用于关键矿物化学鉴定的光谱x射线计算机断层扫描

Florian Buyse , Matthieu N. Boone , Frederic Van Assche , Stéphane Faucher , Peter Moonen , Stijn Dewaele , Veerle Cnudde
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引用次数: 0

摘要

使用高分辨率x射线断层扫描(µCT)区分矿物依赖于衰减系数µ的明显差异。µ值取决于物质密度ρ和矿物相的有效原子序数Zeff之间的相互作用。当这种相互作用给出相似的µ值时,识别矿物相就会出现困难,从而限制了µCT图像内的对比度。解开这两种依赖关系对于改善关键矿物的三维化学鉴定至关重要。基于实验室的方法和技术通常包含不同的测量方法,但在多相地质样品上的应用潜力有限。使用基于实验室的高z光谱微CT,我们研究了在高z光谱探测器的实际范围内直接识别化学元素的潜力。本文使用两种光谱微CT装置比较了三个矿床的结果。利用k边缘成像技术可以正确地识别出Z值高于钼且浓度至少有一定质量百分比的化学元素。不同的高z光谱探测器的适用性在很大程度上取决于样品组成的先验知识的可用性。定量元素浓度是元素和样品特定的,目前不允许最佳的自动化矿物学解决方案。通过对能量依赖的µ曲线进行专门分析,可以提高矿物的三维识别能力,因此这将是未来工作的重点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spectral X-ray computed tomography for the chemical identification of critical minerals
Differentiating minerals using high-resolution X-ray tomography (µCT) relies on distinct differences in the attenuation coefficient µ. The µ value depends on an interplay between the material density ρ and the effective atomic number Zeff of a mineral phase. Difficulties in identifying mineral phases arise when this interplay gives similar µ values and thus limited contrast within µCT images. Untangling these two dependencies is essential to improve the three-dimensional chemical identification of critical minerals. Lab-based methods and techniques often incorporate different measures, but only show a limited application potential on multiphase geological samples. Using high-Z spectral laboratory-based µCT we studied the potential of directly identifying chemical elements within the practical margins of high-Z spectral detectors. This paper compares the results from three mineral deposits using two spectral µCT setups. Chemical elements with a Z higher than molybdenum and a concentration of at least some weight percentage were correctly identified using K-edge imaging. The suitability of the different high-Z spectral detectors depends largely on the availability of prior knowledge of the sample composition. Quantifying elemental concentrations is element- and sample specific and currently does not allow for optimal automated mineralogy solutions. Improving the three-dimensional identification of minerals can be achieved with dedicated analyses of the energy-dependent µ curve and therefore will remain the focus of future work.
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