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“High-resolution electron microscopy : from imaging toward measuring”. Van Aert S, den Dekker AJ, van den Bos A, van Dyck D, IEEE transactions on instrumentation and measurement 51, 611 (2002). http://doi.org/10.1109/TIM.2002.802250
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.456
Times cited: 13
DOI: 10.1109/TIM.2002.802250
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“High resolution electron microscopy from imaging towards measuring”. Van Aert S, den Dekker AJ, van den Bos A, Van Dyck D ... IEEE International Instrumentation and Measurement Technology Conference
T2 – Rediscovering measurement in the age of informatics : proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference (IMTC), 2001: vol 3. Ieee, page 2081 (2001).
Keywords: H2 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
DOI: 10.1109/IMTC.2001.929564
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“Physical limits on atomic resolution”. van Dyck D, Van Aert S, den Dekker AJ, Microscopy and microanalysis 10, 153 (2004). http://doi.org/10.1017/S143192760404036X
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 1.891
Times cited: 14
DOI: 10.1017/S143192760404036X
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“Statistical experimental design for quantitative atomic resolution transmission electron microscopy”. Van Aert S, den Dekker AJ, van den Bos A, van Dyck D Academic Press, San Diego, Calif., page 1 (2004).
Keywords: H1 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
Times cited: 13
DOI: 10.1016/S1076-5670(04)30001-7
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“High-resolution electron microscopy and electron tomography: resolution versus precision”. Van Aert S, den Dekker AJ, van Dyck D, van den Bos A, Journal of structural biology 138, 21 (2002). http://doi.org/10.1016/S1047-8477(02)00016-3
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.767
Times cited: 33
DOI: 10.1016/S1047-8477(02)00016-3
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“Is atomic resolution transmission electron microscopy able to resolve and refine amorphous structures?”.van Dyck D, Van Aert S, den Dekker AJ, van den Bos A, Ultramicroscopy 98, 27 (2003). http://doi.org/10.1016/S0304-3991(03)00023-8
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 26
DOI: 10.1016/S0304-3991(03)00023-8
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“Optimal experimental design of STEM measurement of atom column positions”. Van Aert S, den Dekker AJ, van Dyck D, van den Bos A, Ultramicroscopy 90, 273 (2002). http://doi.org/10.1016/S0304-3991(01)00152-8
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 35
DOI: 10.1016/S0304-3991(01)00152-8
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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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“Maximum likelihood estimation of structure parameters from high resolution electron microscopy images : part 2 : a practical example”. Van Aert S, den Dekker AJ, van den Bos A, van Dyck D, Chen JH, Ultramicroscopy 104, 107 (2005). http://doi.org/10.1016/j.ultramic.2005.03.002
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 37
DOI: 10.1016/j.ultramic.2005.03.002
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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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“How to optimize the experimental design of quantitative atomic resolution TEM experiments?”.Van Aert S, den Dekker AJ, van Dyck D, Micron 35, 425 (2004). http://doi.org/10.1016/j.micron.2004.01.007
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 1.98
Times cited: 14
DOI: 10.1016/j.micron.2004.01.007
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“The benefits of statistical parameter estimation theory for quantitative interpretation of electron microscopy data”. Van Aert S, Bals S, Chang LY, den Dekker AJ, Kirkland AI, Van Dyck D, Van Tendeloo G Springer, Berlin, page 97 (2008).
Keywords: H1 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
DOI: 10.1007/978-3-540-85156-1_49
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“The notion of resolution”. Van Aert S, den Dekker AJ, van Dyck D, van den Bos A Springer, Berlin, page 1228 (2008).
Keywords: H3 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
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“The notion of resolution”. Van Aert S, den Dekker AJ, van Dyck D, van den Bos A Springer, Berlin, page 1228 (2007).
Keywords: H3 Book chapter; Electron microscopy for materials research (EMAT); Vision lab
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“Present state of the composition evaluation of ternary semiconductor nanostructures by lattice fringe analysis”. Rosenauer A, Gerthsen D, Van Aert S, van Dyck D, den Dekker AJ, Institute of physics conference series , 19 (2003)
Abstract: Semiconductor heterostructures are used for the fabrication of optoelectronic devices. Performance of such devices is governed by their chemical morphology. The composition distribution of quantum wells and dots is influenced by kinetic growth processes which are not understood completely at present. To obtain more information about these effects, methods for composition determination with a spatial resolution at a near atomic scale are necessary. In this paper we focus on the present state of the composition evaluation by the lattice fringe analysis (CELFA) technique and explain the basic ideas, optimum imaging conditions, precision and accuracy.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
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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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“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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“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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“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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“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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“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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“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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“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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“Detecting and locating light atoms from high-resolution STEM images: The quest for a single optimal design”. Gonnissen J, De Backer A, den Dekker AJ, Sijbers J, Van Aert S, Ultramicroscopy 170, 128 (2016). http://doi.org/10.1016/j.ultramic.2016.07.014
Abstract: In the present paper, the optimal detector design is investigated for both detecting and locating light atoms from high resolution scanning transmission electron microscopy (HR STEM) images. The principles of detection theory are used to quantify the probability of error for the detection of light atoms from HR STEM images. To determine the optimal experiment design for locating light atoms, use is made of the so-called Cramer-Rao Lower Bound (CRLB). It is investigated if a single optimal design can be found for both the detection and location problem of light atoms. Furthermore, the incoming electron dose is optimised for both research goals and it is shown that picometre range precision is feasible for the estimation of the atom positions when using an appropriate incoming electron dose under the optimal detector settings to detect light atoms.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 6
DOI: 10.1016/j.ultramic.2016.07.014
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“Atom-counting in High Resolution Electron Microscopy: TEM or STEM –, that's the question”. Gonnissen J, De Backer A, den Dekker AJ, Sijbers J, Van Aert S, Ultramicroscopy 174, 112 (2016). http://doi.org/10.1016/j.ultramic.2016.10.011
Abstract: In this work, a recently developed quantitative approach based on the principles of detection theory is used in order to determine the possibilities and limitations of High Resolution Scanning Transmission Electron Microscopy (HR STEM) and HR TEM for atom-counting. So far, HR STEM has been shown to be an appropriate imaging mode to count the number of atoms in a projected atomic column. Recently, it has been demonstrated that HR TEM, when using negative spherical aberration imaging, is suitable for atom-counting as well. The capabilities of both imaging techniques are investigated and compared using the probability of error as a criterion. It is shown that for the same incoming electron dose, HR STEM outperforms HR TEM under common practice standards, i.e. when the decision is based on the probability function of the peak intensities in HR TEM and of the scattering cross-sections in HR STEM. If the atom-counting decision is based on the joint probability function of the image pixel values, the dependence of all image pixel intensities as a function of thickness should be known accurately. Under this assumption, the probability of error may decrease significantly for atom-counting in HR TEM and may, in theory, become lower as compared to HR STEM under the predicted optimal experimental settings. However, the commonly used standard for atom-counting in HR STEM leads to a high performance and has been shown to work in practice.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 2
DOI: 10.1016/j.ultramic.2016.10.011
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“The maximum a posteriori probability rule for atom column detection from HAADF STEM images”. Fatermans J, Van Aert S, den Dekker AJ, Ultramicroscopy 201, 81 (2019). http://doi.org/10.1016/j.ultramic.2019.02.003
Abstract: Recently, the maximum a posteriori (MAP) probability rule has been proposed as an objective and quantitative method to detect atom columns and even single atoms from high-resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images. The method combines statistical parameter estimation and model-order selection using a Bayesian framework and has been shown to be especially useful for the analysis of the structure of beam-sensitive nanomaterials. In order to avoid beam damage, images of such materials are usually acquired using a limited incoming electron dose resulting in a low contrast-to-noise ratio (CNR) which makes visual inspection unreliable. This creates a need for an objective and quantitative approach. The present paper describes the methodology of the MAP probability rule, gives its step-by-step derivation and discusses its algorithmic implementation for atom column detection. In addition, simulation results are presented showing that the performance of the MAP probability rule to detect the correct number of atomic columns from HAADF STEM images is superior to that of other model-order selection criteria, including the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Moreover, the MAP probability rule is used as a tool to evaluate the relation between STEM image quality measures and atom detectability resulting in the introduction of the so-called integrated CNR (ICNR) as a new image quality measure that better correlates with atom detectability than conventional measures such as signal-to-noise ratio (SNR) and CNR.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 1
DOI: 10.1016/j.ultramic.2019.02.003
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“Optimal experimental design for the detection of light atoms from high-resolution scanning transmission electron microscopy images”. Gonnissen J, de Backer A, den Dekker AJ, Martinez GT, Rosenauer A, Sijbers J, Van Aert S, Applied physics letters 105, 063116 (2014). http://doi.org/10.1063/1.4892884
Abstract: We report an innovative method to explore the optimal experimental settings to detect light atoms from scanning transmission electron microscopy (STEM) images. Since light elements play a key role in many technologically important materials, such as lithium-battery devices or hydrogen storage applications, much effort has been made to optimize the STEM technique in order to detect light elements. Therefore, classical performance criteria, such as contrast or signal-to-noise ratio, are often discussed hereby aiming at improvements of the direct visual interpretability. However, when images are interpreted quantitatively, one needs an alternative criterion, which we derive based on statistical detection theory. Using realistic simulations of technologically important materials, we demonstrate the benefits of the proposed method and compare the results with existing approaches.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 3.411
Times cited: 12
DOI: 10.1063/1.4892884
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“Advanced electron crystallography through model-based imaging”. Van Aert S, De Backer A, Martinez GT, den Dekker AJ, Van Dyck D, Bals S, Van Tendeloo G, IUCrJ 3, 71 (2016). http://doi.org/10.1107/S2052252515019727
Abstract: The increasing need for precise determination of the atomic arrangement of non-periodic structures in materials design and the control of nanostructures explains the growing interest in quantitative transmission electron microscopy. The aim is to extract precise and accurate numbers for unknown structure parameters including atomic positions, chemical concentrations and atomic numbers. For this purpose, statistical parameter estimation theory has been shown to provide reliable results. In this theory, observations are considered purely as data planes, from which structure parameters have to be determined using a parametric model describing the images. As such, the positions of atom columns can be measured with a precision of the order of a few picometres, even though the resolution of the electron microscope is still one or two orders of magnitude larger. Moreover, small differences in average atomic number, which cannot be distinguished visually, can be quantified using high-angle annular dark-field scanning transmission electron microscopy images. In addition, this theory allows one to measure compositional changes at interfaces, to count atoms with single-atom sensitivity, and to reconstruct atomic structures in three dimensions. This feature article brings the reader up to date, summarizing the underlying theory and highlighting some of the recent applications of quantitative model-based transmisson electron microscopy.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab; Engineering Management (ENM)
Impact Factor: 5.793
Times cited: 30
DOI: 10.1107/S2052252515019727
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“Resolution of coherent and incoherent imaging systems reconsidered: classical criteria and a statistical alternative”. Van Aert S, van Dyck D, den Dekker AJ, Optics express 14, 3830 (2006). http://doi.org/10.1364/OE.14.003830
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 3.307
Times cited: 45
DOI: 10.1364/OE.14.003830
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