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“A simple method to clean ligand contamination on TEM grids”. Li C, Tardajos AP, Wang D, Choukroun D, Van Daele K, Breugelmans T, Bals S, Ultramicroscopy 221, 113195 (2021). http://doi.org/10.1016/j.ultramic.2020.113195
Abstract: Colloidal nanoparticles (NPs) including nanowires and nanosheets made by chemical methods involve many organic ligands. When the structure of NPs is investigated via transmission electron microscopy (TEM), the organic ligands act as a source for e-beam induced deposition and this causes substantial build-up of carbon layers in the investigated areas, which is typically referred to as “contamination” in the eld of electron mi- croscopy. This contamination is often more severe for scanning TEM, a technique that is based on a focused electron beam and hence higher electron dose rate. In this paper, we report a simple and effective method to clean drop-cast TEM grids that contain NPs with ligands. Using a combination of activated carbon and ethanol, this method effectively reduces the amount of ligands on TEM grids, and therefore greatly improves the quality of electron microscopy images and subsequent analytical measurements. This ef cient and facile method can be helpful during electron microscopy investigation of different kinds of nanomaterials that suffer from ligand- induced contamination.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT); Applied Electrochemistry & Catalysis (ELCAT)
Impact Factor: 2.843
Times cited: 10
DOI: 10.1016/j.ultramic.2020.113195
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“Modelling ADF STEM images using elliptical Gaussian peaks and its effects on the quantification of structure parameters in the presence of sample tilt”. De wael A, De Backer A, Lobato I, Van Aert S, Ultramicroscopy , 113391 (2021). http://doi.org/10.1016/j.ultramic.2021.113391
Abstract: A small sample tilt away from a main zone axis orientation results in an elongation of the atomic columns in ADF STEM images. An often posed research question is therefore whether the ADF STEM image intensities of tilted nanomaterials should be quantified using a parametric imaging model consisting of elliptical rather than the currently used symmetrical peaks. To this purpose, simulated ADF STEM images corresponding to different amounts of sample tilt are studied using a parametric imaging model that consists of superimposed 2D elliptical Gaussian peaks on the one hand and symmetrical Gaussian peaks on the other hand. We investigate the quantification of structural parameters such as atomic column positions and scattering cross sections using both parametric imaging models. In this manner, we quantitatively study what can be gained from this elliptical model for quantitative ADF STEM, despite the increased parameter space and computational effort. Although a qualitative improvement can be achieved, no significant quantitative improvement in the estimated structure parameters is achieved by the elliptical model as compared to the symmetrical model. The decrease in scattering cross sections with increasing sample tilt is even identical for both types of parametric imaging models. This impedes direct comparison with zone axis image simulations. Nonetheless, we demonstrate how reliable atom-counting can still be achieved in the presence of small sample tilt.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
DOI: 10.1016/j.ultramic.2021.113391
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“Shape from projections via differentiable forward projector for computed tomography”. Koo J, Dahl AB, Bærentzen JA, Chen Q, Bals S, Dahl VA, Ultramicroscopy 224, 113239 (2021). http://doi.org/10.1016/j.ultramic.2021.113239
Abstract: In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
Times cited: 3
DOI: 10.1016/j.ultramic.2021.113239
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“ab initio description of bonding for transmission electron microscopy”. Madsen J, Pennycook TJ, Susi T, Ultramicroscopy 231 (2021). http://doi.org/10.1016/J.ULTRAMIC.2021.113253
Abstract: The simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret their contrast and extract specimen features. This is especially true for high-resolution phase-contrast imaging of materials, but electron scattering simulations based on atomistic models are widely used in materials science and structural biology. Since electron scattering is dominated by the nuclear cores, the scattering potential is typically described by the widely applied independent atom model. This approximation is fast and fairly accurate, especially for scanning TEM (STEM) annular dark-field contrast, but it completely neglects valence bonding and its effect on the transmitting electrons. However, an emerging trend in electron microscopy is to use new instrumentation and methods to extract the maximum amount of information from each electron. This is evident in the increasing popularity of techniques such as 4D-STEM combined with ptychography in materials science, and cryogenic microcrystal electron diffraction in structural biology, where subtle differences in the scattering potential may be both measurable and contain additional insights. Thus, there is increasing interest in electron scattering simulations based on electrostatic potentials obtained from first principles, mainly via density functional theory, which was previously mainly required for holography. In this Review, we discuss the motivation and basis for these developments, survey the pioneering work that has been published thus far, and give our outlook for the future. We argue that a physically better justified ab initio description of the scattering potential is both useful and viable for an increasing number of systems, and we expect such simulations to steadily gain in popularity and importance.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
DOI: 10.1016/J.ULTRAMIC.2021.113253
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“Green walls for mitigating urban particulate matter pollution : a review”. Ysebaert T, Koch K, Samson R, Denys S, Urban Forestry &, Urban Greening 59, 127014 (2021). http://doi.org/10.1016/J.UFUG.2021.127014
Abstract: Air pollution caused by particulate matter (PM) is a well-known health issue in urban environments. Urban green infrastructure offers opportunities as a nature-based solution to urban PM pollution. Green walls have advantages over other types of urban green infrastructure, since they can be applied to the enormous available wall area in cities and since they do not interfere with the prevailing ventilation resulting in elevated PM levels. However, this has raised questions about the effectiveness of GW in removing PM and this could explain the limited applicability of green walls to tackle PM pollution. Nevertheless, it is suggested that green walls have a significant unexploited potential and this review article aims to address current knowledge gaps and to propose future research requirements for the implementation of green walls to mitigate urban PM pollution. An in-depth analysis is given of the mechanisms behind PM deposition and the influence of vegetation properties on this process, as well as the practices followed to model PM dispersion and deposition. It was suggested that particle deposition on green walls depends on the green wall species, pollution level, and the residence time of PM in a street (canyon). Rainfall plays an important role in the PM pathway, although it is not a necessary requirement to sustain PM deposition on plant leaves. There are still some discrepancies in the literature about the ideal plant characteristics for PM deposition in terms of the macro- and microstructures that require further investigation, especially in comparison with tree and shrub species. In addition, extensively validated models are required to accurately calculate the impact of green walls on air flow and the PM concentration on site.
Keywords: A1 Journal article; Engineering sciences. Technology; Art; Sustainable Energy, Air and Water Technology (DuEL)
Impact Factor: 2.113
DOI: 10.1016/J.UFUG.2021.127014
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“Development and application of a predictive modelling approach for household packaging waste flows in sorting facilities”. Kleinhans K, Hallemans M, Huysveld S, Thomassen G, Ragaert K, Van Geem KM, Roosen M, Mys N, Dewulf J, De Meester S, Waste Management 120, 290 (2021). http://doi.org/10.1016/j.wasman.2020.11.056
Abstract: Household packaging waste sorting facilities consist of complex networks of processes to separate diverse waste streams. These facilities are a key first step to re-enter materials into the recycling chain. However, so far there are no general methods to predict the performance of such sorting facilities, i.e.
how efficiently the heterogeneous packaging waste is sorted into fractions with value for further recycling. In this paper, a model of the material flow in a sorting facility is presented, which allows changing the incoming waste composition, split factors on the sorting units as well as the setup of the sorting facility. The performance of the sorting facility is judged based on the purity of the output material (grade) and the recovery of the input material. A validation of the model was performed via a case study on Belgian post-consumer packaging waste with a selection of typical waste items that can be found in this stream. Moreover, the model was used to predict the possible sorting qualities of future Belgian postconsumer packaging waste after an extension of the allowed waste packaging items in the waste stream. Finally, a sensitivity analysis was performed on the split factors, which are a key data source in the model. Overall, the developed model is flexible and able to predict the performance of packaging waste sorting facilities as well as support waste management and design for recycling decisions, including future
design of packaging, to ensure proper sorting and separation.
Keywords: A1 Journal Article; Engineering Management (ENM) ;
DOI: 10.1016/j.wasman.2020.11.056
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“Time to act–assessing variations in qPCR analyses in biological nitrogen removal with examples from partial nitritation/anammox systems”. Agrawal S, Weissbrodt DG, Annavajhala M, Jensen MM, Arroyo JMC, Wells G, Chandran K, Vlaeminck SE, Terada A, Smets BF, Lackner S, Water Research 190, 116604 (2021). http://doi.org/10.1016/J.WATRES.2020.116604
Abstract: Quantitative PCR (qPCR) is broadly used as the gold standard to quantify microbial community fractions in environmental microbiology and biotechnology. Benchmarking efforts to ensure the comparability of qPCR data for environmental bioprocesses are still scarce. Also, for partial nitritation/anammox (PN/A) systems systematic investigations are still missing, rendering meta-analysis of reported trends and generic insights potentially precarious. We report a baseline investigation of the variability of qPCR-based analyses for microbial communities applied to PN/A systems. Round-robin testing was performed for three PN/A biomass samples in six laboratories, using the respective in-house DNA extraction and qPCR protocols. The concentration of extracted DNA was significantly different between labs, ranged between 2.7 and 328 ng mg−1 wet biomass. The variability among the qPCR abundance data of different labs was very high (1−7 log fold) but differed for different target microbial guilds. DNA extraction caused maximum variation (3–7 log fold), followed by the primers (1–3 log fold). These insights will guide environmental scientists and engineers as well as treatment plant operators in the interpretation of qPCR data.
Keywords: A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL)
Impact Factor: 6.942
DOI: 10.1016/J.WATRES.2020.116604
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“A database system for querying of river networks : facilitating monitoring and prediction applications”. Bollen E, Pagan BR, Kuijpers B, Van Hoey S, Desmet N, Hendrix R, Dams J, Seuntjens P, Water Science And Technology-Water Supply (2021). http://doi.org/10.2166/WS.2021.433
Abstract: The increasing availability of real-time in situ measurements and remote sensing observations have the potential to contribute to the optimization of water resources management. Global challenges such as climate change, intensive agriculture and urbanization put a high pressure on our water resources. Due to recent innovations in measuring both water quantity and quality, river systems can now be monitored in real time at an unprecedented spatial and temporal scale. To interpret the sensor measurements and remote sensing observations additional data for example on: the location of the measurement, upstream and downstream catchment characteristics, horizontal ellipsis are required. In this paper, we present a data management system to support flow-path related functionality for decision making and prediction modelling. Adding meta data sets and facilitating (near) real-time processing of sensor data questions are key concepts for the systems. The potential of the database framework for hydrological applications is demonstrated using different applications for the river system of Flanders. In one, the database framework is used to simulate the daily discharge for each segment within a catchment using a simple data-driven approach. The presented system is useful for numerous applications including pollution tracking, alerting and inter-sensor validation in river systems, or related networks.
Keywords: A1 Journal article; Sustainable Energy, Air and Water Technology (DuEL)
Impact Factor: 0.573
DOI: 10.2166/WS.2021.433
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“Er bestaan geen absurde, irrationele, onregelmatige of onderling niet-onmeetbare meetkundige getallen”. Gielis J, Wiskunde en onderwijs 47, 23 (2021)
Keywords: A2 Journal article; Sustainable Energy, Air and Water Technology (DuEL)
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