Quantitative analysis of electron spectroscopic imaging series

Micron(1997)

引用 54|浏览6
暂无评分
摘要
We have developed new methods to quantify the data acquired by electron spectroscopic imaging (ESI) which are based on recording series of energy filtered images across inner shell loss edges or in the low loss region. From the series of ESI images, electron energy loss (EEL) spectra can be extracted for any given image area, i.e. each individual pixel or an array of pixels over which the signal is integrated. The EEL spectra can subsequently be analysed using standard EELS quantification techniques. This makes it possible to obtain a measure of the absolute amount (area density) of an element in the given sample area or of the concentration ratios of one element with respect to other elements. From a series of ESI images in the low-loss region, accurate values of the specimen thickness can be obtained, provided the mean free path for inelastic scattering is known. As examples, results obtained on Si2N2O ceramics and thin Al2O3 films, which were grown by anodical oxidation, will be shown. The number densities of the atoms and concentration ratios can be measured with an accuracy of 10–15% using calculated inelastic scattering cross-sections. Similar accuracies can be obtained for the measurements of the specimen thickness, as will be shown for the thin Al2O3 films and for a wedge shaped silicon crystal. In the case of Si, convergent beam electron diffraction was employed to determine the mean free path for inelastic scattering. For the same sample, the thickness of the carbon contamination layers and the amorphous surface oxide layers were measured. The results of the latter measurements may provide important information for the quantitative evaluation of high resolution images or CBED patterns.
更多
查看译文
关键词
electron spectroscopic imaging,energy filtering transmission electron microscopy,quantitative analysis,concentration ratios,specimen thickness measurement,contamination layer thickness
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要