Abstract: Doping two single transition-metal (TM) atoms on a substrate host opens numerous possibilities for catalyst design. However, what if the substrate contains more than one vacancy site? Then, the combination of two TMs along with their distribution patterns becomes a design parameter potentially complementary to the substrate itself and the bimetal composition. In this study, we investigate ammonia synthesis under mild electrocatalytic conditions on a transition-metal-doped porous C24N24 catalyst using density functional theory (DFT). The TMs studied include Ti, Mn, and Cu in a 2:4 dopant ratio (Ti2Mn4@C24N24 and Ti2Cu4@N-24(24)). Our computations show that a single Ti atom in both catalysts exhibits the highest selectivity for N-2 fixation at ambient conditions. This work is a good theoretical model to establish the structure-activity relationship, and the knowledge earned from the metal-N-4 moieties may help studies of related nanomaterials, especially those with curved structures.

Abstract: The alpha-T3 lattice model interpolates a honeycomb (graphene-like) lattice and a T3 (also known as dice) lattice via the parameter alpha. These lattices are made up of three atoms per unit cell. This gives rise to an additional dispersionless flat band touching the conduction and valence bands. Electrons in this model are analogous to Dirac fermions with an enlarged pseudospin, which provides unusual tunneling features like omnidirectional Klein tunneling, also called super-Klein tunneling (SKT). However, it is unknown how small deviations in the equivalence between the atomic sites, i.e., variations in the alpha parameter, and the number of tunnel barriers changes the transmission properties. Moreover, it is interesting to learn how tunneling occurs through regions where the energy spectrum changes from linear with a middle flat band to a hyperbolic dispersion. In this paper we investigate these properties, its dependence on the number of square barriers and the alpha parameter for either gapped and gapless cases. Furthermore, we compare these results to the case where electrons tunnel from a region with linear dispersion to a region with a bandgap. In the latter case, contrary to tunneling through a potential barrier, the SKT is no longer observed. Finally, we find specific cases where transmission is allowed due to a symmetry breaking of sublattice equivalence.

Abstract: Rational composition design of trimetallic phosphide catalysts is of significant importance for enhanced surface reaction and efficient catalytic performance. Herein, hierarchical CoxNiyFezP with precise control of stoichiometric metallic elements (x:y:z = (1-10):(1-10):1) has been synthesized, and Co1.3Ni0.5Fe0.2P, as the most optimal composition, exhibits remarkable catalytic activity (eta = 320 mV at 10 mA cm(-2)) and long-term stability (ignorable decrease after 10 h continuous test at the current density of 10 mA cm(-2)) toward oxygen evolution reaction (OER). It is found that the surface P in Co1.3Ni0.5Fe0.2P was replaced by 0 under the OER process. The density function theory calculations before and after long-term stability tests suggest the clear increasing of the density of states near the Fermi level of Co1.3Ni0.5Fe0.2P/ Co1.3Ni0.5Fe0.2O, which could enhance the OH- adsorption of our electrocatalysts and the corresponding OER performance.

Abstract: The increasing illicit production, distribution and abuse of amphetamine (AMP) poses a challenge for law enforcement worldwide. To effectively combat this issue, fast and portable tools for the on-site screening of suspicious samples are required. Electrochemical profile (EP)-based sensing of illicit drugs has proven to be a viable option for this purpose as it allows rapid voltammetric measurements via the use of disposable and low-cost graphite screen-printed electrodes (SPEs). In this work, a highly practical paraformaldehyde (PFA)-coated sensor, which unlocks the detectability of primary amines through derivatization, is developed for the on-site detection of AMP in seized drug samples. A potential interval was defined at the sole AMP peak (which is used for identification of the target analyte) to account for potential shifts due to fluctuations in concentration and temperature, which are relevant factors for on-site use. Importantly, it was found that AMP detection was not hindered by the presence of common diluents and adulterants such as caffeine, even when present in high amounts. When inter-drug differentiation is desired, a simultaneous second test with the same solution on an unmodified electrode is introduced to provide the required additional electrochemical information. Finally, the concept was validated by analyzing 30 seized AMP samples (reaching a sensitivity of 96.7 %) and comparing its performance to that of commercially available Raman and Fourier Transform Infrared (FTIR) devices.

Abstract: Being confronted with increasing and expanding urbanisation and the loss of natural green spaces, our living environment is threatened more and more by the effects of global climate change. Green infrastructure is often thought of as the solution to increase climate resilience and reinforce the quality of the lived environment simultaneously. While the benefits, or ecosystem services, that are generated through green infrastructure have been studied intensively, forces that influence green infrastructure decision-making have been far less subjected to thorough research. In this study a discrete choice experiment was conducted with local decision makers in Flemish municipalities to reveal crucial factors in the decision process applied to green infrastructure projects. Flanders is one of the most densely built regions in Europe, stressing the urgency to understand local spatial decision factors to guarantee green space. 568 decision makers active in the local administration of 235 Flemish municipalities participated in the experiment, set in a hypothetical neighbourhood park. Every choice alternative exists of five attributes: investment cost, maintenance cost, deferred investment, recreational value, and climate impact. We find that barriers hampering Flemish munipalities' GI implementation, differ over size of the municipality: smallers municipalities are more affected by knowledge gaps, while larger municipalities are experiencing prioritization issues. Results from hierarchical Bayes choice models indicate that municipal decisions on green infrastructure are highly – almost solely -cost-driven, rarely consider the full range of benefits, and centre around short-term and immediate arguments. Moreover, interaction models reveal that a municipalities' financial result is a key determinant of its willingness to invest in public greening and consider long term benefits, suggesting that GI is a luxury good. The results expose some of the heuristics in GI decision making and can be used to inform higher authorities on ways to overcome barriers towards informed decision-making and to facilitate GI investment.

Abstract: The success and continued expansion of research on metal-oxo clusters owe largely to their structural richness and wide range of functions. However, while most of them known to date are negatively charged polyoxometalates, there is only a handful of cationic ones, much less functional ones. Here, we show an all-inorganic hydroxyiodide [H(10.)7Sb(32.1)O(44)][H2.1Sb2.1I8O6][Sb0.76I6](2)center dot 25H(2)O (HSbOI), forming a face-centered cubic structure with cationic Sb32O44 clusters and two types of anionic clusters in its interstitial spaces. Although it is submicrometer in size, electron diffraction tomography of HSbOI allowed the construction of the initial structural model, followed by powder Rietveld refinement to reach the final structure. The cationic cluster is characterized by the presence of acidic protons on its surface due to substantial Sb3+ deficiencies, which enables HSbOI to serve as an excellent solid acid catalyst. These results open up a frontier for the exploration and functionalization of cationic metal-oxo clusters containing heavy main group elements.

Abstract: Dynamic recrystallization (DRX) within adiabatic shear bands forming during the fracture of TRIP-TWIP β−metastable Ti-12Mo (wt %) alloy was recently reported. The formation of 1-3 µm thick-adiabatic shear bands, and of dynamic recrystallization, was quite surprising as their occurrence generally requires high temperature and/or high strain rate loading while these samples were loaded in quasi-static conditions at room temperature. To better understand the fracture mechanism and associated microstructural evolution, thin foils representative of different stages of the fracture process were machined from the fracture surface by Focused Ion Beam (FIB) and analyzed by Transmission Electron Microscopy (TEM) and Automated Crystal Orientation mapping (ACOM-TEM). Complex microstructure transformations involving severe plastic deformed nano-structuration, crystalline rotation and local precipitation of the omega phase were identified. The spatial and temporal evolution of the microstructure during the propagation of the crack was explained through dynamic recovery and continuous dynamic recrystallization, and linked to the modelled distribution of temperature and strain level where TEM samples were extracted.

Abstract: Among lithium battery cathode materials, Li1.2Ni0.13Mn0.54Co0.13O2 (LR-NMC) has a high theoretical capacity, but suffers from voltage and capacity fade during cycling. This is partially ascribed to transition metal cation migration, which involves the local transformation of the honeycomb layered structure to spinel-like nano-domains. Determination of the honeycomb layered/spinel phase ratio from powder X-ray diffraction data is hindered by the nanoscale of the functional material and the domains, diverse types of twinning, stacking faults, and the possible presence of the rock salt phase. Determining the phase ratio from transmission electron microscopy imaging can only be done for thin regions near the surfaces of the crystals, and the intense beam that is needed for imaging induces the same transformation to spinel as cycling does. In this article, it is demonstrated that the low electron dose sufficient for electron diffraction allows the collection of data without inducing a phase transformation. Using calculated electron diffraction patterns, we demonstrate that it is possible to determine the volume ratio of the different phases in the particles using a pair-wise comparison of the intensities of the reflections. Using this method, the volume ratio of spinel structure to honeycomb layered structure is determined for a submicron sized crystal from experimental three-dimensional electron diffraction (3D ED) and precession electron diffraction (PED) data. Both twinning and the possible presence of the rock salt phase are taken into account. After 150 charge-discharge cycles, 4% of the volume in LR-NMC particles was transformed irreversibly from the honeycomb layered structure to the spinel structure. The proposed method would be applicable to other multi-phase materials as well.

Abstract: We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen from the Convolutional Neural Network (CNN) predicted exit waves. We demonstrate that an appropriate forward model in combination with open data frameworks can be used to generate large synthetic datasets for training. In combination with augmenting the data with Poisson noise corresponding to varying dose-values, we effectively eliminate overfitting issues. The U-NET[1] based architecture of the CNN is adapted to the task at hand and performs well while maintaining a relatively small size and fast performance. The validity of the approach is confirmed by comparing the reconstruction to well-established methods using simulated, as well as real electron microscopy data. The proposed method is shown to be effective particularly in the low dose range, evident by strong suppression of noise, good spatial resolution, and sensitivity to different atom types, enabling the simultaneous visualisation of light and heavy elements and making different atomic species distinguishable. Since the method acts on a very local scale and is comparatively fast it bears the potential to be used for near-real-time reconstruction during data acquisition.

Abstract: Enhancing aluminium interaction with graphene-based materials is of crucial importance for the development of Al-storage materials and novel functional materials via atomically precise doping. Here, DFT calculations are employed to investigate Al interactions with non-doped and N-doped graphene nanoribbons (GNRs) and address the impact of the edge sites and N-containing defects on the material's reactivity towards Al. The presence of edges does not influence the energetics of Al adsorption significantly (compared to pristine graphene sheet). On the other hand, N-doping of graphene nanoribbons is found to affect the adsorption energy of Al to an extent that strongly depends on the type of N-containing defect. The introduction of edge-NO group and doping with in -plane pyridinic N result in Al adsorption nearly twice as strong as on pristine graphene. Moreover, double n-type doping via N and Al significantly alters the electronic structure of Al,N-containing GNRs. Our results suggest that selectively doped GNRs with pyridinic N can have enhanced Al-storage capacity and could be potentially used for selective Al electrosorption and removal. On the other hand, Al,N-containing GNRs with pyridinic N could also be used in resistive sensors for mechanical deformation. Namely, strain along the longitudinal axis of these dual doped GNRs does not affect the binding of Al but tunes the bandgap and causes more than 700-fold change in the conductivity. Thus, careful defect engineering and selective doping of GNRs with N (and Al) could lead to novel multifunctional materials with exceptional properties. [GRAPHICS]

Abstract: Air quality currently poses a major risk to human health worldwide. Transportation is one of the principal contributors to air pollution due to the quality of exhaust gases. For example, the widely used diesel fuel is a significant source of nitrogen oxides (NOx) and particulate matter (PM). To reduce the content NOx and PM, different oxygenated compounds were mixed into a mineral diesel available at the pump, and their effect on the composition of exhaust gas emissions was measured using a one-cylinder diesel generator. In this setup, adding methanol gave the best relative results. The addition of 2000 ppm of methanol decreased the content of NO by 56%, 2000 ppm of isopropanol decreased NO2 by 50%, and 2000 ppm ethanol decreased PM by 63%. An interesting question is whether it is possible to reduce the impact of hazardous components in the exhaust gas even more by adding oxygenates to biodiesels. In this article, alcohol is added to biodiesel in order to establish the impact on PM and NOx concentrations in the exhaust gases. Adding methanol, ethanol, and isopropanol at concentrations of 2000 ppm and 4000 ppm did not improve NOx emissions. The best results were using pure RME for a low NO content, pure diesel for a low NO2 content, and for PM there were no statistically significant differences.

Abstract: We derive a lumped circuit model for inductive antenna spin-wave transducers in the vicinity of a ferromagnetic medium. The model considers the antenna's Ohmic resistance, its inductance, as well as the additional inductance due to the excitation of ferromagnetic resonance or spin waves in the ferromagnetic medium. As an example, the additional inductance is discussed for a wire antenna on top of a ferromagnetic waveguide, a structure that is characteristic for many magnonic devices and experiments. The model is used to assess the scaling properties and the energy efficiency of inductive antennas. Issues related to scaling antenna transducers to the nanoscale and possible solutions are also addressed.

Abstract: Effective abatement of the greenhouse gas sulphur hexafluoride (SF6) waste is of great importance for the environment protection. This work investigates the size effect and the surface properties of gamma-Al2O3 pellets on SF6 degradation in a packed bed dielectric barrier discharge (PB-DBD) system. Experimental results show that decreasing the packing size improves the filamentary discharges and promotes the ignition and the maintenance of plasma, enhancing the degradation performance at low input powers. However, too small packing pellets decrease the gas residence time and reduce the degradation efficiency, especially for the input power beyond 80 W. Besides, lowering the packing size promotes the generation of SO2, while reduces the yields of S-O-F products, corresponding to a better degradation. After the discharge, the pellet surface becomes smoother with the appearance of S and F elements. Density functional theory calculations show that SF6 is likely to be adsorbed at the Al-III site over the gamma-Al2O3(110) surface, and it is much more easily to decompose than in the gas phase. The fluorine gaseous products can decompose and stably adsorb on the pellet surface to change the surface element composition. This work provides a better understanding of SF6 degradation in a PB-DBD system.

Abstract: Supershapes are used in Parametric Design to model, literally, thou-sands of natural and man-made shapes with a single 6 parameter formula. However, users are left to probe such a rich yet dense collection of supershapes using a set of independent 1-D sliders. Some of the formula’s parameters are non-linear in nature, making them particularly difficult to grasp with conventional 1-D sliders alone. VR appears as a promising setting for Parametric Design with supershapes since it empowers users with more natural visual inspection and shape browsing techniques, with multiple solutions being displayed at once and the possibility to design more interesting forms of slider interaction. In this work, we propose VR shape widgets that allow users to probe and select supershapes from a multitude of solutions. Our designs take leverage on thumbnails, mini-maps, haptic feedback and spatial interaction, while supporting 1-D, 2-D and 3-D supershape parameter spaces. We conducted a user study (N = 18) and found that VR shape widgets are effective, more efficient, and natural than conventional VR 1-D sliders while also usable for users without prior knowledge on supershapes. We also found that the proposed VR widgets provide a quick overview of the main supershapes, and users can easily reach the desired solution without having to perform fine-grain handle manipulations.

Abstract: One of the most basic criteria in documenting rangeland use prospects is the recognition of byproducts and their economic appraisal. The current study was conducted to assess the economic indices of exploiting byproduct production in Shahindej, Northwest Iran. For this purpose, 24 by-product-generating species were selected in 114 locations that belong to 49 rangeland units. The total expected value of 24 by-product generating species yield and forage production was calculated at 44.22 USD ha(-1). The results of this study showed that the sustainability of natural resources depends on the effective participation and empowerment of local communities. Furthermore, by-product exploitation contributes significantly to the local economy and employment while also reducing grazing intensity. Overall, the findings of this study show that by-product earnings should be considered in range management schemes and comprehensive natural-area management.