J. Sittner, M. Merkulova, J. Godinho, A. Renno, V. Cnudde, M. Boone, T. de Schryver, D. van Loo, A. Roine, J. Liipo, B. Guy, S. Dewaele
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Furthermore, different monazite grains were investigated, which can be divided into two groups with respect to the content of different RE elements on the basis of the spectrum: La-Ce-rich and La-Ce-poor. In addition, samples from the Au-U Witwatersrand Supergroup demonstrate the potential applications of Sp-CT for geological samples. We measured different drill core samples from the Kalkoenkrans Reef at the Welkom Gold field. Sp-CT can distinguish gold, uraninite and galena grains based on their K-edge energies in the drill core without preparation.</p><p>Sittner, J., Godinho, J. R. A., Renno, A. D., Cnudde, V., Boone, M., De Schryver, T., Van Loo, D., Merkulova, M., Roine, A., & Liipo, J. (2020). Spectral X-ray computed micro tomography: 3-dimensional chemical imaging. 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引用次数: 0
摘要
地球科学中基于图像的分析工具对于矿物的表征是必不可少的,但大多数工具仅限于样品的抛光平面表面,缺乏3D信息。x射线显微计算机断层扫描(micro CT)提供了样品内部微观结构缺失的三维信息。然而,微型CT在矿物表征方面的一个主要缺点是缺乏化学信息,这使得矿物分类具有挑战性。光谱x射线微计算机断层扫描(Sp-CT)是一种新兴的、不断发展的工具,在医学、安全、材料科学和地质等不同领域都有应用。这种非破坏性的方法使用多像素光子计数探测器(PCD),如碲化镉(CdTe),结合传统的CT扫描仪(TESCAN CoreTOM)对样品进行成像,并检测其透射的多色x射线光谱。根据光谱,样品中的元素可以通过在特定k边能量处衰减的增加来识别。因此,在一次CT扫描中,可以区分样品内部化学性质不同的颗粒。该方法能够区分25 ~ 160 keV范围内的k边元素,适用于Z > 48的元素(Sittner et al., 2020)。我们给出了不同样品材料的结果。测量了不同的纯元素和元素氧化物,比较了理论和实测k边能的位置。所有测量的k边能量都略高于理论值,但根据结果可以开发出一种校正算法。此外,对不同的独居石颗粒进行了研究,根据不同稀土元素的含量,可以将其分为富la - ce和贫la - ce两类。此外,来自Au-U Witwatersrand超级群的样品展示了Sp-CT在地质样品中的潜在应用。我们测量了来自Welkom金矿Kalkoenkrans礁的不同钻孔岩芯样本。Sp-CT可根据钻芯中的k边能对金、铀矿和方铅矿晶粒进行判别,无需预处理。Sittner, J., Godinho, J. R. A., Renno, A. D., Cnudde, V., Boone, M., De Schryver, T., Van Loo, D., Merkulova, M., Roine, A.和Liipo, J.(2020)。光谱x射线计算机显微断层扫描:三维化学成像。x射线光谱,9月,1–
Spectral X-ray computed micro tomography: a tool for 3-dimensional chemical imaging
Image-based analytical tools in geosciences are indispensable for the characterization of minerals, but most of them are limited to the surface of a polished plane in a sample and lack 3D information. X-ray micro computed tomography (micro CT) provides the missing 3D information of the microstructures inside samples. However, a major drawback of micro CT in the characterization of minerals is the lack of chemical information that makes mineral classification challenging.
Spectral X-ray micro computed tomography (Sp-CT) is a new and evolving tool in different applications such as medicine, security, material science, and geology. This non-destructive method uses a multi-pixel photon-counting detector (PCD) such as cadmium telluride (CdTe) in combination with a conventional CT scanner (TESCAN CoreTOM) to image a sample and detect its transmitted polychromatic X-ray spectrum. Based on the spectrum, elements in a sample can be identified by an increase in attenuation at specific K-edge energies. Therefore, chemically different particles can be distinguished inside a sample from a single CT scan. The method is able to distinguish elements with K-edges in the range from 25 to 160 keV, which applies to elements with Z > 48 (Sittner et al., 2020).
We present results from various sample materials. Different pure elements and element oxides were measured to compare the position of theoretical and measured K-edge energies. All measured K-edge energies are slightly above the theoretical value, but based on the results a correction algorithm could be developed. Furthermore, different monazite grains were investigated, which can be divided into two groups with respect to the content of different RE elements on the basis of the spectrum: La-Ce-rich and La-Ce-poor. In addition, samples from the Au-U Witwatersrand Supergroup demonstrate the potential applications of Sp-CT for geological samples. We measured different drill core samples from the Kalkoenkrans Reef at the Welkom Gold field. Sp-CT can distinguish gold, uraninite and galena grains based on their K-edge energies in the drill core without preparation.
Sittner, J., Godinho, J. R. A., Renno, A. D., Cnudde, V., Boone, M., De Schryver, T., Van Loo, D., Merkulova, M., Roine, A., & Liipo, J. (2020). Spectral X-ray computed micro tomography: 3-dimensional chemical imaging. X-Ray Spectrometry, September, 1–14.