Abstract: In this letter, a dipole sheet method is proposed to theoretically study the adsorption and decomposition of C5F10O over-discharged Cu (111) and Al (111) surfaces. A synergistic effect of external electric fields and surface excess charges shows up for jointly promoting the adsorption of C5F10O, accompanied by the enhancement of C-F bond elongation and charge transfer process. The decomposition of C5F10O is facilitated in the discharged region and the initial decomposition is found most likely to occur via the cleavage of the C-F single bond. The results indicate that the decomposition of C5F10O over the metal electrode surfaces is much accelerated when discharge faults occur and free F atoms could be generated from C5F10O before its carbon chain breakage. These findings help to elucidate the underlying decomposition tendency of C5F10O in discharged systems and provide a practical method for evaluating and designing new insulation gases.

Abstract: This study investigates farmers' preferences and willingness to pay for cropland attributes in Bahir Dar, north-west Ethiopia. A choice experiment is used to elicit farmers' preferences between different land use attributes, including a monetary attribute. The study was conducted in the croplands that are threatened by land expro-priation for urban expansion. A survey was undertaken with 144 farmers in four rural kebeles surrounding the city (Addis Alem, Weramit, Wereb and Zenzelima). In the survey, respondents were provided with hypothetical land purchasing decisions, with three alternatives (i.e., two hypothetical parcels and an opt-out option). A choice experiment was undertaken to measure farmers' interest in different types of croplands, which varies with respect to irrigability, number of trees per ha, soil erosion resistance and water holding capacity of the cropland. Estimation of two mixed logit models was carried out. The estimation results show that, although the farmers did not show strong preferences for each attribute of the cropland, many farmers in the area showed interest in the proposed alternative croplands. Farmers show more interest for the land that is irrigable, gentle slope and with medium water holding capacity. The results also indicate that farmers assign highest marginal willingness to pay (MWTP) (79.01 ETB per square meter) for irrigated land, followed by medium water holding capacity with MWTP of 52.13 ETB per square meter. We believe that the results of this study would help land use policy and decision makers in the study area to consider the various attributes of cropland in land use planning, including land expropriation programs, which assures the sustainability of ecosystem services.

Abstract: This work reports the use of modified screen-printed carbon electrodes (SPCEs) for the identification of three drugs of abuse and two habitual cutting agents, caffeine and paracetamol, combining voltammetric sensing and chemometrics. In order to achieve this goal, codeine, heroin and morphine were subjected to Square Wave Voltammetry (SWV) at pH 7, in order to elucidate their electrochemical fingerprints. The optimized SPCEs electrode array, which have a differentiated response for the three oxidizable compounds, was derived from Carbon, Prussian blue, Cobalt (II) phthalocyanine, Copper (II) oxide, Polypyrrole and Palladium nanoparticles ink-modified carbon electrodes. Finally, Principal Component Analysis (PCA) coupled with Silhouette parameter assessment was used to select the most suitable combination of sensors for identification of drugs of abuse in presence of cutting agents.

Abstract: The shape of leaf laminae exhibits considerable diversity and complexity that reflects adaptations to environmental factors such as ambient light and precipitation as well as phyletic legacy. Many leaves appear to be elliptical which may represent a ‘default’ developmental condition. However, whether their geometry truly conforms to the ellipse equation (EE), i.e., (x/a)2 + (y/b)2 = 1, remains conjectural. One alternative is described by the superellipse equation (SE), a generalized version of EE, i.e., |x/a|n +|y/b|n = 1. To test the efficacy of EE versus SE to describe leaf geometry, the leaf shapes of two Michelia species (i.e., M. cavaleriei var. platypetala, and M. maudiae), were investigated using 60 leaves from each species. Analysis shows that the majority of leaves (118 out of 120) had adjusted root-mean-square errors of < 0.05 for the nonlinear fitting of SE to leaf geometry, i.e., the mean absolute deviation from the polar point to leaf marginal points was smaller than 5% of the radius of a hypothesized circle with its area equaling leaf area. The estimates of n for the two species were ˂ 2, indicating that all sampled leaves conformed to SE and not to EE. This study confirms the existence of SE in leaves, linking this to its potential functional advantages, particularly the possible influence of leaf shape on hydraulic conductance.

Abstract: The number and composition of species in a community can be quantified with alpha-diversity indices, including species richness (R), Simpson's index (D), and the Shannon-Wiener index (HGREEK TONOS). In forest communities, there are large variations in tree size among species and individuals of the same species, which result in differences in ecological processes and ecosystem functions. However, tree size inequality (TSI) has been largely neglected in studies using the available diversity indices. The TSI in the diameter at breast height (DBH) data for each of 999 20 m x 20 m forest census quadrats was quantified using the Gini index (GI), a measure of the inequality of size distribution. The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat. We also examined the relationships of alpha-diversity indices with the GI using correlation tests. The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions, with most root-mean-square errors (990 out of 999 quadrats) being < 0.0030. There were significant positive correlations between each of three alpha-diversity indices (i.e., R, D, and H') and the GI. Nevertheless, the total abundance of trees in each quadrat did not significantly influence the GI. This means that the TSI increased with increasing species diversity. Thus, two new indices are proposed that can balance alpha-diversity against the extent of TSI in the community: (1 – GI) x D, and (1 – GI) x H'. These new indices were significantly correlated with the original D and HGREEK TONOS, and did not increase the extent of variation within each group of indices. This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities, especially in the face of cumulative species loss under global climate change.

Abstract: The evaluation of nucleation rates from molecular dynamics trajectories is hampered by the slow nucleation time scale and impact of finite size effects. Here, we show that accurate nucleation rates can be obtained in a very general fashion relying only on the free energy barrier, transition state theory, and a simple dynamical correction for diffusive recrossing. In this setup, the time scale problem is overcome by using enhanced sampling methods, in casu metadynamics, whereas the impact of finite size effects can be naturally circumvented by reconstructing the free energy surface from an appropriate ensemble. Approximations from classical nucleation theory are avoided. We demonstrate the accuracy of the approach by calculating macroscopic rates of droplet nucleation from argon vapor, spanning 16 orders of magnitude and in excellent agreement with literature results, all from simulations of very small (512 atom) systems.

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: More and more countries and organisations emphasise the value of harm reduction measures in the context of illicit drug use and abuse. One of these measures is drug checking, a preventive action that can represent a quick win by tailored consultation on the risks of substance use upon analytical screening of a submitted sample. Unlike drop-in centres that operate within a fixed setting, enabling drug checking in a harm reduction context at events requires portable, easy to use analytical approaches, operated by personnel with limited knowledge of analytical chemistry. In this case study, four different approaches were compared for the characterisation of 3,4-methylenedioxymethamphetamine samples and this in the way the approaches would be applied today in an event context. The four approaches are mid-infrared (MIR), near-infrared, and Raman spectroscopy, which are today used in drug checking context in Belgium, as well as an electrochemical sensor approach initially developed in the context of law enforcement at ports. The MIR and the electrochemical approach came out best, with the latter allowing for a direct straightforward analysis of the percentage 3,4-methylenedioxymethamphetamine (as base equivalent) in the samples. However, MIR has the advantage that, in a broader drug checking context, it allows to screen for several molecules and so is able to identify unexpected active components or at least the group to which such components belong. The latter is also an important advantage in the context of the growing emergence of new psychotropic substances. MIR, NIR, Raman spectroscopy, and an electrochemical sensor (Narcoreader (R)) for MDMA analysis were compared in a realistic harm reduction context. NIR and Raman failed in simple library approaches. MIR and Narcoreader (R) were preferred. MIR came out as first choice. MIR and Narcoreader (R) have complementary (dis)advantages and could be used in a two-step approach: MIR for screening and Narcoreader (R) for dosage/risk evaluation of MDMA samples.image

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.

Abstract: Energy-autonomous sewage treatment can be achieved if nitrogen (N) removal does not rely on organic carbon (∼chemical oxygen demand, COD), so that a maximum of the COD can be redirected to energy recovery. Shortcut N removal technologies such as partial nitritation/anammox and nitritation/denitritation are therefore essential, enabling carbon- and energy-lean nitrogen removal. In this study, a novel three-reactor pilot design was tested and consisted of a denitrification, an intermittent aeration, and an anammox tank. A vibrating sieve was added for differential sludge retention time (SRT) control. The 13 m3 pilot was operated on pre-treated sewage (A-stage effluent) at 12–24 °C. Selective suppression of unwanted nitrite-oxidizing bacteria over aerobic ammonium-oxidizing bacteria was achieved with strict floccular SRT management combined with innovative aeration control, resulting in a minimal nitrate production ratio of 17 ± 10%. Additionally, anoxic ammonium-oxidizing bacteria (AnAOB) activity could be maintained in the reactor for at least 150 days because of long granular SRT management and the anammox tank. Consequently, the COD/N removal ratio of 2.3 ± 0.7 demonstrated shortcut N removal almost three times lower than the currently applied nitrification/denitrification technology. The effluent total N concentrations of 17 ± 3 mg TN per L (at 21 ± 1 °C) and 17 ± 6 mg TN per L (at 15 ± 1 °C) were however too high for application at the sewage treatment plant Nieuwveer (Breda, The Netherlands). Corresponding N removal efficiencies were 52 ± 12% and 37 ± 21%, respectively. Further development should focus on redirecting more nitrite to AnAOB in the B-stage, exploring effluent-polishing options, or cycling nitrate for increased A-stage denitrification.

Abstract: Particulate matter (PM) deposition on urban green enables the collection of particulate pollution from a diversity of contexts, and insight into the physico-chemical profiles of PM is key for identifying main polluting sources. This study reports on the morphological and elemental characterization of PM2-10 deposited on ivy leaves from five different environments (forest, rural, roadside, train, industry) in the region of Antwerp, Belgium. Ca. 40,000 leaf-deposited particles were thoroughly investigated by particle-based analysis using scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM/EDX) and their physico-chemical characteristics were explored for PM source apportionment purposes. The size distribution of all deposited particles was biased towards small-sized PM, with 32% of the particles smaller than 2.5 mu m (PM2.5) and median diameters of 2.80-3.09 mu m. The source type influenced both the particles' size and morphology (aspect ratio and shape), with roadside particles being overall the smallest in size and the most spherical. While forest and rural elemental profiles were associated with natural PM, the industry particles revealed the highest anthropogenic metal input. PM2-10 profiles for roadside and train sites were rather comparable and only distinguishable when evaluating the fine (2-2.5 mu m) and coarse (2.5-10 mu m) PM fractions separately, which enabled the identification of a larger contribution of combustion-derived particles (small, circular, Fe-enriched) at the roadside compared to the train. Random forest prediction model classified the source type correctly for 61-85% of the leaf-deposited PM. The still modest classification accuracy denotes the influence of regional background PM and demands for additional fingerprinting techniques to facilitate source apportionment. Nonetheless, the obtained results demonstrate the utility of leaf particle-based analysis to fingerprint and pinpoint source-specific PM, particularly when considering both the composition and size of leaf-deposited particles.

Abstract: Forensic drug laboratories are confronted with increasing amounts of drugs and a demand for faster results that are directly available on-site. In addition, the drug market is getting more complex with hundreds of new psychoactive substances (NPS) entering the market in recent years. Rapid and on-scene presumptive drug testing therefore faces a shift from manual colorimetric tests towards approaches that can detect a wider range of components and process results automatically. Electrochemical detection offers these desired characteristics, making it a suitable candidate for on-site drug detection. In this study, a two-step electrochemical sensor is introduced for the detection of MDMA and 2C-B. Firstly, a direct electrochemical analysis was performed to detect MDMA. Validation experiments on over 70 substances revealed that 2C-B was the only frequently encountered drug that gave a false positive result for MDMA in this first analysis. A second step using in-situ derivatization was subsequently introduced. To this end, formaldehyde was used for N-methylation of 2C-B thereby enhancing its electrochemical profile. The enriched electrochemical fingerprint in the second step allowed for clear differentiation between MDMA and 2C-B. The applicability of this approach was demonstrated with 71 ecstasy tablets seized by the Amsterdam Police. The MDMA/2C-B sensor correctly identified all 39 MDMA-containing tablets and 10 out of 11 tablets containing 2C-B. Most notably, correct results were also obtained for dark colored tablets in which both spectroscopic analysis and colorimetric tests failed due to obscured signals.

Abstract: Preston's equation is a general model describing the egg shape of birds. The parameters of Preston's equation are usually estimated after re-expressing it as the Todd-Smart equation and scaling the egg's actual length to two. This method assumes that the straight line through the two points on an egg's profile separated by the maximum distance (i.e., the longest axis of an egg's profile) is the mid-line. It hypothesizes that the photographed egg's profile is perfectly bilaterally symmetrical, which seldom holds true because of photographic errors and placement errors. The existing parameter estimation method for Preston's equation considers an angle of deviation for the longest axis of an egg's profile from the mid-line, which decreases prediction errors to a certain degree. Nevertheless, this method cannot provide an accurate estimate of the coordinates of the egg's center, and it leads to sub-optimal parameter estimation. Thus, it is better to account for the possible asymmetry between the two sides of an egg's profile along its mid-line when fitting egg-shape data. In this paper, we propose a method based on the optimization algorithm (optimPE) to fit egg-shape data and better estimate the parameters of Preston's equation by automatically searching for the optimal mid-line of an egg's profile and testing its validity using profiles of 59 bird eggs spanning a wide range of existing egg shapes. We further compared this method with the existing one based on multiple linear regression (lmPE). This study demonstrated the ability of the optimPE method to estimate numerical values of the parameters of Preston's equation and provide the theoretical egg length (i.e., the distance between two ends of the mid-line of an egg's profile) and the egg's maximum breadth. This provides a valuable approach for comparing egg shapes among conspecifics or across different species, or even different classes (e.g., birds and reptiles), in future investigations.

Abstract: High-performance rechargeable batteries are becoming very important for high-end technologies with their ever increasing application areas. Hence, improving the performance of such batteries has become the main bottleneck to transferring high-end technologies to end users. In this study, we propose an argon intercalation strategy to enhance battery performance via engineering the interlayer spacing of honeycomb structures such as graphite, a common electrode material in lithium-ion batteries (LIBs). Herein, we systematically investigated the LIB performance of graphite and hexagonal boron nitride (h-BN) when argon atoms were sent into between their layers by using first-principles density-functional-theory calculations. Our results showed enhanced lithium binding for graphite and h-BN structures when argon atoms were intercalated. The increased interlayer space doubles the gravimetric lithium capacity for graphite, while the volumetric capacity also increased by around 20% even though the volume was also increased. The ab initio molecular dynamics simulations indicate the thermal stability of such graphite structures against any structural transformation and Li release. The nudged-elastic-band calculations showed that the migration energy barriers were drastically lowered, which promises fast charging capability for batteries containing graphite electrodes. Although a similar level of battery promise was not achieved for h-BN material, its enhanced battery capabilities by argon intercalation also support that the argon intercalation strategy can be a viable route to enhance such honeycomb battery electrodes.

Abstract: When studying paintings with active infrared thermography (IRT), minimizing the temperature fluctuations and thermal shock during a measurement becomes important. Under these conditions, it might be beneficial to use lock-in thermography instead of the conventionally used pulse thermography (PT). This study compared the observations made with lock-in thermography (LIT) and pulse phase thermography (PPT) with halogen light excitation. Three distinctly different paintings were examined. The LIT measurements caused smaller temperature fluctuations and, overall, the phase images appeared to have a higher contrast and less noise. However, in the PPT phase images, the upper paint layer was less visible, an aspect which is of particular interest when trying to observe subsurface defects or the structure of the support. The influence of the spectral range of the cameras on the results was also investigated. All measurements were taken with a mid-wave infrared (MWIR) and long wave infrared (LWIR) camera. The results show that there is a significant number of direct reflection artifacts, caused by the use of the halogen light sources when using the MWIR camera. Adding a long-pass filter to the MWIR camera eliminated most of these artifacts. All results are presented in a side-by-side comparison.