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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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“A decade of atom-counting in STEM: From the first results toward reliable 3D atomic models from a single projection”. De Backer A, Bals S, Van Aert S, Ultramicroscopy , 113702 (2023). http://doi.org/10.1016/j.ultramic.2023.113702
Abstract: Quantitative structure determination is needed in order to study and understand nanomaterials at the atomic scale. Materials characterisation resulting in precise structural information is a crucial point to understand the structure–property relation of materials. Counting the number of atoms and retrieving the 3D atomic structure of nanoparticles plays an important role here. In this paper, an overview will be given of the atom-counting methodology and its applications over the past decade. The procedure to count the number of atoms will be discussed in detail and it will be shown how the performance of the method can be further improved. Furthermore, advances toward mixed element nanostructures, 3D atomic modelling based on the atom-counting results, and quantifying the nanoparticle dynamics will be highlighted.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.2
Times cited: 3
DOI: 10.1016/j.ultramic.2023.113702
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“In Situ Plasma Studies Using a Direct Current Microplasma in a Scanning Electron Microscope”. Grünewald L, Chezganov D, De Meyer R, Orekhov A, Van Aert S, Bogaerts A, Bals S, Verbeeck J, Advanced Materials Technologies (2024). http://doi.org/10.1002/admt.202301632
Abstract: Microplasmas can be used for a wide range of technological applications and to improve the understanding of fundamental physics. Scanning electron microscopy, on the other hand, provides insights into the sample morphology and chemistry of materials from the mm‐ down to the nm‐scale. Combining both would provide direct insight into plasma‐sample interactions in real‐time and at high spatial resolution. Up till now, very few attempts in this direction have been made, and significant challenges remain. This work presents a stable direct current glow discharge microplasma setup built inside a scanning electron microscope. The experimental setup is capable of real‐time in situ imaging of the sample evolution during plasma operation and it demonstrates localized sputtering and sample oxidation. Further, the experimental parameters such as varying gas mixtures, electrode polarity, and field strength are explored and experimental<italic>V</italic>–<italic>I</italic>curves under various conditions are provided. These results demonstrate the capabilities of this setup in potential investigations of plasma physics, plasma‐surface interactions, and materials science and its practical applications. The presented setup shows the potential to have several technological applications, for example, to locally modify the sample surface (e.g., local oxidation and ion implantation for nanotechnology applications) on the µm‐scale.
Keywords: A1 Journal Article; Electron Microscopy for Materials Science (EMAT) ;
Impact Factor: 6.8
DOI: 10.1002/admt.202301632
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Zhang Z, Lobato I, Brown H, Jannis D, Verbeeck J, Van Aert S, Nellist P (2023) Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions
Abstract: Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1]. The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions. We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration. Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3] Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference. Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script. Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.
Keywords: Dataset; Electron microscopy for materials research (EMAT)
DOI: 10.5281/ZENODO.8360240
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Grü,newald L, Chezganov D, De Meyer R, Orekhov A, Van Aert S, Bogaerts A, Bals S, Verbeeck J (2023) Supplementary Information for “In-situ Plasma Studies using a Direct Current Microplasma in a Scanning Electron Microscope”
Abstract: Supplementary information for the article “In-situ Plasma Studies using a Direct Current Microplasma in a Scanning Electron Microscope” containing the videos of in-situ SEM imaging (mp4 files), raw data/images, and Jupyter notebooks (ipynb files) for data treatment and plots. Link to the preprint: https://doi.org/10.48550/arXiv.2308.15123 Explanation of the data files can be found in the Information.pdf file. The Videos folder contains the in-situ SEM image series mentioned in the paper. If there are any questions/bugs, feel free to contact me at lukas.grunewaldatuantwerpen.be
Keywords: Dataset; Engineering sciences. Technology; Electron microscopy for materials research (EMAT); Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT)
DOI: 10.5281/ZENODO.8042030
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Cioni M, Delle Piane M, Polino D, Rapetti D, Crippa M, Arslan Irmak E, Pavan GM, Van Aert S, Bals S (2024) Data for Sampling Real‐Time Atomic Dynamics in Metal Nanoparticles by Combining Experiments, Simulations, and Machine Learning
Abstract: Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic‐resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state‐of‐the‐art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark‐field scanning transmission electron microscopy enables the acquisition of ten high‐resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allows resolving the real‐time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions.
Keywords: Dataset; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
DOI: 10.5281/ZENODO.10997963
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“Sampling real-time atomic dynamics in metal nanoparticles by combining experiments, simulations, and machine learning”. Cioni M, Delle Piane M, Polino D, Rapetti D, Crippa M, Arslan Irmak E, Van Aert S, Bals S, Pavan GM, Advanced Science , 1 (2024). http://doi.org/10.1002/ADVS.202307261
Abstract: Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic-resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state-of-the-art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark-field scanning transmission electron microscopy enables the acquisition of ten high-resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allow resolving the real-time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions. Experimental and computational techniques are bridged to unveil atomic dynamics in gold nanoparticles (NPs), using annular dark-field scanning transmission electron microscopy and molecular dynamics simulations informed by machine learning. The approach provides unprecedented insights into the real-time structural behaviors of NPs, merging state-of-the-art techniques to accurately characterize their dynamics under realistic conditions. image
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Impact Factor: 15.1
DOI: 10.1002/ADVS.202307261
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“Single-layered imine-linked porphyrin-based two-dimensional covalent organic frameworks targeting CO₂, reduction”. Arisnabarreta N, Hao Y, Jin E, Salame A, Muellen K, Robert M, Lazzaroni R, Van Aert S, Mali KS, De Feyter S, Advanced energy materials (2024). http://doi.org/10.1002/AENM.202304371
Abstract: The reduction of carbon dioxide (CO2) using porphyrin-containing 2D covalent organic frameworks (2D-COFs) catalysts is widely explored nowadays. While these framework materials are normally fabricated as powders followed by their uncontrolled surface heterogenization or directly grown as thin films (thickness >200 nm), very little is known about the performance of substrate-supported single-layered (approximate to 0.5 nm thickness) 2D-COFs films (s2D-COFs) due to its highly challenging synthesis and characterization protocols. In this work, a fast and straightforward fabrication method of porphyrin-containing s2D-COFs is demonstrated, which allows their extensive high-resolution visualization via scanning tunneling microscopy (STM) in liquid conditions with the support of STM simulations. The as-prepared single-layered film is then employed as a cathode for the electrochemical reduction of CO2. Fe porphyrin-containing s2D-COF@graphite used as a single-layered heterogeneous catalyst provided moderate-to-high carbon monoxide selectivity (82%) and partial CO current density (5.1 mA cm(-2)). This work establishes the value of using single-layered films as heterogene ous catalysts and demonstrates the possibility of achieving high performance in CO2 reduction even with extremely low catalyst loadings.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Impact Factor: 27.8
DOI: 10.1002/AENM.202304371
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