“Atom counting from a combination of two ADF STEM images”. Şentürk DG, Yu CP, De Backer A, Van Aert S, Ultramicroscopy 255, 113859 (2024). http://doi.org/10.1016/j.ultramic.2023.113859
Abstract: To understand the structure–property relationship of nanostructures, reliably quantifying parameters, such as the number of atoms along the projection direction, is important. Advanced statistical methodologies have made it possible to count the number of atoms for monotype crystalline nanoparticles from a single ADF STEM image. Recent developments enable one to simultaneously acquire multiple ADF STEM images. Here, we present an extended statistics-based method for atom counting from a combination of multiple statistically independent ADF STEM images reconstructed from non-overlapping annular detector collection regions which improves the accuracy and allows one to retrieve precise atom-counts, especially for images acquired with low electron doses and multiple element structures.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.2
DOI: 10.1016/j.ultramic.2023.113859
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“Control of Knock-On Damage for 3D Atomic Scale Quantification of Nanostructures: Making Every Electron Count in Scanning Transmission Electron Microscopy”. Van Aert S, De Backer A, Jones L, Martinez GT, Béché, A, Nellist PD, Physical review letters 122, 066101 (2019). http://doi.org/10.1103/PhysRevLett.122.066101
Abstract: Understanding nanostructures down to the atomic level is the key to optimizing the design of advancedmaterials with revolutionary novel properties. This requires characterization methods capable of quantifying the three-dimensional (3D) atomic structure with the highest possible precision. A successful approach to reach this goal is to count the number of atoms in each atomic column from 2D annular dark field scanning transmission electron microscopy images. To count atoms with single atom sensitivity, a minimum electron dose has been shown to be necessary, while on the other hand beam damage, induced by the high energy electrons, puts a limit on the tolerable dose. An important challenge is therefore to develop experimental strategies to optimize the electron dose by balancing atom-counting fidelity vs the risk of knock-on damage. To achieve this goal, a statistical framework combined with physics-based modeling of the dose-dependent processes is here proposed and experimentally verified. This model enables an investigator to theoretically predict, in advance of an experimental measurement, the optimal electron dose resulting in an unambiguous quantification of nanostructures in their native state with the highest attainable precision.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 8.462
Times cited: 3
DOI: 10.1103/PhysRevLett.122.066101
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“Particle deposition in airways of chronic respiratory patients exposed to an urban aerosol”. Horemans B, Van Holsbeke C, Vos W, Darchuk L, Novakovic V, Fontan AC, de Backer J, van Grieken R, de Backer W, De Wael K, Environmental science and technology 46, 12162 (2012). http://doi.org/10.1021/es302755s
Abstract: Urban atmospheres in modern cities carry characteristic mixtures of particulate pollution which are potentially aggravating for chronic respiratory patients (CRP). Although air quality surveys can be detailed, the obtained information is not always useful to evaluate human health effects. This paper presents a novel approach to estimate particle deposition rates in airways of CRP, based on real air pollution data. By combining computational fluid dynamics with physical-chemical characteristics of particulate pollution, deposition rates are estimated for particles of different toxicological relevance, that is, minerals, iron oxides, sea salts, ammonium salts, and carbonaceous particles. Also, it enables some qualitative evaluation of the spatial, temporal, and patient specific effects on the particle dose upon exposure to the urban atmosphere. Results show how heavy traffic conditions increases the deposition of anthropogenic particles in the trachea and lungs of respiratory patients (here, +0.28 and +1.5 μg·h1, respectively). In addition, local and synoptic meteorological conditions were found to have a strong effect on the overall dose. However, the pathology and age of the patient was found to be more crucial, with highest deposition rates for toxic particles in adults with a mild anomaly, followed by mild asthmatic children and adults with severe respiratory dysfunctions (7, 5, and 3 μg·h1, respectively).
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Laboratory Experimental Medicine and Pediatrics (LEMP)
Impact Factor: 6.198
Times cited: 5
DOI: 10.1021/es302755s
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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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“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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“Procedure to count atoms with trustworthy single-atom sensitivity”. Van Aert S, de Backer A, Martinez GT, Goris B, Bals S, Van Tendeloo G, Rosenauer A, Physical review : B : condensed matter and materials physics 87, 064107 (2013). http://doi.org/10.1103/PhysRevB.87.064107
Abstract: We report a method to reliably count the number of atoms from high-angle annular dark field scanning transmission electron microscopy images. A model-based analysis of the experimental images is used to measure scattering cross sections at the atomic level. The high sensitivity of these measurements in combination with a thorough statistical analysis enables us to count atoms with single-atom sensitivity. The validity of the results is confirmed by means of detailed image simulations. We will show that the method can be applied to nanocrystals of arbitrary shape, size, and atom type without the need for a priori knowledge about the atomic structure.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 3.836
Times cited: 106
DOI: 10.1103/PhysRevB.87.064107
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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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“Locating and controlling the Zn content in In(Zn)P quantum dots”. Kirkwood N, De Backer A, Altantzis T, Winckelmans N, Longo A, Antolinez FV, Rabouw FT, De Trizio L, Geuchies JJ, Mulder JT, Renaud N, Bals S, Manna L, Houtepen AJ, Chemistry of materials 32, 557 (2019). http://doi.org/10.1021/acs.chemmater.9b04407
Abstract: Zinc is routinely employed in the synthesis of InP quantum dots (QDs) to improve the photoluminescence efficiency and carrier mobility of the resulting In(Zn)P alloy nanostructures. The exact location of Zn in the final structures and the mechanism by which it enhances the optoelectronic properties of the QDs is debated. We use synchrotron X-ray absorbance spectroscopy to show that the majority of Zn in In(Zn)P QDs is located at their surface as Zn-carboxylates. However, a small amount of Zn is present inside the bulk of the QDs with the consequent contraction of their lattice, as confirmed by combining high resolution high-angle annular dark-field imaging scanning transmission electron microscopy (HAADF-STEM) with statistical parameter estimation theory. We further demonstrate that the Zn content and its incorporation into the QDs can be tuned by the ligation of commonly employed Zn carboxylate precursors: the use of highly reactive Zn-acetate leads to the formation of undesired Zn3P2 and the final nanostructures being characterized by broad optical features, whereas Zn-carboxylates with longer carbon chains lead to InP crystals with much lower zinc content and narrow optical features. These results can explain the differences between structural and optical properties of In(Zn)P samples reported across the literature, and provide a rational method to tune the amount of Zn in InP nanocrystals and to drive the incorporation of Zn either as surface Zn-carboxylate, as a substitutional dopant inside the InP crystal lattice, or even predominantly as Zn3P2.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 9.466
Times cited: 39
DOI: 10.1021/acs.chemmater.9b04407
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