows that: the absorption region 4 000～1 200 cm-1 is induced by stretching vibration of the hydroxyl group, the strong absorption peaks range from 1 200～600 cm-1 are relative with the anti-symmetry and symmetry stretching vibration of tetrahedral T—O bonds (T=Si or Al). The Raman spectra scattering peaks are located in the range of 300～600 and 700～1 200 cm-1. The low intensity Raman scattering spectrum in the range of 300～360 cm-1 corresponds to the vibration of the water molecules in the crystal. The medium intensity Raman scattering spectrum is assigned to the deformation of SiO4 tetrahedra. The Raman spectra scattering peak at 726 cm-1 is assigned to the stretching vibration of Al—O; The Si—O stretching vibration displays the Raman spectra scattering peaks at 974, 1 038 and 1 084 cm-1.
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Received: 2013-12-25
Accepted: 2014-06-17
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Corresponding Authors:
LIU Xian-yu
E-mail: kipperrocklau@gmail.com
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[1] QI Jin-ying, JIANG Shao-ying（齐进英，江绍英）. Journal of the Chinese Ceramic Society(硅酸盐学报), 1982, 10(4): 478.
[2] QI Jin-ying, JIANG Shao-ying（齐进英，江绍英）. Chinese Science Bulletin(科学通报), 1983, 3: 162.
[3] Chen T T, Chao G Y. Canadian Mineralogist, 1980, 18: 77.
[4] Peng C J. American Mineralogist, 1955, 40(9-10): 853.
[5] Pechar F, Rykl D. Canadian Mineralogist, 1983, 21: 693.
[6] Pechar F. Chemical Papers-Chemicke Zvesti (in Czech), 1982, 36: 773.
[7] Dutta P K, Barco B D. Journal of Physical Chemistry, 1985, 89: 1862. |
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