“Recombination reactions and geometry effects in laser microprobe mass analysis studied with 12C/13C bilayers”. Bruynseels F, Van Grieken R, (1986)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Reference matarials for microanalytical nuclear techniques”. Injuk J, Van Grieken R, (1995)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Research for preventive conservation and optimal presentation of world heritage in Museum Plantin-Moretus, Antwerp”. Kontozova V, Krupińska B, Van Grieken R, Janssen E, Moris H, Aerts D, Watteeuw L, van Bos M, Peckstadt A, (2011)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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Chou L, Harlay J, Roevros N, Lannuzel D, Rebreanu L, van der Zee C, Lapernat P-E, Daro M-H, Aerts K, Godoi R, Van Grieken R (2009) Role of oceanic production and dissolution of calcium carbonate in climate change (CCCC): final report
Keywords: Minutes and reports; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Salt weathering research: present state and future directions”. Delalieux F, Van Grieken R, Moropoulou A, (2003)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Single particle characterisation of inorganic North Sea suspensions”. Jambers W, Van Grieken R, (1996)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Some properties of “bulky&rdquo, links, generated by Generalized Möbius Listing's bodies GML4n”. Caratelli D, Gielis J, Ricci PE, Tavkhelidze I, (2013)
Keywords: P3 Proceeding; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL)
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“Some studies of the effect of indoor and outdoor pollutants on cultural heritage items”. Van Grieken R, Kontozova V, Godoi RHM, Spolnik Z, Worobiec A, Deutsch F, Bencs L, (2005)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Laboratory Experimental Medicine and Pediatrics (LEMP)
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“Speciation and distribution of sulfur and nitrogen in individual aerosol particles measured by LAMMA”. Bruynseels F, Van Grieken R, (1984)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Stof : begrippen, bronnen en analysmethoden”. Van Grieken R, (1985)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Study of environmental effects on deterioration of monuments: case study the cathedral of Bari, Italy”. Zezza F, Torfs K, Van Grieken R, García Pascua N, Macri F, (1996)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Study of individual estuarine suspension particles by automated electron-probe X-ray microanalysis”. Bernard P, Van Grieken R, Eisma D, (1985)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Study of individual particle types and heavy metal deposition for North Sea aerosols using micro- and trace analysis techniques”. Injuk J, de Bock L, van Malderen H, Van Grieken R, (1996)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Study of the main physical processes contributing to image formation in emission radiography using mathematical modeling”. Leyva Pernia D, Cabal Rodríguez AE, Schalm O, van Espen P, Piñera Hernández I, Abreu Alfonso Y, (2013)
Keywords: P3 Proceeding; Engineering sciences. Technology; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Antwerp Cultural Heritage Sciences (ARCHES)
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“Studying the composition of atmospheric aerosols through the joint application of hierarchical, non-hierarchical and fuzzy clustering to EPXMA data sets”. Treiger B, Bondarenko I, van Malderen H, Van Grieken R, (1996)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Sub-minute determination of BTEX in environmental samples using low pressure GC-ITMS”. Joos PE, Godoi AFL, de Jong R, de Zeeuw J, Van Grieken R, (2002)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Sulfur and heavy metals over the Atlantic Ocean : comparison with other marine data”. Maenhaut W, Selen A, van Espen P, Van Grieken R, Winchester JW, (1980)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation); Chemometrics (Mitac 3)
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“Synchrotron computed X-ray fluorescence microtomography in environmental and earth sciences”. Vincze L, Vekemans B, Adams F, (2003)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Synchrotron computed X-ray fluorescence tomography in environmental and earth sciences: radiation”. Vincze L, Vekemans B, Adams F, (2004)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Towards a geometrical theory of morphology and morphogenesis”. Gielis J, Ding Y, Shi P, (2016)
Keywords: P3 Proceeding; Engineering sciences. Technology; Sustainable Energy, Air and Water Technology (DuEL)
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“Understanding ultrafine particles dynamics within a one km urban grid”. Mishra VK, Dons E, Panis LI, Frijns E, van Poppel M, Berghmans P, Bleux N, Wuyts K, Samson R, (2010)
Keywords: P3 Proceeding; Sustainable Energy, Air and Water Technology (DuEL)
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“Use of grazing emission XRF spectrometry for silicon wafer surface contamination measurements”. de Gendt S, Kenis K, Mertens PW, Heyns MM, Claes M, Van Grieken RE, Bailleul A, Knotter M, de Bokx PK, (1996)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Weathering mechanism of Pentelic marble under ambient atmospheric conditions derived from runoff studies”. Delalieux F, Sweevers H, Van Grieken R, (1997)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“Weathering of bare and treated limestones under ambient conditions using runoff water analysis and microanalysis”. Vleugels G, Van Grieken R, (1992)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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Van Grieken R (1998) Working close to the detection limits: XRF
Keywords: Minutes and reports; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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“X-ray spectrometry for air pollution and cultural heritage research”. Van Grieken R, Delalieux F, (2004)
Keywords: P3 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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Nakazato R, Matsumoto K, Yamaguchi N, Cavallo M, Crocella V, Bonino F, Quintelier M, Hadermann J, Rosero-Navarro NC, Miura A, Tadanaga K (2023) CO2 Electrochemical Reduction with Zn-Al Layered Double Hydroxide-Loaded Gas-Diffusion Electrode (Supporting Information)
Abstract: 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.
Keywords: Dataset; Electron microscopy for materials research (EMAT)
DOI: 10.50892/DATA.ELECTROCHEMISTRY.24069993
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Annys A, Jannis D, Verbeeck J (2023) Core-loss EELS dataset and neural networks for element identification
Abstract: 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)
Keywords: Dataset; Electron microscopy for materials research (EMAT)
DOI: 10.5281/ZENODO.8004912
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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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“Noise-resistant correlation-based alignment of head-related transfer functions for high-fidelity spherical harmonics representation”. Reijniers J, Partoens B, Peremans H, (2023)
Abstract: It is standard practice in virtual reality applications to synthesize binaural audio based on a discrete set of directionally-dependent head-related impulse responses (HRIRs). This set of HRIRs is often time-aligned in a pre-processing step, to allow for high-fidelity interpolation between HRIRs corresponding with neighbouring directions. The fidelity of this operation depends on the similarity of neighbouring aligned HRIRs. The pairwise quality of similarity makes it a difficult criterion to optimize globally and consequently one often resorts to alignment methods based on a specific feature that can be extracted for each HRIR separately, e.g., the first-onset of the peak or the group delay. However, such proxies for similarity are very sensitive to noise and therefore require a high signal-to-noise ratio, which makes them less suitable for processing HRIRs acquired outside an anechoic room. In this paper, we advance a novel alignment method, which maximizes the similarity – defined as the correlation between the full-length HRIRs – between neighbouring aligned HRIRs for all directions at once. We show that this correlation-based alignment procedure outperforms the first-onset alignment with regards to the fidelity of the spherical harmonics representation of both the spectral and interaural time difference (ITD) information, when tested on the KEMAR HRIR and six human HRIRs. Finally, we show that the correlation-based alignment is more robust to noise.
Keywords: P3 Proceeding; Engineering sciences. Technology; Engineering Management (ENM); Condensed Matter Theory (CMT)
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