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Automated background subtraction technique for electron energy‐loss spectroscopy and application to semiconductor heterostructures
Author(s) -
ANGADI VEERENDRA C,
ABHAYARATNE CHARITH,
WALTHER THOMAS
Publication year - 2016
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12397
Subject(s) - deconvolution , electron energy loss spectroscopy , heterojunction , computational physics , spectroscopy , semiconductor , ionization , materials science , enhanced data rates for gsm evolution , background subtraction , ionization energy , analytical chemistry (journal) , optoelectronics , optics , chemistry , computer science , physics , transmission electron microscopy , nanotechnology , artificial intelligence , ion , pixel , organic chemistry , chromatography , quantum mechanics
Summary Electron energy‐loss spectroscopy (EELS) has become a standard tool for identification and sometimes also quantification of elements in materials science. This is important for understanding the chemical and/or structural composition of processed materials. In EELS, the background is often modelled using an inverse power‐law function. Core‐loss ionization edges are superimposed on top of the dominating background, making it difficult to quantify their intensities. The inverse power‐law has to be modelled for each pre‐edge region of the ionization edges in the spectrum individually rather than for the entire spectrum. To achieve this, the prerequisite is that one knows all core losses possibly present. The aim of this study is to automatically detect core‐loss edges, model the background and extract quantitative elemental maps and profiles of EELS, based on several EELS spectrum images (EELS SI) without any prior knowledge of the material. The algorithm provides elemental maps and concentration profiles by making smart decisions in selecting pre‐edge regions and integration ranges. The results of the quantification for a semiconductor thin film heterostructure show high chemical sensitivity, reasonable group III/V intensity ratios but also quantification issues when narrow integration windows are used without deconvolution.