“Restoration of X-ray fluorescence images of hidden paintings”. Anitha A, Brasoveanu A, Duarte M, Hughes S, Daubechies I, Dik J, Janssens K, Alfeld M, Signal processing 93, 592 (2013). http://doi.org/10.1016/J.SIGPRO.2012.09.027
Abstract: This paper describes our methods for repairing and restoring images of hidden paintings (paintings that have been painted over and are now covered by a new surface painting) that have been obtained via noninvasive X-ray fluorescence imaging of their canvases. This recently developed imaging technique measures the concentrations of various chemical elements at each two-dimensional spatial location across the canvas. These concentrations in turn result from pigments present both in the surface painting and in the hidden painting beneath. These X-ray fluorescence images provide the best available data from which to noninvasively study a hidden painting. However, they are typically marred by artifacts of the imaging process, features of the surface painting, and areas of information loss. Repairing and restoring these images thus consists of three stages: (1) repairing acquisition artifacts in the dataset, (2) removal of features in the images that result from the surface painting rather than the hidden painting, and (3) identification and repair of areas of information loss. We describe methods we have developed to address each of these stages: a total-variation minimization approach to artifact correction, a novel method for underdetermined blind source separation with multimodal side information to address surface feature removal, and two application-specific new methods for automatically identifying particularly thick or X-ray absorbent surface features in the painting. Finally, we demonstrate the results of our methods on a hidden painting by the artist Vincent van Gogh. (C) 2012 Elsevier B.V. All rights reserved.
Keywords: A1 Journal article; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
Impact Factor: 3.11
Times cited: 13
DOI: 10.1016/J.SIGPRO.2012.09.027
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“Ligand-Mode Directed Selectivity in Cu–Ag Core–Shell Based Gas Diffusion Electrodes for CO2Electroreduction”. Irtem E, Arenas Esteban D, Duarte M, Choukroun D, Lee S, Ibáñez M, Bals S, Breugelmans T, Acs Catalysis , 13468 (2020). http://doi.org/10.1021/acscatal.0c03210
Abstract: Bimetallic nanoparticles with tailored size and specific composition have shown promise as stable and selective catalysts for electrochemical reduction of CO2 (CO2R) in batch systems. Yet, limited effort was devoted to understand the effect of ligand coverage and postsynthesis treatments on CO2 reduction, especially under industrially applicable conditions, such as at high currents (>100 mA/cm2) using gas diffusion electrodes (GDE) and flow reactors. In this work, Cu–Ag core–shell nanoparticles (11 ± 2 nm) were prepared with three different surface modes: (i) capped with oleylamine, (ii) capped with monoisopropylamine, and (iii) surfactant free with a reducing borohydride agent; Cu–Ag (OAm), Cu–Ag (MIPA), and Cu–Ag (NaBH4), respectively. The ligand exchange and removal was evidenced by infrared spectroscopy (ATR-FTIR) analysis, whereas high-resolution scanning transmission electron microscopy (HAADF-STEM) showed their effect on the interparticle distance and nanoparticle rearrangement. Later on, we developed a process-on-substrate method to track these effects on CO2R. Cu–Ag (OAm) gave a lower on-set potential for hydrocarbon production, whereas Cu–Ag (MIPA) and Cu–Ag (NaBH4) promoted syngas production. The electrochemical impedance and surface area analysis on the well-controlled electrodes showed gradual increases in the electrical conductivity and active surface area after each surface treatment. We found that the increasing amount of the triple phase boundaries (the meeting point for the electron–electrolyte–CO2 reactant) affect the required electrode potential and eventually the C+2e̅/C2e̅ product ratio. This study highlights the importance of the electron transfer to those active sites affected by the capping agents—particularly on larger substrates that are crucial for their industrial application.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT); Applied Electrochemistry & Catalysis (ELCAT)
Impact Factor: 12.9
Times cited: 23
DOI: 10.1021/acscatal.0c03210
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“Enhanced CO2 electroreduction with metal-nitrogen-doped carbons in a continuous flow reactor”. Duarte M, Daems N, Hereijgers J, Arenas Esteban D, Bals S, Breugelmans T, Journal Of Co2 Utilization 50, 101583 (2021). http://doi.org/10.1016/J.JCOU.2021.101583
Abstract: As part of a mitigation and adaptation approach to increasing carbon dioxide atmospheric concentrations, we report superior performance of various metal-nitrogen-doped carbon catalysts, synthesized using an easily up-scalable method, for the electrochemical reduction to carbon monoxide and/or formate at industrially relevant current densities up to 200 mAcm−2. Altering the embedded transition metal (i.e. Sn, Co, Fe, Mn and Ni) allowed to tune the selectivity towards the desired product. Mn-N-C and Fe-N-C performance was compromised by its high CO* binding energy, while Co-N-C catalyzed preferentially the HER. Ni-N-C and Sn-N-C revealed to be promising electrocatalysts, the latter being evaluated for the first time in a flow reactor. A productivity of 589 L CO m-2 h-1 at -1.39 VRHE with Ni-N-C and 751 g HCOO- m-2 h-1 at -1.47 VRHE with Sn-N-C was achieved with no signs of degradation detected after 24 h of operation at industrially relevant current densities (100 mAcm−2). Stable operation at 200 mAcm−2 led to turnover frequencies for the production of carbon products of up to 5176 h-1. These enhanced productivities, in combination with high stability, constitute an essential step towards the scalability and ultimately towards the economical valorization of CO2 electrolyzers using metal-containing nitrogen-doped catalysts.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT); Applied Electrochemistry & Catalysis (ELCAT)
Impact Factor: 4.292
Times cited: 14
DOI: 10.1016/J.JCOU.2021.101583
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“Virtual underpainting reconstruction from X-ray fluorescence imaging data”. Anitha A, Brasoveanu A, Duarte MF, Hughes SM, Daubechies I, Dik J, Janssens K, Alfeld M, , 1239 (2011)
Keywords: P1 Proceeding; AXES (Antwerp X-ray Analysis, Electrochemistry and Speciation)
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