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Quantitative analysis of backscattered‐electron contrast in scanning electron microscopy
Author(s) -
Čalkovský Martin,
Müller Erich,
Gerthsen Dagmar
Publication year - 2023
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.13148
Subject(s) - scanning electron microscope , materials science , homogeneity (statistics) , monte carlo method , electron , characterization (materials science) , wedge (geometry) , electron microscope , optics , analytical chemistry (journal) , biomedical engineering , nanotechnology , computer science , chemistry , physics , mathematics , statistics , composite material , medicine , chromatography , quantum mechanics , machine learning
Abstract Backscattered‐electron scanning electron microscopy (BSE‐SEM) imaging is a valuable technique for materials characterisation because it provides information about the homogeneity of the material in the analysed specimen and is therefore an important technique in modern electron microscopy. However, the information contained in BSE‐SEM images is up to now rarely quantitatively evaluated. The main challenge of quantitative BSE‐SEM imaging is to relate the measured BSE intensity to the backscattering coefficient η and the (average) atomic number Z to derive chemical information from the BSE‐SEM image. We propose a quantitative BSE‐SEM method, which is based on the comparison of Monte–Carlo (MC) simulated and measured BSE intensities acquired from wedge‐shaped electron‐transparent specimens with known thickness profile. The new method also includes measures to improve and validate the agreement of the MC simulations with experimental data. Two different challenging samples (ZnS/Zn(O x S 1– x )/ZnO/Si‐multilayer and PTB7/PC 71 BM‐multilayer systems) are quantitatively analysed, which demonstrates the validity of the proposed method and emphasises the importance of realistic MC simulations for quantitative BSE‐SEM analysis. Moreover, MC simulations can be used to optimise the imaging parameters (electron energy, detection‐angle range) in advance to avoid tedious experimental trial and error optimisation. Under optimised imaging conditions pre‐determined by MC simulations, the BSE‐SEM technique is capable of distinguishing materials with small composition differences.