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“Atom counting from a combination of two ADF STEM images”. Şentürk DG, Yu CP, De Backer A, Van Aert S, Ultramicroscopy 255, 113859 (2024). http://doi.org/10.1016/j.ultramic.2023.113859
Abstract: To understand the structure–property relationship of nanostructures, reliably quantifying parameters, such as the number of atoms along the projection direction, is important. Advanced statistical methodologies have made it possible to count the number of atoms for monotype crystalline nanoparticles from a single ADF STEM image. Recent developments enable one to simultaneously acquire multiple ADF STEM images. Here, we present an extended statistics-based method for atom counting from a combination of multiple statistically independent ADF STEM images reconstructed from non-overlapping annular detector collection regions which improves the accuracy and allows one to retrieve precise atom-counts, especially for images acquired with low electron doses and multiple element structures.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.2
DOI: 10.1016/j.ultramic.2023.113859
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“Convexity constraints on linear background models for electron energy-loss spectra”. Van den Broek W, Jannis D, Verbeeck J, Ultramicroscopy 254, 113830 (2023). http://doi.org/10.1016/j.ultramic.2023.113830
Abstract: In this paper convexity constraints are derived for a background model of electron energy loss spectra (EELS) that is linear in the fitting parameters. The model outperforms a power-law both on experimental and simulated backgrounds, especially for wide energy ranges, and thus improves elemental quantification results. Owing to the model’s linearity, the constraints can be imposed through fitting by quadratic programming. This has important advantages over conventional nonlinear power-law fitting such as high speed and a guaranteed unique solution without need for initial parameters. As such, the need for user input is significantly reduced, which is essential for unsupervised treatment of large datasets. This is demonstrated on a demanding spectrum image of a semiconductor device sample with a high number of elements over a wide energy range.
Keywords: A1 Journal Article; Electron Microscopy for Materials Science (EMAT) ;
Impact Factor: 2.2
DOI: 10.1016/j.ultramic.2023.113830
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“Element specific atom counting for heterogeneous nanostructures: Combining multiple ADF STEM images for simultaneous thickness and composition determination”. Şentürk DG, De Backer A, Van Aert S, Ultramicroscopy 259, 113941 (2024). http://doi.org/10.1016/j.ultramic.2024.113941
Abstract: In this paper, a methodology is presented to count the number of atoms in heterogeneous nanoparticles based on the combination of multiple annular dark field scanning transmission electron microscopy (ADF STEM) images. The different non-overlapping annular detector collection regions are selected based on the principles of optimal statistical experiment design for the atom-counting problem. To count the number of atoms, the total intensities of scattered electrons for each atomic column, the so-called scattering cross-sections, are simultaneously compared with simulated library values for the different detector regions by minimising the squared differences. The performance of the method is evaluated for simulated Ni@Pt and Au@Ag core-shell nanoparticles. Our approach turns out to be a dose efficient alternative for the investigation of beam-sensitive heterogeneous materials as compared to the combination of ADF STEM and energy dispersive X-ray spectroscopy.
Keywords: A1 Journal Article; Electron Microscopy for Materials Science (EMAT) ;
Impact Factor: 2.2
DOI: 10.1016/j.ultramic.2024.113941
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