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Cautaerts, N.; Lamm, S.; Stergar, E.; Pakarinen, J.; Yang, Y.; Hofer, C.; Schnitzer, R.; Felfer, P.; Verwerft, M.; Delville, R.; Schryvers, D. |
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Atom probe tomography data collection from DIN 1.4970 (15-15Ti) austenitic stainless steel irradiated with Fe ions |
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2020 |
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Dataset; Electron microscopy for materials research (EMAT) |
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This dataset comprises a large collection of atom probe tomography datasets collected from DIN 1.4970 alloy that was irradiated with Fe ions at different conditions. The DIN 1.4970 alloy is an austenitic stainless steel with 15 wt% Cr, 15 wt% Ni, a small addition of Ti. The full composition and characterization of our material can be found published elsewhere [1,2]. Some of our material was subjected to ageing heat treatments at different temperatures for different times. Small samples of our original material and aged material was irradiated at the Michigan Ion Beam Laboratory in 2017 with 4.5 MeV Fe ions up to 40 dpa at an average dose rate of 2×10−4 dpa/s. This was done at three different temperatures: 300, 450, and 600 ºC. Atom probe samples were made of the irradiated layers (approximately 1.5 micron deep) with focused ion beam and mounted on Microtip coupons. APT measurements took place on three CAMECA LEAP-HR systems located at CAES in Idaho Falls, USA (files beginning with R33), at Montanuniversität Leoben in Leoben, Austria (R21) and at Friedrich–Alexander University in Erlangen, Germany (R56). |
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UA @ admin @ c:irua:169127 |
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6454 |
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Skorikov, A.; Heyvaert, W.; Albrecht, W.; Pelt, D.M.; Bals, S. |
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EMAT Simulated 3D Nanoparticle Structures Dataset |
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2021 |
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Dataset; Electron microscopy for materials research (EMAT) |
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This dataset contains 1000 simulated nanoparticle-like 3D structures and noisy EDX-like elemental maps based on them. These data are intended to be used for quantitative analysis of data processing methods in (EDX) tomography of nanoparticles and training the data-driven approaches for these tasks. The dataset is structured as follows: voxel_data/clean 3D voxel grid representation of the simulated nanoparticles. Voxel intensities are adjusted so that the total intensity equals 103. All 3D structures have unique identifiers in 0..999 range. The data derived from a 3D structure preserves this unique identifier. sinograms/clean Tilt series of projection images obtained from the corresponding 3D structures over an angular range of -75..75 degrees with a tilt step of 10 degrees to simulate a typical tilt series used in EDX tomography. Total intensity in each projection image equals 103. sinograms/noisy Tilt series of projection images corrupted with Poisson noise and an additional spatially uniform background noise. projections/clean Projection images extracted from the clean tilt series at 0 degrees tilt angle. projections/noisy Projection images extracted from the noisy tilt series at 0 degrees tilt angle. images/clean Visualizations of the clean projections as PNG images with the intensity range adjusted to 0..255 images/noisy Visualizations of the noisy projections as PNG images with the intensity range adjusted to 0..255 |
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UA @ admin @ c:irua:180615 |
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6838 |
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Guzzinati, G.; Ghielens, W.; Mahr, C.; Béché, A.; Rosenauer, A.; Calders, T.; Verbeeck, J. |
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Electron Bessel beam diffraction patterns, line scan of Si/SiGe multilayer |
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2019 |
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Dataset; ADReM Data Lab (ADReM); Electron microscopy for materials research (EMAT) |
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UA @ admin @ c:irua:169114 |
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6865 |
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Guzzinati, G.; Das, P.P.; Zompra, A., A.; Nicopoulos, S.; Verbeeck, J. |
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Electron energy loss spectra of several organic compounds |
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2020 |
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Dataset; Electron microscopy for materials research (EMAT) |
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We placed crystals of different compounds to explore the possibility of fingerprinting them through EELS. Here are representative datasets of 7 different compounds: b-cyclodextrin hexacarboxy cyclohexane tannin TH-15 peptide TH-27 peptide two different forms of piroxicam The datasets were collected at EMAT, using a monochromated FEI Titan3 TEM, within the scope of an EUSMI request. More information as well as analysis methodologies adopted for the data are detailed in the paper: Das et al. “Reliable Characterization of Organic & Pharmaceutical Compounds with High Resolution Monochromated EEL Spectroscopy”, Polymers 2020, 12(7), 1434. |
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UA @ admin @ c:irua:180654 |
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6866 |
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Samaeeaghmiyoni, V.; Cordier, P.; Demouchy, S.; Bollinger, C.; Gasc, J.; Mussi, A.; Schryvers, D.; Idrissi, H. |
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Research data supporting for Stress-induced amorphization triggers deformation in the lithospheric mantle |
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2020 |
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UA @ admin @ c:irua:180668 |
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6881 |
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Guzzinati, G.; Béché, A.; McGrouther, D.; Verbeeck, J. |
Title |
Rotation of electron beams in the presence of localised, longitudinal magnetic fields |
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2019 |
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Electron Bessel beams have been generated by inserting an annular aperture in the illumination system of a TEM. These beams have passed through a localised magnetic field. As a result a low amount of image rotation (which is expected to be proportional to the longitudinal component of the magnetic field) is observed in the far field. A measure of this rotation should give access to the magneti field. The two datasets have been acquired in a FEI Titan3 microscope, operated at 300kV. The file focalseries.tif contains a series of images acquired varying the magnetic field through the objective lens. The file lineprofile.ser contains a series of images acquired by scanning the beam over a sample with several magnetised nanopillars. For reference, check the associated publication. |
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UA @ admin @ c:irua:169135 |
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6883 |
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Jannis, D.; Müller-Caspary, K.; Béché, A.; Oelsner, A.; Verbeeck, J. |
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Spectrocopic coincidence experiment in transmission electron microscopy |
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2019 |
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This dataset contains individual EEL and EDX events where for every event (electron or X-ray), their energy and time of arrival is stored. The experiment was performed in a transmission electron microscope (Tecnai Osiris) at 200 keV. The material investigated is an Al-Mg-Si-Cu alloy. The 'full_dataset.mat' contains the full dataset and the 'subset.mat' has the first five frames of the full dataset. The attached 'EELS-EDX.ipynb' is a jupyter notebook file. This file describes the data processing in order to observe the temporal correlation between the electrons and X-rays. |
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UA @ admin @ c:irua:169112 |
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6888 |
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Idrissi, H.; Samaee, V.; Lumbeeck, G.; van der Werf, T.; Pardoen, T.; Schryvers, D.; Cordier, P. |
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Supporting data for “In situ Quantitative Tensile Tests on Antigorite in a Transmission Electron Microscope” |
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2019 |
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The determination of the mechanical properties of serpentinites is essential towards the understanding of the mechanics of faulting and subduction. Here, we present the first in situ tensile tests on antigorite in a transmission electron microscope. A push-to-pull deformation device is used to perform quantitative tensile tests, during which force and displacement are measured, while the microstructure is imaged with the microscope. The experiments have been performed at room temperature on beams prepared by focused ion beam. The specimens are not single crystals despite their small sizes. Orientation mapping indicated that some grains were well-oriented for plastic slip. However, no dislocation activity has been observed even though engineering tensile stress went up to 700 MPa. We show also that antigorite does not exhibit an pure elastic-brittle behaviour since, despite the presence of defects, the specimens underwent plastic deformation and did not fail within the elastic regime. Instead, we observe that strain localizes at grain boundaries. All observations concur to show that under our experimental conditions, grain boundary sliding is the dominant deformation mechanism. This study sheds a new light on the mechanical properties of antigorite and calls for further studies on the structure and properties of grain boundaries in antigorite and more generally in phyllosilicates. |
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UA @ admin @ c:irua:169107 |
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6891 |
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Nakazato, R.; Matsumoto, K.; Yamaguchi, N.; Cavallo, M.; Crocella, V.; Bonino, F.; Quintelier, M.; Hadermann, J.; Rosero-Navarro, N.C.; Miura, A.; Tadanaga, K. |
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CO2 Electrochemical Reduction with Zn-Al Layered Double Hydroxide-Loaded Gas-Diffusion Electrode (Supporting Information) |
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2023 |
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Dataset; Electron microscopy for materials research (EMAT) |
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Carbon dioxide electrochemical reduction (CO2ER) has attracted considerable attention as a technology to recycle CO2 into raw materials for chemicals using renewable energies. We recently found that Zn-Al layered double hydroxides (Zn-Al LDH) have the CO-forming CO2ER activity. However, the activity was only evaluated by using the liquid-phase CO2ER. In this study, Ni-Al and Ni-Fe LDHs as well as Zn-Al LDH were synthesized using a facile coprecipitation process and the gas-phase CO2ER with the LDH-loaded gas-diffusion electrode (GDE) was examined. The products were characterized by XRD, STEM-EDX, BF-TEM and ATR-IR spectroscopy. In the ATR-IR results, the interaction of CO2 with Zn-Al LDH showed a different carbonates evolution with respect to other LDHs, suggesting a different electrocatalytic activity. The LDH-loaded GDE was prepared by simple drop-casting of a catalyst ink onto carbon paper. For gas-phase CO2ER, only Zn-Al LDH exhibited the CO2ER activity for carbon monoxide (CO) formation. By using different potassium salt electrolytes affording neutral to strongly basic conditions, such as KCl, KHCO3 and KOH, the gas-phase CO2ER with Zn-Al LDH-loaded GDE showed 1.3 to 2.1 times higher partial current density for CO formation than the liquid-phase CO2ER. |
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UA @ admin @ c:irua:200933 |
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9010 |
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Annys, A.; Jannis, D.; Verbeeck, J. |
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Core-loss EELS dataset and neural networks for element identification |
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2023 |
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Dataset; Electron microscopy for materials research (EMAT) |
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We present a large dataset containing simulated core-loss electron energy loss spectroscopy (EELS) spectra with the elemental content as ground-truth labels. Additionally we present some neural networks trained on this data for element identification. The simulated dataset contains zero padded core-loss spectra from 0 to 3072 eV, which represents 107 core-loss edges through all 80 elements from Be up to Bi. The core-loss edges are calculated from the generalised oscillator strength (GOS) database presented by Zhang et al.[1] Generic fine structures using lifetime broadened peaks are used to imitate fine structure due to solid-state effects in experimental spectra. Generic low-loss regions are used to imitate the effect of multiple scattering. Each spectrum contains at least one edge of a given query element and possibly additional edges depending on samples drawn from The Materials Project [2]. The dataset contains for each of the 80 elements: 7000 training spectra, 1500 test spectra, 600 validation spectra and 100 spectra representing only the query element. This results in a total 736 000 labeled spectra. Code on how to – read the simulated data – transform HDF5 format to TFRecord format – train and evaluate neural networks using the simulated data – use the trained networks for automated element identification is available on GitHub at arnoannys/EELS_ID A full report on the simulation of the dataset and the training and evaluation of the neural networks can be found at: Annys, A., Jannis, D. & Verbeeck, J. Deep learning for automated materials characterisation in core-loss electron energy loss spectroscopy. Sci Rep 13, 13724 (2023). https://doi.org/10.1038/s41598-023-40943-7 [1] Zezhong Zhang, Ivan Lobato, Daen Jannis, Johan Verbeeck, Sandra Van Aert, & Peter Nellist. (2023). Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7729585 [2] Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, William Davidson Richards, Stephen Dacek, Shreyas Cholia, Dan Gunter, David Skinner, Gerbrand Ceder, Kristin A. Persson; Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. APL Mater 1 July 2013; 1 (1): 011002. [https://doi.org/10.1063/1.4812323](https://doi.org/10.1063/1.4812323) |
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UA @ admin @ c:irua:203391 |
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9015 |
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Zhang, Z.; Lobato, I.; Brown, H.; Jannis, D.; Verbeeck, J.; Van Aert, S.; Nellist, P. |
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Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions |
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2023 |
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Dataset; Electron microscopy for materials research (EMAT) |
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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. |
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UA @ admin @ c:irua:203392 |
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9042 |
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Grünewald, L.; Chezganov, D.; De Meyer, R.; Orekhov, A.; Van Aert, S.; Bogaerts, A.; Bals, S.; Verbeeck, J. |
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Supplementary Information for “In-situ Plasma Studies using a Direct Current Microplasma in a Scanning Electron Microscope” |
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2023 |
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Dataset; Engineering sciences. Technology; Electron microscopy for materials research (EMAT); Plasma Lab for Applications in Sustainability and Medicine – Antwerp (PLASMANT) |
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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 |
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UA @ admin @ c:irua:203389 |
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9100 |
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Cioni, M.; Delle Piane, M.; Polino, D.; Rapetti, D.; Crippa, M.; Arslan Irmak, E.; Pavan, G.M.; Van Aert, S.; Bals, S. |
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Data for Sampling Real‐Time Atomic Dynamics in Metal Nanoparticles by Combining Experiments, Simulations, and Machine Learning |
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2024 |
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Dataset; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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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. |
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UA @ admin @ c:irua:205843 |
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9143 |
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Lembrechts, J.; Clavel, J.; Lenoir, J.; Haider, S.; McDougall, K.; Nunez, M.; Alexander, J.; Barros, A.; Milbau, A.; Seipel, T.; Verbruggen, E.; Nijs, I. |
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Dataset: Roadside disturbance promotes plant communities with arbuscular mycorrhizal associations in mountain regions worldwide |
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2024 |
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Dataset; Plant and Ecosystems (PLECO) – Ecology in a time of change |
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Aim: We aimed to assess the impact of road disturbances on the dominant mycorrhizal types in ecosystems at the global level and how this mechanism can potentially lead to lasting plant community changes. Location: Globally distributed mountain regions Time Period: 2007-2018 Taxa studied: Plants (linked to their associated mycorrhizal fungi) Methods: We used a database of coordinated plant community surveys following mountain roads from 894 plots in 11 mountain regions across the globe in combination with an existing database of mycorrhizal-plant associations in order to approximate the relative abundance of mycorrhizal types in natural and disturbed environments. Results: Our findings show that roadside disturbance promotes the cover of plants associated with arbuscular mycorrhizal (AM) fungi. This effect is especially strong in colder mountain environments and in mountain regions where plant communities are dominated by ectomycorrhizal (EcM) or ericoid-mycorrhizal (ErM) associations. Furthermore, non-native plant species, which we confirmed to be mostly AM plants, are more successful in environments dominated by AM associations. Main Conclusions: These biogeographical patterns suggest that changes in mycorrhizal types could be a crucial factor in the worldwide impact of anthropogenic disturbances on mountain ecosystems. Indeed, roadsides foster AM-dominated systems, where AM-fungi might aid AM-associated plant species while potentially reducing the biotic resistance against invasive non-native species, often also associated with AM networks. Restoration efforts in mountain ecosystems will have to contend with changes in the fundamental make-up of EcM- and ErM plant communities induced by roadside disturbance. |
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UA @ admin @ c:irua:206132 |
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9198 |
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