Suppr超能文献

波长色散谱仪与硅漂移探测器能谱仪:天然硅酸盐矿物定量化学分析比较的病例报告

WDS versus silicon drift detector EDS: a case report for the comparison of quantitative chemical analyses of natural silicate minerals.

作者信息

Cubukçu H Evren, Ersoy Orkun, Aydar Erkan, Cakir Uner

机构信息

Department of Geological Engineering, 06800 Beytepe, Ankara, Turkey.

出版信息

Micron. 2008;39(2):88-94. doi: 10.1016/j.micron.2006.11.004. Epub 2006 Dec 11.

Abstract

Electron probe microanalysis (EPMA) is an essential analytical approach to determine elemental concentrations of various solid specimens quantitatively in mineralogical, petrological and materials research. Either wavelength dispersive X-ray (WDS) or energy dispersive X-ray (EDS) spectrometric techniques can collect the characteristic X-rays generated from each element in the specimen by an incident electron beam in order to define chemical constituents. Although WDS has been the preferred technique because of its higher spectral resolution and ability to detect trace elements, new generation EDS systems with silicon drift detectors (SDD), equipped with thin windows and integrated digital processing electronics, are claimed to approach the WDS throughput. In this study, we compared the analytical capability of a SDD EDS system with respect to WDS equipped systems on natural silicate minerals. For this purpose, natural rock samples, in which the silicate minerals present had already been analysed by various WDS systems, were chosen to compare these results with the ones acquired with a SDD EDS system. SDD EDS yielded satisfactory results for major elements (Na, Mg, Al, Si, K, Ca, Ti, Mn and Fe) compared with the results of the same minerals obtained by various WDS systems.

摘要

电子探针微分析(EPMA)是矿物学、岩石学和材料研究中定量测定各种固体样品元素浓度的重要分析方法。波长色散X射线(WDS)或能量色散X射线(EDS)光谱技术都可以通过入射电子束收集样品中各元素产生的特征X射线,以确定化学成分。尽管由于WDS具有更高的光谱分辨率和检测微量元素的能力,一直是首选技术,但新一代配备硅漂移探测器(SDD)、薄窗和集成数字处理电子设备的EDS系统据称已接近WDS的通量。在本研究中,我们比较了SDD EDS系统与配备WDS的系统对天然硅酸盐矿物的分析能力。为此,选择了天然岩石样品,其中存在的硅酸盐矿物已通过各种WDS系统进行了分析,以便将这些结果与用SDD EDS系统获得的结果进行比较。与各种WDS系统对相同矿物获得的结果相比,SDD EDS对主要元素(Na、Mg、Al、Si、K、Ca、Ti、Mn和Fe)得出了令人满意的结果。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验