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“Optimal experimental design for nano-particle atom-counting from high-resolution STEM images”. de Backer A, De wael A, Gonnissen J, Van Aert S, Ultramicroscopy 151, 46 (2015). http://doi.org/10.1016/j.ultramic.2014.10.015
Abstract: In the present paper, the principles of detection theory are used to quantify the probability of error for atom-counting from high resolution scanning transmission electron microscopy (HR STEM) 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 for the probability of error. We show that for very thin objects LAADF is optimal and that for thicker objects the optimal inner detector angle increases.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
Times cited: 24
DOI: 10.1016/j.ultramic.2014.10.015
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“Atom counting”. de Backer A, Fatermans J, den Dekker AJ, Van Aert S Advances in imaging and electron physics
T2 – Advances in imaging and electron physics. page 91 (2021).
Abstract: 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.
Keywords: H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
DOI: 10.1016/BS.AIEP.2021.01.004
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“Efficient fitting algorithm”. de Backer A, Fatermans J, den Dekker AJ, Van Aert S Advances in imaging and electron physics
T2 – Advances in imaging and electron physics. page 73 (2021).
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.
Keywords: H2 Book chapter; Electron microscopy for materials research (EMAT)
DOI: 10.1016/BS.AIEP.2021.01.003
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“General conclusions and future perspectives”. de Backer A, Fatermans J, den Dekker AJ, Van Aert S Advances in imaging and electron physics
T2 – Advances in imaging and electron physics. page 243 (2021).
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.
Keywords: H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
DOI: 10.1016/BS.AIEP.2021.01.008
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“Introduction”. de Backer A, Fatermans J, den Dekker AJ, Van Aert S Advances in imaging and electron physics
T2 – Advances in imaging and electron physics. page 1 (2021).
Keywords: H2 Book chapter; Electron microscopy for materials research (EMAT)
DOI: 10.1016/BS.AIEP.2021.01.001
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“Optimal experiment design for nanoparticle atom counting from ADF STEM images”. de Backer A, Fatermans J, den Dekker AJ, Van Aert S Advances in imaging and electron physics
T2 – Advances in imaging and electron physics. page 145 (2021).
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.
Keywords: H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
DOI: 10.1016/BS.AIEP.2021.01.005
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“Statistical parameter estimation theory : principles and simulation studies”. de Backer A, Fatermans J, den Dekker AJ, Van Aert S Advances in imaging and electron physics
T2 – Advances in imaging and electron physics. page 29 (2021).
Abstract: 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.
Keywords: H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
DOI: 10.1016/BS.AIEP.2021.01.002
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“Three-dimensional atomic models from a single projection using Z-contrast imaging: verification by electron tomography and opportunities”. De Backer A, Jones L, Lobato I, Altantzis T, Goris B, Nellist PD, Bals S, Van Aert S, Nanoscale 9, 8791 (2017). http://doi.org/10.1039/C7NR02656K
Abstract: In order to fully exploit structure–property relations of nanomaterials, three-dimensional (3D) characterization at the atomic scale is often required. In recent years, the resolution of electron tomography has reached the atomic scale. However, such tomography typically requires several projection images demanding substantial electron dose. A newly developed alternative circumvents this by counting the number of atoms across a single projection. These atom counts can be used to create an initial atomic model with which an energy minimization can be applied to obtain a relaxed 3D reconstruction of the nanoparticle. Here, we compare, at the atomic scale, this single projection reconstruction approach with tomography and find an excellent agreement. This new approach allows for the characterization of beam-sensitive materials or where the acquisition of a tilt series is impossible. As an example, the utility is illustrated by the 3D atomic scale characterization of a nanodumbbell on an in situ heating holder of limited tilt range.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 7.367
Times cited: 33
DOI: 10.1039/C7NR02656K
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“Dose limited reliability of quantitative annular dark field scanning transmission electron microscopy for nano-particle atom-counting”. de Backer A, Martinez GT, MacArthur KE, Jones L, Béché, A, Nellist PD, Van Aert S, Ultramicroscopy 151, 56 (2015). http://doi.org/10.1016/j.ultramic.2014.11.028
Abstract: Quantitative annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique to characterise nano-particles on an atomic scale. Because of their limited size and beam sensitivity, the atomic structure of such particles may become extremely challenging to determine. Therefore keeping the incoming electron dose to a minimum is important. However, this may reduce the reliability of quantitative ADF STEM which will here be demonstrated for nano-particle atom-counting. Based on experimental ADF STEM images of a real industrial catalyst, we discuss the limits for counting the number of atoms in a projected atomic column with single atom sensitivity. We diagnose these limits by combining a thorough statistical method and detailed image simulations.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
Times cited: 29
DOI: 10.1016/j.ultramic.2014.11.028
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“Atom counting in HAADF STEM using a statistical model-based approach : methodology, possibilities, and inherent limitations”. de Backer A, Martinez GT, Rosenauer A, Van Aert S, Ultramicroscopy 134, 23 (2013). http://doi.org/10.1016/j.ultramic.2013.05.003
Abstract: In the present paper, a statistical model-based method to count the number of atoms of monotype crystalline nanostructures from high resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images is discussed in detail together with a thorough study on the possibilities and inherent limitations. In order to count the number of atoms, it is assumed that the total scattered intensity scales with the number of atoms per atom column. These intensities are quantitatively determined using model-based statistical parameter estimation theory. The distribution describing the probability that intensity values are generated by atomic columns containing a specific number of atoms is inferred on the basis of the experimental scattered intensities. Finally, the number of atoms per atom column is quantified using this estimated probability distribution. The number of atom columns available in the observed STEM image, the number of components in the estimated probability distribution, the width of the components of the probability distribution, and the typical shape of a criterion to assess the number of components in the probability distribution directly affect the accuracy and precision with which the number of atoms in a particular atom column can be estimated. It is shown that single atom sensitivity is feasible taking the latter aspects into consideration.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
Times cited: 48
DOI: 10.1016/j.ultramic.2013.05.003
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“Experimental reconstructions of 3D atomic structures from electron microscopy images using a Bayesian genetic algorithm”. De Backer A, Van Aert S, Faes C, Arslan Irmak E, Nellist PD, Jones L, N P J Computational Materials 8, 216 (2022). http://doi.org/10.1038/s41524-022-00900-w
Abstract: We introduce a Bayesian genetic algorithm for reconstructing atomic models of monotype crystalline nanoparticles from a single projection using Z-contrast imaging. The number of atoms in a projected atomic column obtained from annular dark field scanning transmission electron microscopy images serves as an input for the initial three-dimensional model. The algorithm minimizes the energy of the structure while utilizing a priori information about the finite precision of the atom-counting results and neighbor-mass relations. The results show promising prospects for obtaining reliable reconstructions of beam-sensitive nanoparticles during dynamical processes from images acquired with sufficiently low incident electron doses.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
DOI: 10.1038/s41524-022-00900-w
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“High precision measurements of atom column positions using model-based exit wave reconstruction”. de Backer A, Van Aert S, van Dyck D, Ultramicroscopy 111, 1475 (2011). http://doi.org/10.1016/j.ultramic.2011.07.002
Abstract: In this paper, it has been investigated how to measure atom column positions as accurately and precisely as possible using a focal series of images. In theory, it is expected that the precision would considerably improve using a maximum likelihood estimator based on the full series of focal images. As such, the theoretical lower bound on the variances of the unknown atom column positions can be attained. However, this approach is numerically demanding. Therefore, maximum likelihood estimation has been compared with the results obtained by fitting a model to a reconstructed exit wave rather than to the full series of focal images. Hence, a real space model-based exit wave reconstruction technique based on the channelling theory is introduced. Simulations show that the reconstructed complex exit wave contains the same amount of information concerning the atom column positions as the full series of focal images. Only for thin samples, which act as weak phase objects, this information can be retrieved from the phase of the reconstructed complex exit wave.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 8
DOI: 10.1016/j.ultramic.2011.07.002
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“StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images”. De Backer A, van den Bos KHW, Van den Broek W, Sijbers J, Van Aert S, Ultramicroscopy 171, 104 (2016). http://doi.org/10.1016/j.ultramic.2016.08.018
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 neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, has been investigated. The highest attainable precision is reached even for low dose images. Furthermore, the advantages of the model-based approach taking into account overlap between neighbouring columns are highlighted. This is done for the estimation of the distance between two neighbouring columns as a function of their distance and for the estimation of the scattering cross-section which is compared to the integrated intensity from a Voronoi cell. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 43
DOI: 10.1016/j.ultramic.2016.08.018
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“StatSTEM: An efficient program for accurate and precise model-based quantification of atomic resolution electron microscopy images”. De Backer A, van den Bos KHW, Van den Broek W, Sijbers J, Van Aert S, Journal of physics : conference series
T2 –, Electron Microscopy and Analysis Group Conference 2017 (EMAG2017), 3-6 July 2017, Manchester, UK 902, 012013 (2017). http://doi.org/10.1088/1742-6596/902/1/012013
Abstract: An efficient model-based estimation algorithm is introduced in order 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 the overlap between neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, is investigated. The highest attainable precision is reached even for low dose images. Furthermore, advantages of the model- based approach taking into account overlap between neighbouring columns are highlighted. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license.
Keywords: P1 Proceeding; Electron microscopy for materials research (EMAT); Vision lab
Times cited: 1
DOI: 10.1088/1742-6596/902/1/012013
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“Element Specific Atom Counting at the Atomic Scale by Combining High Angle Annular Dark Field Scanning Transmission Electron Microscopy and Energy Dispersive X‐ray Spectroscopy”. De Backer A, Zhang Z, van den Bos KHW, Bladt E, Sánchez‐Iglesias A, Liz‐Marzán LM, Nellist PD, Bals S, Van Aert S, Small methods , 2200875 (2022). http://doi.org/10.1002/smtd.202200875
Abstract: A new methodology is presented to count the number of atoms in multimetallic nanocrystals by combining energy dispersive X-ray spectroscopy (EDX) and high angle annular dark field scanning transmission electron microscopy (HAADF STEM). For this purpose, the existence of a linear relationship between the incoherent HAADF STEM and EDX images is exploited. Next to the number of atoms for each element in the atomic columns, the method also allows quantification of the error in the obtained number of atoms, which is of importance given the noisy nature of the acquired EDX signals. Using experimental images of an Au@Ag core–shell nanorod, it is demonstrated that 3D structural information can be extracted at the atomic scale. Furthermore, simulated data of an Au@Pt core–shell nanorod show the prospect to characterize heterogeneous nanostructures with adjacent atomic numbers.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Impact Factor: 12.4
Times cited: 5
DOI: 10.1002/smtd.202200875
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“Hybrid statistics-simulations based method for atom-counting from ADF STEM images”. De wael A, De Backer A, Jones L, Nellist PD, Van Aert S, Ultramicroscopy 177, 69 (2017). http://doi.org/10.1016/j.ultramic.2017.01.010
Abstract: A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
Times cited: 8
DOI: 10.1016/j.ultramic.2017.01.010
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“Measuring Dynamic Structural Changes of Nanoparticles at the Atomic Scale Using Scanning Transmission Electron Microscopy”. De wael A, De Backer A, Jones L, Varambhia A, Nellist PD, Van Aert S, Physical Review Letters 124, 106105 (2020). http://doi.org/10.1103/PhysRevLett.124.106105
Abstract: We propose a new method to measure atomic scale dynamics of nanoparticles from experimental high-resolution annular dark field scanning transmission electron microscopy images. By using the so-called hidden Markov model, which explicitly models the possibility of structural changes, the number of atoms in each atomic column can be quantified over time. This newly proposed method outperforms the current atom-counting procedure and enables the determination of the probabilities and cross sections for surface diffusion. This method is therefore of great importance for revealing and quantifying the atomic structure when it evolves over time via adatom dynamics, surface diffusion, beam effects, or during in situ experiments.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 8.6
DOI: 10.1103/PhysRevLett.124.106105
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“Modelling ADF STEM images using elliptical Gaussian peaks and its effects on the quantification of structure parameters in the presence of sample tilt”. De wael A, De Backer A, Lobato I, Van Aert S, Ultramicroscopy , 113391 (2021). http://doi.org/10.1016/j.ultramic.2021.113391
Abstract: A small sample tilt away from a main zone axis orientation results in an elongation of the atomic columns in ADF STEM images. An often posed research question is therefore whether the ADF STEM image intensities of tilted nanomaterials should be quantified using a parametric imaging model consisting of elliptical rather than the currently used symmetrical peaks. To this purpose, simulated ADF STEM images corresponding to different amounts of sample tilt are studied using a parametric imaging model that consists of superimposed 2D elliptical Gaussian peaks on the one hand and symmetrical Gaussian peaks on the other hand. We investigate the quantification of structural parameters such as atomic column positions and scattering cross sections using both parametric imaging models. In this manner, we quantitatively study what can be gained from this elliptical model for quantitative ADF STEM, despite the increased parameter space and computational effort. Although a qualitative improvement can be achieved, no significant quantitative improvement in the estimated structure parameters is achieved by the elliptical model as compared to the symmetrical model. The decrease in scattering cross sections with increasing sample tilt is even identical for both types of parametric imaging models. This impedes direct comparison with zone axis image simulations. Nonetheless, we demonstrate how reliable atom-counting can still be achieved in the presence of small sample tilt.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
DOI: 10.1016/j.ultramic.2021.113391
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“Hidden Markov model for atom-counting from sequential ADF STEM images: Methodology, possibilities and limitations”. De wael A, De Backer A, Van Aert S, Ultramicroscopy 219, 113131 (2020). http://doi.org/10.1016/j.ultramic.2020.113131
Abstract: We present a quantitative method which allows us to reliably measure dynamic changes in the atomic structure of monatomic crystalline nanomaterials from a time series of atomic resolution annular dark field scanning transmission electron microscopy images. The approach is based on the so-called hidden Markov model and estimates the number of atoms in each atomic column of the nanomaterial in each frame of the time series. We discuss the origin of the improved performance for time series atom-counting as compared to the current state-of-the-art atom-counting procedures, and show that the so-called transition probabilities that describe the probability for an atomic column to lose or gain one or more atoms from frame to frame are particularly important. Using these transition probabilities, we show that the method can also be used to estimate the probability and cross section related to structural changes. Furthermore, we explore the possibilities for applying the method to time series recorded under variable environmental conditions. The method is shown to be promising for a reliable quantitative analysis of dynamic processes such as surface diffusion, adatom dynamics, beam effects, or in situ experiments.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.2
DOI: 10.1016/j.ultramic.2020.113131
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“Three Approaches for Representing the Statistical Uncertainty on Atom-Counting Results in Quantitative ADF STEM”. De wael A, De Backer A, Yu C-P, Sentürk DG, Lobato I, Faes C, Van Aert S, Microscopy and microanalysis , 1 (2022). http://doi.org/10.1017/S1431927622012284
Abstract: A decade ago, a statistics-based method was introduced to count the number of atoms from annular dark-field scanning transmission electron microscopy (ADF STEM) images. In the past years, this method was successfully applied to nanocrystals of arbitrary shape, size, and composition (and its high accuracy and precision has been demonstrated). However, the counting results obtained from this statistical framework are so far presented without a visualization of the actual uncertainty about this estimate. In this paper, we present three approaches that can be used to represent counting results together with their statistical error, and discuss which approach is most suited for further use based on simulations and an experimental ADF STEM image.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.8
DOI: 10.1017/S1431927622012284
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“Conformation-Dependent Monolayer and Bilayer Structures of an Alkylated TTF Derivative Revealed using STM and Molecular Modeling”. Delfino CL, Hao Y, Martin C, Minoia A, Gopi E, Mali KS, Van der Auweraer M, Geerts YH, Van Aert S, Lazzaroni R, De Feyter S, The Journal of Physical Chemistry C 127, 23023 (2023). http://doi.org/10.1021/acs.jpcc.3c04913
Abstract: In this study, the multi-layer self-assembled molecular network formation of an alkylated tetrathiafulvalene compound is studied at the liquid-solid interface between 1-phenyloctane and graphite. A combined theoretical/experimental approach associating force-field and quantum-chemical calculations with scanning tunnelling microscopy is used to determine the two-dimensional self-assembly beyond the monolayer, but also to further the understanding of the molecular adsorption conformation and its impact on the molecular packing within the assemblies at the monolayer and bilayer level.
Keywords: A1 Journal Article; Electron Microscopy for Materials Science (EMAT) ;
Impact Factor: 3.7
DOI: 10.1021/acs.jpcc.3c04913
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“Estimation of unknown structure parameters from high-resolution (S)TEM images : what are the limits?”.den Dekker AJ, Gonnissen J, de Backer A, Sijbers J, Van Aert S, Ultramicroscopy 134, 34 (2013). http://doi.org/10.1016/j.ultramic.2013.05.017
Abstract: Statistical parameter estimation theory is proposed as a quantitative method to measure unknown structure parameters from electron microscopy images. Images are then purely considered as data planes from which structure parameters have to be determined as accurately and precisely as possible using a parametric statistical model of the observations. For this purpose, an efficient algorithm is proposed for the estimation of atomic column positions and intensities from high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) images. Furthermore, the so-called CramérRao lower bound (CRLB) is reviewed to determine the limits to the precision with which continuous parameters such as atomic column positions and intensities can be estimated. Since this lower bound can only be derived for continuous parameters, alternative measures using the principles of detection theory are introduced for problems concerning the estimation of discrete parameters such as atomic numbers. An experimental case study is presented to show the practical use of these measures for the optimization of the experiment design if the purpose is to decide between the presence of specific atom types using STEM images.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 31
DOI: 10.1016/j.ultramic.2013.05.017
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“Maximum likelihood estimation of structure parameters from high resolution electron microscopy images: part 1: a theoretical framework”. den Dekker AJ, Van Aert S, van den Bos A, van Dyck D, Ultramicroscopy 104, 83 (2005). http://doi.org/10.1016/j.ultramic.2005.03.001
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 70
DOI: 10.1016/j.ultramic.2005.03.001
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“Does a monochromator improve the precision in quantitative HRTEM?”.den Dekker AJ, Van Aert S, van Dyck D, van den Bos A, Geuens P, Ultramicroscopy 89, 275 (2001). http://doi.org/10.1016/S0304-3991(01)00089-4
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 22
DOI: 10.1016/S0304-3991(01)00089-4
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“Introduction to a special issue in honour of W. Owen Saxton, David J. Smith and Dirk Van Dyck on the occasion of their 65th birthdays”. Dunin-Borkowski RE, Lichte H, Tillmann K, Van Aert S, Van Tendeloo G, Ultramicroscopy 134, 1 (2013). http://doi.org/10.1016/j.ultramic.2013.07.013
Keywords: Editorial; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
Times cited: 1
DOI: 10.1016/j.ultramic.2013.07.013
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“Atomic resolution mapping of phonon excitations in STEM-EELS experiments”. Egoavil R, Gauquelin N, Martinez GT, Van Aert S, Van Tendeloo G, Verbeeck J, Ultramicroscopy 147, 1 (2014). http://doi.org/10.1016/j.ultramic.2014.04.011
Abstract: Atomically resolved electron energy-loss spectroscopy experiments are commonplace in modern aberration-corrected transmission electron microscopes. Energy resolution has also been increasing steadily with the continuous improvement of electron monochromators. Electronic excitations however are known to be delocalized due to the long range interaction of the charged accelerated electrons with the electrons in a sample. This has made several scientists question the value of combined high spatial and energy resolution for mapping interband transitions and possibly phonon excitation in crystals. In this paper we demonstrate experimentally that atomic resolution information is indeed available at very low energy losses around 100 meV expressed as a modulation of the broadening of the zero loss peak. Careful data analysis allows us to get a glimpse of what are likely phonon excitations with both an energy loss and gain part. These experiments confirm recent theoretical predictions on the strong localization of phonon excitations as opposed to electronic excitations and show that a combination of atomic resolution and recent developments in increased energy resolution will offer great benefit for mapping phonon modes in real space.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
Times cited: 22
DOI: 10.1016/j.ultramic.2014.04.011
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“Atom column detection”. Fatermans J, de Backer A, den Dekker AJ, Van Aert S Advances in imaging and electron physics
T2 – Advances in imaging and electron physics. page 177 (2021).
Abstract: By combining statistical parameter estimation and model-order selection using a Bayesian framework, the maximum a posteriori (MAP) probability rule is proposed in this chapter as an objective and quantitative method to detect atom columns from high-resolution scanning transmission electron microscopy (HRSTEM) images. The validity and usefulness of this approach is demonstrated to both simulated and experimental annular dark-field (ADF) STEM images, but also to simultaneously acquired annular bright-field (ABF) and ADF STEM image data.
Keywords: H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
DOI: 10.1016/BS.AIEP.2021.01.006
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“Image-quality evaluation and model selection with maximum a posteriori probability”. Fatermans J, de Backer A, den Dekker AJ, Van Aert S Advances in imaging and electron physics
T2 – Advances in imaging and electron physics. page 215 (2021).
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.
Keywords: H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
DOI: 10.1016/BS.AIEP.2021.01.007
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“Single Atom Detection from Low Contrast-to-Noise Ratio Electron Microscopy Images”. Fatermans J, den Dekker A J, Müller-Caspary K, Lobato I, O’Leary C M, Nellist P D, Van Aert S, Physical review letters 121, 056101 (2018). http://doi.org/10.1103/PhysRevLett.121.056101
Abstract: Single atom detection is of key importance to solving a wide range of scientific and technological problems. The strong interaction of electrons with matter makes transmission electron microscopy one of the most promising techniques. In particular, aberration correction using scanning transmission electron microscopy has made a significant step forward toward detecting single atoms. However, to overcome radiation damage, related to the use of high-energy electrons, the incoming electron dose should be kept low enough. This results in images exhibiting a low signal-to-noise ratio and extremely weak contrast, especially for light-element nanomaterials. To overcome this problem, a combination of physics-based model fitting and the use of a model-order selection method is proposed, enabling one to detect single atoms with high reliability.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 8.462
Times cited: 6
DOI: 10.1103/PhysRevLett.121.056101
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“Atom column detection from simultaneously acquired ABF and ADF STEM images”. Fatermans J, den Dekker Aj, Müller-Caspary K, Gauquelin N, Verbeeck J, Van Aert S, Ultramicroscopy 219, 113046 (2020). http://doi.org/10.1016/j.ultramic.2020.113046
Abstract: In electron microscopy, the maximum a posteriori (MAP) probability rule has been introduced as a tool to determine the most probable atomic structure from high-resolution annular dark-field (ADF) scanning transmission electron microscopy (STEM) images exhibiting low contrast-to-noise ratio (CNR). Besides ADF imaging, STEM can also be applied in the annular bright-field (ABF) regime. The ABF STEM mode allows to directly visualize light-element atomic columns in the presence of heavy columns. Typically, light-element nanomaterials are sensitive to the electron beam, limiting the incoming electron dose in order to avoid beam damage and leading to images exhibiting low CNR. Therefore, it is of interest to apply the MAP probability rule not only to ADF STEM images, but to ABF STEM images as well. In this work, the methodology of the MAP rule, which combines statistical parameter estimation theory and model-order selection, is extended to be applied to simultaneously acquired ABF and ADF STEM images. For this, an extension of the commonly used parametric models in STEM is proposed. Hereby, the effect of specimen tilt has been taken into account, since small tilts from the crystal zone axis affect, especially, ABF STEM intensities. Using simulations as well as experimental data, it is shown that the proposed methodology can be successfully used to detect light elements in the presence of heavy elements.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.2
Times cited: 9
DOI: 10.1016/j.ultramic.2020.113046
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