Model-Based EELS Quantification and ELNES Phase Mapping Using Experimentally Measured Cross-Sections
Model-Based EELS Quantification and ELNES Phase Mapping Using Experimentally Measured Cross-Sections
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使用实验测量的横截面进行基于模型的 EELS 量化和 ELNES 相图
DOI：
10.1017/s1431927619003970
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发表时间：
2019
影响因子：
2.8
通讯作者：
P. Thomas
中科院分区：
文献类型：
--
作者：
B. Schaffer;Liam Spillane;P. Thomas
电子能量损失谱（EELS）可以以高灵敏度和高空间分辨率揭示被测样品的丰富信息。然而，由于各种原因，以最佳方式提取该信息通常是不平凡的。近年来，基于模型的量化简化并提高了EELS中量化过程的准确性（例如[1，2]）。可以表明，使用幂律衰减背景沿着与理论计算的横截面的组合作为预期边缘形状的一阶近似给出了执行成分量化的合理鲁棒的方式，在许多常见情况下自动分离出重叠边缘形状的贡献。只要有合适的EELS低损耗光谱可用，多重散射效应也可以被纳入这样的分析中，以进一步改善量化。虽然这种方法可以极大地提高量化的再现性和准确性，并允许在光谱成像应用中非常快速的地图计算，但一些紧密重叠的边缘组仍然不能自动地充分分离。这种能力是由理论截面不能正确地再现电子损失近边精细结构（ELNES）的功能，是目前在实验测量的光谱。
Electron-energy-loss spectroscopy (EELS) can reveal a wealth of information about the sample under investigation with high sensitivity and high spatial resolution. However, extracting this information in an optimal manner is often non-trivial for a variety of reasons. In recent years, model-based quantification has both simplified and improved the accuracy of the quantification process in EELS (e.g. [1, 2]). It could be shown that using a combination of a power-law decaying background along with theoretically computed cross-sections as first-order approximation of the expected edge shape gives a reasonably robust way of performing compositional quantification, automatically separating out contributions of overlapping edge shapes in many commonly encountered situations. Provided a suitable EELS low-loss spectrum is available, plural scattering effects can also be incorporated into such an analysis to further improve the quantification. While this approach can greatly improve the reproducibility and accuracy of quantification and allows for very fast map computations in the spectrum-imaging application, some groups of tightly overlapping edges can still not be sufficiently separated automatically. This inability is caused by the theoretical cross-sections not correctly reproducing the electron loss near-edge finestructure (ELNES) features that are present in experimentally measured spectra.