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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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“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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“Three-dimensional atomic structure of supported Au nanoparticles at high temperature”. Liu P, Arslan Irmak E, De Backer A, De wael A, Lobato I, Béché, A, Van Aert S, Bals S, Nanoscale 13 (2021). http://doi.org/10.1039/D0NR08664A
Abstract: Au nanoparticles (NPs) deposited on CeO2 are extensively used as thermal catalysts since the morphology of the NPs is expected to be stable at elevated temperatures. Although it is well known that the activity of Au NPs depends on their size and surface structure, their three-dimensional (3D) structure at the atomic scale has not been completely characterized as a function of temperature. In this paper, we overcome the limitations of conventional electron tomography by combining atom counting applied to aberration-corrected scanning transmission electron microscopy images and molecular dynamics relaxation. In this manner, we are able to perform an atomic resolution 3D investigation of supported Au NPs. Our results enable us to characterize the 3D equilibrium structure of single NPs as a function of temperature. Moreover, the dynamic 3D structural evolution of the NPs at high temperatures, including surface layer jumping and crystalline transformations, has been studied.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Impact Factor: 7.367
Times cited: 13
DOI: 10.1039/D0NR08664A
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De wael A (2021) Model-based quantitative scanning transmission electron microscopy for measuring dynamic structural changes at the atomic scale. xiv, 146 p
Abstract: Nanomaterialen kunnen uiterst interessante eigenschappen vertonen voor een verscheidenheid aan veelbelovende toepassingen, gaande van zonnecrème tot batterijen voor elektrische auto’s. Een nanometer is een miljard keer kleiner dan een meter. Op deze schaal kunnen de materiaaleigenschappen volledig verschillen van bulkmaterialen op grotere schaal. Bovendien hangen de eigenschappen van nanomaterialen sterk af van hun exacte grootte en vorm. Kleine verschillen in de posities van de atomen, in de grootte-orde van een picometer (nog eens duizend maal kleiner dan een nanometer), kunnen de fysische eigenschappen al drastisch beïnvloeden. Daarom is een betrouwbare kwantificering van de atomaire structuur van kritisch belang om de evolutie naar materiaalontwerp mogelijk te maken en inzicht te verwerven in de relatie tussen de fysische eigenschappen en de structuur van nanomaterialen. Daarnaast kan de atomaire structuur van nanomaterialen ook veranderen in de loop van de tijd ten gevolge van verschillende fysische processen. Het onderzoek dat in deze thesis gepresenteerd wordt, maakt het mogelijk om de dynamische structuurveranderingen van nanomaterialen betrouwbaar te kwantificeren op atomaire schaal door gebruik te maken van raster transmissie elektronenmicroscopie (STEM). Ik heb dit gerealiseerd door methodes te ontwikkelen waarmee ik het aantal atomen “achter elkaar” kan tellen in elke atoomkolom van een nanomateriaal, en dit op basis van beelden opgenomen met een elektronenmicroscoop. Een belangrijk verschil met telmethodes voor de analyse van een enkel beeld is het schatten van de kans dat een atoomkolom atomen zal verliezen of bijkrijgen van het ene naar het andere beeld in de tijdreeks. Deze kwantitatieve methode kan het ontrafelen van de tijdsafhankelijke structuur-eigenschappen relatie van een nanomateriaal mogelijk maken, wat uiteindelijk kan leiden tot efficiënter design en productie van nanomaterialen voor innovatieve toepassingen.
Keywords: Doctoral thesis; Electron microscopy for materials research (EMAT)
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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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“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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“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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“Quantitative annular dark field scanning transmission electron microscopy for nanoparticle atom-counting: What are the limits?”.De Backer A, De Wael A, Gonnissen J, Martinez GT, Béché, A, MacArthur KE, Jones L, Nellist PD, Van Aert S, Journal of physics : conference series 644Electron Microscopy and Analysis Group Conference (EMAG), JUN 02-JUL 02, 2015, Manchester, ENGLAND, 012034 (2015). http://doi.org/10.1088/1742-6596/644/1/012034
Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atom-counting diagnosed by combining a thorough statistical method and detailed image simulations.
Keywords: P1 Proceeding; Electron microscopy for materials research (EMAT)
DOI: 10.1088/1742-6596/644/1/012034
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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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“Quantitative annular dark field scanning transmission electron microscopy for nanoparticle atom-counting : what are the limits?”.de Backer A, De wael A, Gonnissen J, Martinez GT, Béché, A, MacArthur KE, Jones L, Nellist PD, Van Aert S, Journal of physics : conference series 644, 012034 (2015). http://doi.org/10.1088/1742-6596/644/012034
Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atomcounting diagnosed by combining a thorough statistical method and detailed image simulations.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
DOI: 10.1088/1742-6596/644/012034
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