Mapping chemical and bonding information using multivariate analysis of electron energy-loss spectrum images
Mapping chemical and bonding information using multivariate analysis of electron energy-loss spectrum images
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DOI：
10.1016/j.ultramic.2006.04.016
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发表时间：
2006-10-01
期刊：
影响因子：
2.2
通讯作者：
Keast, V. J.
中科院分区：
文献类型：
--
作者：
Bosman, M.;Watanabe, M.;Keast, V. J.
透射电子显微镜（TEM）中的电子能量损失谱（EELS）用于获得有关材料成分和化学键合类型的高分辨率信息。光谱成像，其中在图像中的每个像素处获取并存储完整的EEL光谱，给出了空间和光谱特征的精确相关性。然而，从光谱图像（SI）中包含的大量信息中确定和提取重要的光谱分量可能是困难的。本文表明，主成分分析的EEL SI可以用来提取化学相关的成分。通过加权或双向缩放主成分分析，可以提取成分和键合信息。部分还原的二氧化钛样品中的化学变化的映射和氮化硼和碳纳米管中的取向依赖性键合作为例子给出。(c)2006 Elsevier B.V.保留所有权利。
Electron energy-loss spectroscopy (EELS) in the transmission electron microscope (TEM) is used to obtain high-resolution information on the composition and the type of chemical bonding of materials. Spectrum imaging, where a full EEL spectrum is acquired and stored at each pixel in the image, gives an exact correlation of spatial and spectral features. However, determining and extracting the important spectral components from the large amount of information contained in a spectrum image (SI) can be difficult. This paper demonstrates that principal component analysis of EEL SIs can be used to extract chemically relevant components. With weighted or two-way scaled principal component analysis, both compositional and bonding information can be extracted. Mapping of the chemical variations in a partially reduced titanium dioxide sample and the orientation-dependent bonding in boron nitride and carbon nanotubes are given as examples. (c) 2006 Elsevier B.V. All rights reserved.