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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
Atom counting |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
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Volume |
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Pages |
91-144 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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In this chapter, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. We show that this method can be applied to nanocrystals of arbitrary shape, size, and atom type. The validity of the atom-counting results is confirmed by means of detailed image simulations and it is shown that the high sensitivity of our method enables us to count atoms with single atom sensitivity. |
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Publication Date |
2021-03-06 |
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Series Volume |
217 |
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ISBN |
978-0-12-824607-8; 1076-5670 |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177529 |
Serial |
6776 |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
Efficient fitting algorithm |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Pages |
73-90 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT) |
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Abstract |
An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic-resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighboring columns, enabling the analysis of a large field of view. To provide end-users with this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license. In this chapter, this efficient algorithm is applied to three different nanostructures for which the analysis of a large field of view is required. |
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2021-03-06 |
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Series Volume |
217 |
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ISBN |
978-0-12-824607-8; 1076-5670 |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177528 |
Serial |
6778 |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
General conclusions and future perspectives |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Pages |
243-253 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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Abstract |
This chapter provides an overview of statistical and quantitative methodologies that have pushed (scanning) transmission electron microscopy ((S)TEM) toward accurate and precise measurements of unknown structure parameters for understanding the relation between the structure of a material and its properties. Hereby, statistical parameter estimation theory has extensively been used which enabled not only measuring atomic column positions, but also quantifying the number of atoms, and detecting atomic columns as accurately and precisely as possible from experimental images. As a general conclusion, it can be stated that advanced statistical techniques are ideal tools to perform quantitative electron microscopy at the atomic scale. In the future, statistical methods will continue to be developed and novel quantification procedures will open up new possibilities for studying material structures at the atomic scale. |
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2021-03-06 |
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Series Volume |
217 |
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ISBN |
978-0-12-824607-8; 1076-5670 |
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UA library record |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177533 |
Serial |
6781 |
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Author |
Fatermans, J.; de Backer, A.; den Dekker, A.J.; Van Aert, S. |
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Title |
Image-quality evaluation and model selection with maximum a posteriori probability |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
215-242 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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Abstract |
The maximum a posteriori (MAP) probability rule for atom column detection can also be used as a tool to evaluate the relation between scanning transmission electron microscopy (STEM) image quality and atom detectability. In this chapter, a new image-quality measure is proposed that correlates well with atom detectability, namely the integrated contrast-to-noise ratio (ICNR). Furthermore, the working principle of the MAP probability rule is described in detail showing a close relation to the principles of model-selection methods. |
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2021-03-06 |
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Series Volume |
217 |
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ISBN |
978-0-12-824607-8; 1076-5670 |
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UA library record |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177532 |
Serial |
6782 |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
Introduction |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Pages |
1-28 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT) |
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2021-03-06 |
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Series Volume |
217 |
Series Issue |
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ISBN |
978-0-12-824607-8; 1076-5670 |
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UA library record |
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Open Access |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177525 |
Serial |
6784 |
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Permanent link to this record |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
Optimal experiment design for nanoparticle atom counting from ADF STEM images |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
145-175 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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Abstract |
In this chapter, the principles of detection theory are used to quantify the probability of error for atom counting from high-resolution scanning transmission electron microscopy (HRSTEM) images. Binary and multiple hypothesis testing have been investigated in order to determine the limits to the precision with which the number of atoms in a projected atomic column can be estimated. The probability of error has been calculated when using STEM images, scattering cross-sections or peak intensities as a criterion to count atoms. Based on this analysis, we conclude that scattering cross-sections perform almost equally well as images and perform better than peak intensities. Furthermore, the optimal STEM detector design can be derived for atom counting using the expression of the probability of error. We show that for very thin objects the low-angle annular dark-field (LAADF) regime is optimal and that for thicker objects the optimal inner detector angle increases. |
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Publication Date |
2021-03-06 |
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Series Volume |
217 |
Series Issue |
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Edition |
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ISBN |
978-0-12-824607-8; 1076-5670 |
Additional Links |
UA library record |
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Times cited |
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Open Access |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177530 |
Serial |
6785 |
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Author |
de Backer, A.; Fatermans, J.; den Dekker, A.J.; Van Aert, S. |
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Title |
Statistical parameter estimation theory : principles and simulation studies |
Type |
H2 Book chapter |
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Year |
2021 |
Publication |
Advances in imaging and electron physics
T2 – Advances in imaging and electron physics |
Abbreviated Journal |
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Volume |
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Pages |
29-72 |
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Keywords |
H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab |
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In this chapter, the principles of statistical parameter estimation theory for a quantitative analysis of atomic-resolution electron microscopy images are introduced. Within this framework, electron microscopy images are described by a parametric statistical model. Here, parametric models are introduced for different types of electron microscopy images: reconstructed exit waves, annular dark-field (ADF) scanning transmission electron microscopy (STEM) images, and simultaneously acquired ADF and annular bright-field (ABF) STEM images. Furthermore, the Cramér-Rao lower bound (CRLB) is introduced, i.e. a theoretical lower bound on the variance of any unbiased estimator. This CRLB is used to quantify the precision of the structure parameters of interest, such as the atomic column positions and the integrated atomic column intensities. |
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2021-03-06 |
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Series Volume |
217 |
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ISBN |
978-0-12-824607-8; 1076-5670 |
Additional Links |
UA library record |
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Notes |
ERC Consolidator project funded by the European Union grant #770887 Picometrics |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:177527 |
Serial |
6788 |
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Author |
Zhang, Z.; Lobato, I.; Brown, H.; Jannis, D.; Verbeeck, J.; Van Aert, S.; Nellist, P. |
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Title |
Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions |
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Dataset |
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2023 |
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Dataset; Electron microscopy for materials research (EMAT) |
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Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1]. The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions. We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration. Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3] Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference. Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script. Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689. |
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Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:203392 |
Serial |
9042 |
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Author |
Grünewald, L.; Chezganov, D.; De Meyer, R.; Orekhov, A.; Van Aert, S.; Bogaerts, A.; Bals, S.; Verbeeck, J. |
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Title |
Supplementary Information for “In-situ Plasma Studies using a Direct Current Microplasma in a Scanning Electron Microscope” |
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Year |
2023 |
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Dataset; Engineering sciences. Technology; Electron microscopy for materials research (EMAT); Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT) |
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Supplementary information for the article “In-situ Plasma Studies using a Direct Current Microplasma in a Scanning Electron Microscope” containing the videos of in-situ SEM imaging (mp4 files), raw data/images, and Jupyter notebooks (ipynb files) for data treatment and plots. Link to the preprint: https://doi.org/10.48550/arXiv.2308.15123 Explanation of the data files can be found in the Information.pdf file. The Videos folder contains the in-situ SEM image series mentioned in the paper. If there are any questions/bugs, feel free to contact me at lukas.grunewaldatuantwerpen.be |
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Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:203389 |
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9100 |
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Author |
Cioni, M.; Delle Piane, M.; Polino, D.; Rapetti, D.; Crippa, M.; Arslan Irmak, E.; Pavan, G.M.; Van Aert, S.; Bals, S. |
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Title |
Data for Sampling Real‐Time Atomic Dynamics in Metal Nanoparticles by Combining Experiments, Simulations, and Machine Learning |
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2024 |
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Dataset; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic‐resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state‐of‐the‐art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark‐field scanning transmission electron microscopy enables the acquisition of ten high‐resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allows resolving the real‐time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions. |
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Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:205843 |
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9143 |
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