Abstract: Both landfill taxes and Enhanced Waste Management (EWM) practices can mitigate the scarcity issue of landfill capacity by respectively reducing landfilled waste volumes and valorising future waste streams. However, high landfill taxes might erode incentives for EWM, even though EWM creates value by valorising waste. Concentrating on Flanders (Belgium), the paper applies dynamic optimisation modelling techniques to analyse how landfill taxation and EWM can reinforce each other and how taxation schemes can be adjusted in order to foster sustainable and welfare maximising ways of processing future waste streams. Based on the Flemish simulation results, insights are offered that are generally applicable in international waste and resource management policy. As shown, the optimal Flemish landfill tax that optimises welfare in the no EWM scenario is higher than the one in the EWM scenario (93 against (sic)50/ton). This difference should create incentives for applying EWM and is driven by the positive external effects that are generated by EWM practices. In Flanders, as the current landfill tax is slightly lower than these optimal levels, the choice that can be made is to further increase taxation levels or show complete commitment to EWM. A first generally applicable insight that was found points to the fact that it is not necessarily the case that the higher the landfill tax, the more effective waste management improvements can be realised. Other insights are about providing sufficient incentives for applying EMW practices and formulating appropriate pleas in support of technological development. By these insights, this paper should provide relevant information that can assist in triggering the transition towards a resource efficient, circular economy in Europe. (C) 2016 Elsevier Ltd. All rights reserved.

Abstract: A new version of the open source program MULTEM is presented here. It includes a graphical user interface, tapering truncation of the atomic potential, CPU multithreading functionality, single/double precision calculations, scanning transmission electron microscopy (STEM) simulations using experimental detector sensitivities, imaging STEM (ISTEM) simulations, energy filtered transmission electron microscopy (EFTEM) simulations, STEM electron energy loss spectroscopy (EELS) simulations along with other improvements in the algorithms. We also present a mixed channeling approach for the calculation of inelastic excitations, which allows one to considerably speed up time consuming EFTEM/STEM-EELS calculations.

Abstract: Electron tomography is a powerful technique for the 3D characterization of the morphology of nanostructures. Nevertheless, resolving the chemical composition of complex nanostructures in 3D remains challenging and the number of studies in which electron energy loss spectroscopy (EELS) is combined with tomography is limited. During the last decade, dedicated reconstruction algorithms have been developed for HAADF-STEM tomography using prior knowledge about the investigated sample. Here, we will use the prior knowledge that the experimental spectrum of each reconstructed voxel is a linear combination of a well-known set of references spectra in a so-called direct spectroscopic tomography technique. Based on a simulation experiment, it is shown that this technique provides superior results in comparison to conventional reconstruction methods for spectroscopic data, especially for spectrum images containing a relatively low signal to noise ratio. Next, this technique is used to investigate the spatial distribution of Fe dopants in Fe:Ceria nanoparticles in 3D. It is shown that the presence of the Fe2+ dopants is correlated with a reduction of the Ce atoms from Ce4+ towards Ce3+. In addition, it is demonstrated that most of the Fe dopants are located near the voids inside the nanoparticle.

Abstract: In the present paper, the optimal detector design is investigated for both detecting and locating light atoms from high resolution scanning transmission electron microscopy (HR STEM) images. The principles of detection theory are used to quantify the probability of error for the detection of light atoms from HR STEM images. To determine the optimal experiment design for locating light atoms, use is made of the so-called Cramer-Rao Lower Bound (CRLB). It is investigated if a single optimal design can be found for both the detection and location problem of light atoms. Furthermore, the incoming electron dose is optimised for both research goals and it is shown that picometre range precision is feasible for the estimation of the atom positions when using an appropriate incoming electron dose under the optimal detector settings to detect light atoms.

Abstract: Recently, imaging scanning transmission electron microscopy (ISTEM) has been proposed as a promising new technique combining the advantages of conventional TEM (CTEM) and STEM [1]. The ability to visualize light and heavy elements together makes it a particularly interesting new, spatially incoherent imaging mode. Here, we evaluate this technique in term of precision with which atomic column locations can be measured. By using statistical parameter estimation theory, we will show that these locations can be accurately measured with a precision in the picometer range. Furthermore, a quantitative comparison is made with HAADF STEM imaging to investigate the advantages of ISTEM.

Abstract: Aberration correction in scanning transmission electron microscopy (STEM) has greatly improved the lateral and depth resolution. When using depth sectioning, a technique during which a series of images is recorded at different defocus values, single impurity atoms can be visualised in three dimensions. In this paper, we investigate new possibilities emerging when combining depth sectioning and precise atom-counting in order to reconstruct nanosized particles in three dimensions. Although the depth resolution does not allow one to precisely locate each atom within an atomic column, it will be shown that the depth location of an atomic column as a whole can be measured precisely. In this manner, the morphology of a nanoparticle can be reconstructed in three dimensions. This will be demonstrated using simulations and experimental data of a gold nanorod.

Abstract: Recent studies are concisely reviewed, in which X-ray beams of (sub)micrometre to millimetre dimensions have been used for non-destructive analysis and characterization of pigments, minute paint samples, and/or entire paintings from the seventeenth to the early twentieth century painters. The overview presented encompasses the use of laboratory and synchrotron radiation-based instrumentation and deals with the use of several variants of X-ray fluorescence (XRF) as a method of elemental analysis and imaging, as well as with the combined use of X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS). Microscopic XRF is a variant of the method that is well suited to visualize the elemental distribution of key elements, mostly metals, present in paint multi-layers, on the length scale from 1 to 100 μm inside micro-samples taken from paintings. In the context of the characterization of artists pigments subjected to natural degradation, the use of methods limited to elemental analysis or imaging usually is not sufficient to elucidate the chemical transformations that have taken place. However, at synchrotron facilities, combinations of μ-XRF with related methods such as μ-XAS and μ-XRD have proven themselves to be very suitable for such studies. Their use is often combined with microscopic Fourier transform infra-red spectroscopy and/or Raman microscopy since these methods deliver complementary information of high molecular specificity at more or less the same length scale as the X-ray microprobe techniques. Since microscopic investigation of a relatively limited number of minute paint samples, taken from a given work of art, may not yield representative information about the entire artefact, several methods for macroscopic, non-invasive imaging have recently been developed. Those based on XRF scanning and full-field hyperspectral imaging appear very promising; some recent published results are discussed.

Abstract: Triple-modal imaging magnetic nanocapsules, encapsulating hydrophobic superparamagnetic iron oxide nanoparticles, are formulated and used to magnetically target solid tumours after intravenous administration in tumour-bearing mice. The engineered magnetic polymeric nanocapsules m-NCs are ~200 nm in size with negative Zeta potential and shown to be spherical in shape. The loading efficiency of superparamagnetic iron oxide nanoparticles in the m-NC was ~100%. Up to ~3- and ~2.2-fold increase in tumour uptake at 1 and 24 h was achieved, when a static magnetic field was applied to the tumour for 1 hour. m-NCs, with multiple imaging probes (e.g. indocyanine green, superparamagnetic iron oxide nanoparticles and indium-111), were capable of triple-modal imaging (fluorescence/magnetic resonance/nuclear imaging) in vivo. Using triple-modal imaging is to overcome the intrinsic limitations of single modality imaging and provides complementary information on the spatial distribution of the nanocarrier within the tumour. The significant findings of this study could open up new research perspectives in using novel magnetically-responsive nanomaterials in magnetic-drug targeting combined with multi-modal imaging.

Abstract: Drought is regarded as a slow-onset natural disaster that causes inevitable damage to water resources and to farm life. Currently, crisis management is the basis of drought mitigation plans, however, thus far studies indicate that effective drought management strategies are based on risk management. As a primary tool in mitigating the impact of drought, vulnerability assessment can be used as a benchmark in drought mitigation plans and to enhance farmers ability to cope with drought. Moreover, literature pertaining to drought has focused extensively on its impact, only awarding limited attention to vulnerability assessment as a tool. Therefore, the main purpose of this paper is to develop a conceptual framework for designing a vulnerability model in order to assess farmers level of vulnerability before, during and after the onset of drought. Use of this developed drought vulnerability model would aid disaster relief workers by enhancing the adaptive capacity of farmers when facing the impacts of drought. The paper starts with the definition of vulnerability and outlines different frameworks on vulnerability developed thus far. It then identifies various approaches of vulnerability assessment and finally offers the most appropriate model. The paper concludes that the introduced model can guide drought mitigation programs in countries that are impacted the most by drought.

Abstract: To get better performance from inductively coupled plasma (ICP)-based methods, it is informative to study the properties of the ICP under different conditions. Annemie Bogaerts and Maryam Aghaei at the University of Antwerp, Belgium, are using computational modeling to examine how various properties of the ICP, such as gas flow path lines and velocity, temperature changes, and ionization effects, are affected by numerous factors, such as the gas flow rates of injector and auxiliary gas, applied power, and even the very presence of a mass spectrometry (MS) sampler. They have also applied their models to study particle transport through the ICP. Using their developed model, it is now possible to predict optimum conditions for specific analyses. Bogaerts and Aghaei spoke to us about this work.

Abstract: Using density-functional theory in combination with the nonequilibrium Green's function formalism, we study the effect of the crystal lattice structure of organometallic perovskite CH3NH3PbI3 on its electronic transport properties. Both dispersive interactions and spin-orbit coupling are taken into account in describing structural and electronic properties of the system. We consider two different phases of the material, namely the orthorhombic and cubic lattice structures, which are energetically stable at low (< 160 K) and high (> 330 K) temperatures, respectively. The sizable geometrical differences between the two structures in term of lattice parameters, PbI6 octahedral tilts, rotation and deformations, have considerable impact on the transport properties of the material. For example, at zero bias and for all considered electron energies, the cubic phase has a larger transmission than the orthorhombic one, although both show similar electronic densities of states. Depending on the applied voltage, the current in the cubic system can be several orders of magnitude larger as compared to the one obtained for the orthorhombic sample. We attribute this enhancement in the transmission to the presence of extended states in the cubic phase due to the symmetrically shaped and ordered PbI6 octaherdra. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: Solar-powered consumer electronics are a likely starting point for organic photovoltaic (OPV) market development. Therefore, a generic discrete choice experiments study can determine how Flemish consumers value solar-cell characteristics for solar-poweied consumer electronics. Such characteristics include efficiency, lifetime, aesthetics, integratability, and price. We contribute to the literature by investigating preference heterogeneity in a solar-power niche market with an experimental design with a fixed reference alternative. The error components random parameter logit (ECRPL) with interactions provides a better fit than the latent class (LC) model for our choice data. The main effects had the expected signs. Consequently, aesthetics and integratability are OPV's assets. Nevertheless, heterogeneity puts the results that are valid for the average consumer into perspective. Based on our findings, OPV commercialization efforts should target the experienced, impatient user who highly values design and functionality. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: Hybrid nanostructures composed of metal nanoparticles and metal-organic frameworks (MOFs) have recently received increasing attention toward various applications due to the combination of optical and catalytic properties of nanometals with the large internal surface area, tunable crystal porosity and unique chemical properties of MOFs. Encapsulation of metal nanoparticles of well-defined shapes into porous MOFs in a core-shell type configuration can thus lead to enhanced stability and selectivity in applications such as sensing or catalysis. In this study, the encapsulation of single noble metal nanoparticles with arbitrary shapes within zeolitic imidazolate-based metal organic frameworks (ZIF-8) is demonstrated. The synthetic strategy is based on the enhanced interaction between ZIF-8 nanocrystals and metal nanoparticle surfaces covered by quaternary ammonium surfactants. High resolution electron microscopy and tomography confirm a complete core-shell morphology. Such a well-defined morphology allowed us to study the transport of guest molecules through the ZIF-8 porous shell by means of surface-enhanced Raman scattering by the metal cores. The results demonstrate that even molecules larger than the ZIF-8 aperture and pore size may be able to diffuse through the framework and reach the metal core.

Abstract: Automated crystal orientation and phase mapping in TEM are applied to the quantification of Ni4Ti3 precipitates in Ni–Ti shape memory alloys which will be used for the implantation of artificial sphincters operating using the all-round shape memory effect. This paper focuses on the optimization process of the technique to obtain best values for all major parameters in the acquisition of electron diffraction patterns as well as template generation. With the obtained settings, vast statistical data on nano- and microstructures essential to the operation of these shape memory devices become available.

Abstract: Urban green works as a recorder of atmospheric PM. This paper reports on the utility of combining magnetic- and particle-based techniques to investigate PM leaf deposition as a bio-indicator of metal pollution. Ivy (Hedera helix) leaves were collected from five different land use classes, i.e. forest, rural, roadside, industrial, train. Leaf magnetic measurements were done in terms of saturation isothermal remanent magnetization (leaf SIRM), while ca. 40,000 leaf-deposited particles were analyzed through SEM/EDX to estimate the elemental composition. The influence of the different land use classes was registered both magnetically and in terms of metal content. Leaf area-normalized SIRM values ranged from 19.9 to 444.0 μA, in the following order forest < rural < roadside < industrial < train. Leaf SIRM showed to be significantly correlated (p < 0.01) with the content in Fe, Zn, and Pb, followed by Mn and Cd (p < 0.05), while no significant correlation was found with the metals Cr and Cu. Although presenting a similar metal content, roadside and train were magnetically very distinct. By exhibiting a very high content in Pb, and with an Fe content being comparable to the one observed at the forest and rural land uses, the industrial leaf-deposited particles showed to be mainly due to industrial activity. While SEM/EDX is a suitable approach for detailed particle analysis, leaf SIRM of ivy can be used as a rapid discriminatory tool for metal pollution. Their complementary use delivers further knowledge on land use classes reflecting different PM conditions and/or sources.