Abstract: The quantum anomalous Hall effect was first observed experimentally by doping the Bi2Se3 materials family with chromium, where 5% doping induces an exchange field of around 0.1 eV. In ultrathin films, a topological phase transition from a normal insulator to a Chern insulator can be induced with an exchange field proportional to the hybridization gap. Subsequent transitions to states with higher Chern numbers require an exchange field larger than the (bulk) band gap, but are prohibited in practice by the detrimental effects of higher doping levels. Here, we show that threshold doping for these phase transitions in thin films is controllable by strain. As a consequence, higher Chern states can be reached with experimentally feasible doping, sufficiently dilute for the topological insulator to remain structurally stable. Such a facilitated realization of higher Chern insulators opens prospects for multichannel quantum computing, higher-capacity circuit interconnects, and energy-efficient electronic devices at elevated temperatures.

Abstract: An unbiased photo-fuel cell (PFC) is a device that integrates the functions of a photoanode and a cathode to achieve simultaneous light-driven oxidation and dark reduction reactions. As such, it generates electricity while degrading pollutants like volatile organic compounds (VOCs). The photoanode is excited by light to generate electron-hole pairs, which give rise to a photocurrent, and are utilized to oxidise organic pollutants simultaneously. Here we have systematically studied various TiO2/WO3 photoanodes towards their photocatalytic soot degradation performance, PFC performance in the presence of VOCs, and the combination of both. The latter thus mimics an urban environment where VOCs and soot are present simultaneously. The formation of a type-II heterojunction after the addition of a thin TiO2 top layer over a dense WO3 bottom layer, improved both soot oxidation efficiency as well as photocurrent generation, thus paving the way towards low-cost PFC technology for energy recovery from real polluted air.

Abstract: Research efforts on the description of the low-temperature magnetic order and electronic properties of U3O8 have been inconclusive so far. Reinterpreting neutron scattering results, we use group representation theory to show that the ground state presents collinear out-of-plane magnetic moments, with antiferromagnetic coupling both in-layer and between layers. Charge order relieves the initial geometric frustration, generating a slightly distorted honeycomb sublattice with Néel-type order. The precise knowledge of the characteristics of this magnetic ground state is then used to explain the fine features of the band gap. In this system, spin-orbit coupling (SOC) is of critical importance, as it strongly affects the electronic structure, narrowing the gap by ∼38%, compared to calculations neglecting SOC. The predicted electronic structure actually explains the salient features of recent optical absorption measurements, further demonstrating the excellent agreement between the calculated ground state properties and experiment.

Abstract: In 2023, the European Union will vote on the reauthorization of glyphosate use, renewed in 2017 despite concern on impacts on the environment and public health. A ban is supported by several Member States but rejected by most farmers. What are citizens’ preferences to phase out glyphosate? To assess whether taxation could be an alternative to a ban, we conducted a discrete choice experiment in five European countries. Our results reveal that the general public is strongly willing to pay for a reduction in glyphosate use. However, while 75.5% of respondents stated to support a ban in the pre-experimental survey, experimental results reveal that in 73.35% of cases, earmarked taxation schemes are preferred when they lead to a strong reduction in glyphosate use for an increase in food price lower than that induced by a ban. When glyphosate reduction is balanced against its costs, a tax may be preferred.

Abstract: Morphological characterization of nanoparticle assemblies and hybrid nanomaterials is critical in determining their structure-property relationships as well as in the development of structures with desired properties. Electron tomography has become a widely utilized technique for the three-dimensional characterization of nanoparticle assemblies. However, the extraction of quantitative morphological parameters from the reconstructed volume can be a complex and labor-intensive task. In this study, we aim to overcome this challenge by automating the volumetric segmentation process applied to three-dimensional reconstructions of nanoparticle assemblies. The key to enabling automated characterization is to assess the performance of different volumetric segmentation methods in accurately extracting predefined quantitative descriptors for morphological characterization. In our methodology, we compare the quantitative descriptors obtained through manual segmentation with those obtained through automated segmentation methods, to evaluate their accuracy and effectiveness. To show generality, our study focuses on the characterization of assemblies of CdSe/CdS quantum dots, gold nanospheres and CdSe/CdS encapsulated in polymeric micelles, and silica-coated gold nanorods decorated with both CdSe/CdS or PbS quantum dots. We use two unsupervised segmentation algorithms: the watershed transform and the spherical Hough transform. Our results demonstrate that the choice of automated segmentation method is crucial for accurately extracting the predefined quantitative descriptors. Specifically, the spherical Hough transform exhibits superior performance in accurately extracting quantitative descriptors, such as particle size and interparticle distance, thereby allowing for an objective, efficient, and reliable volumetric segmentation of complex nanoparticle assemblies.

Abstract: This study presents new insights on the effect of (sub)micrometer particle sized materials in plasma-based CO2-
CH4 reforming by investigating the performance of SiO2 spheres (with/without supported metal) of varying
particle sizes. (Sub)micron particles synthesized through the St¨ober method were used instead of (sub)millimeter
particles employed in previous studies. Increasing particle size (from 120 nm to 2390 nm) was found to first
increase and then decrease conversion and energy yield, with optimal performance achieved using 740 nm 5 wt%
Ni loaded SiO2, which improved CO2 and CH4 conversion, and energy yield to 44%, 55%, and 0.271 mmol/kJ,
respectively, compared to 20%, 27%, and 0.116 mmol/kJ in an empty reactor at the same flow rate. This is the
first to achieve significant performance improvement in a fully packed reactor, highlighting the importance of
selecting a suitable particle size. The findings can offer guidance towards rational design of catalysts for plasmabased
reactions.

Abstract: Gold nanorods (Au NRs) are an exceptionally promising tool in nanotechnology due to three key factors: (i) their strong interaction with electromagnetic radiation, stemming from their plasmonic nature, (ii) the ease with which the resonance frequency of their longitudinal plasmon mode can be tuned from the visible to the near-infrared region of the electromagnetic spect r u m based on their aspect ratio, and (iii) their simple and cost-effective preparation through seed-mediated chemical growth. In this synthetic method, surfactants play a critical role in controlling the size, shape, and colloidal stabi l i t y of Au NRs. For example, surfactants can stabilize specific crystallographic facets during the formation of Au NRs, leading to t h e formation of NRs with specific morphologies. The process of surfactant adsorption onto the NR surface may result in various assemblies of surfactant molecules, such as spherical micelles, elongated micelles, or bilayers. Again, the assembly mode is critical toward determining the further availabi l i t y of the Au NR surface to the surrounding medium. Despite its importance and a great deal of research effort, the interaction between Au NPs and surfactants remains insufficiently understood, because the assembly process is influenced by numerous factors, including the chemical nature of the surfactant, the surface morphology of Au NPs, and solution parameters. Therefore, gaining a more comprehensive understanding of these interactions is essential to unlock the full potential of the seed-mediated growth method and the applications of plasmonic NPs. A plethora of characterization techniques have been applied to reach such an understanding , but many open questions remain. In this Account, we review the current knowledge on the interactions between surfactants and Au NRs. We briefly introduce the state-of-the-art methods for synthesizing Au NRs and highlight the crucial role of cationic surfactants during this process. The self-assembly and organization of surfactants on the Au NR surface is then discussed to better understand their role in seed-mediated growth. Subsequently, we provide examples and elucidate how chemical additives can be used to modulate micellar assemblies, in turn allowing for a finer control over the growth of Au NRs, including chiral NRs. Next, we review the main experimental characterization and computational modeling techniques that have been applied to shed light on the arrangement of surfactants on Au NRs and summarize the advantages and disadvantages for each technique. The Account ends with a “Conclusions and Outlook” section, outlining promising future research directions and developments that we consider are sti l l required, mostly related to the application of electron microscopy in liquid and in 3D. Finally, we remark on the potential of exploiting machine learning techniques to predict synthetic routes for NPs with predefined structures and properties.

Abstract: We have developed a sustainable method to produce NH3 directly from air using a plasma tandem-electrocatalysis system that operates via the N2−NOx−NH3 pathway. To efficiently reduce NO2− to NH3, we propose a novel electrocatalyst consisting of defective N-doped molybdenum sulfide nanosheets on vertical graphene arrays (N-MoS2/VGs). We used a plasma engraving process to form the metallic 1T phase, N doping, and S vacancies in the electrocatalyst simultaneously. Our system exhibited a remarkable NH3 production rate of 7.3 mg h−1 cm−2 at −0.53 V vs RHE, which is almost 100 times higher than the state-of-the-art electrochemical nitrogen reduction reaction and more than double that of other hybrid systems. Moreover, a low energy consumption of only 2.4 MJ molNH3−1 was achieved in this study. Density functional theory calculations revealed that S vacancies and doped N atoms play a dominant role in the selective reduction of NO2− to NH3. This study opens up new avenues for efficient NH3 production using cascade systems.

Abstract: A supersolid, a counterintuitive quantum state in which a rigid lattice of particles flows without resistance, has to date not been unambiguously realized. Here we reveal a supersolid ground state of excitons in a double-layer semiconductor heterostructure over a wide range of layer separations outside the focus of recent experiments. This supersolid conforms to the original Chester supersolid with one exciton per supersolid site, as distinct from the alternative version reported in cold-atom systems of a periodic density modulation or clustering of the superfluid. We provide the phase diagram augmented by the supersolid. This new phase appears at layer separations much smaller than the predicted exciton normal solid, and it persists up to a solid-solid transition where the quantum phase coherence collapses. The ranges of layer separations and exciton densities in our phase diagram are well within reach of the current experimental capabilities.

Abstract: Egg geometry can be described using Preston's equation, which has seldom been used to calculate egg volume (V) and surface area (S) to explore S versus V scaling relationships. Herein, we provide an explicit re-expression of Preston's equation (designated as EPE) to calculate V and S, assuming that an egg is a solid of revolution. The side (longitudinal) profiles of 2221 eggs of six avian species were digitized, and the EPE was used to describe each egg profile. The volumes of 486 eggs from two avian species predicted by the EPE were compared with those obtained using water displacement in graduated cylinders. There was no significant difference in V using the two methods, which verified the utility of the EPE and the hypothesis that eggs are solids of revolution. The data also indicated that V is proportional to the product of egg length (L) and maximum width (W) squared. A 2/3-power scaling relationship between S and V for each species was observed, that is, S is proportional to (LW2)(2/3). These results can be extended to describe the shapes of the eggs of other species to study the evolution of avian (and perhaps reptilian) eggs.

Abstract: We explore the influence of strain on the valley-polarized transmission of graphene by employing the wave-function matching and the non-equilibrium Green's function technique. When the transmission is along the armchair direction, we show that the valley polarization and transmission can be improved by increasing the width of the strained region and increasing (decreasing) the extensional strain in the armchair (zigzag) direction. It is noted that the shear strain does not affect transmission and valley polarization. Furthermore, when we consider the smooth strain barrier, the valley-polarized transmission can be enhanced by increasing the smoothness of the strain barrier. We hope that our finding can shed new light on constructing graphene-based valleytronic and quantum computing devices by solely employing strain.

Abstract: A wave-packet time evolution method, based on the split-operator technique, is developed to investigate the scattering of quasiparticles at a normal-superconductor interface of arbitrary profile and shape. As a practical application, we consider a system where low-energy electrons can be described as Dirac particles, which is the case for most two-dimensional materials, such as graphene and transition-metal dichalcogenides. However, the method is easily adapted for other cases such as electrons in few-layer black phosphorus or any Schrodinger quasiparticles within the effective mass approximation in semiconductors. We employ the method to revisit Andreev reflection in mono-, bi-, and trilayer graphene, where specular-and retro-reflection cases are observed for electrons scattered by a steplike superconducting region. The effect of opening a zero-gap channel across the superconducting region on the electron and hole scattering is also addressed, as an example of the versatility of the technique proposed here.

Abstract: The agri-food value chain is a major cause of nitrogen (N) and phosphorus (P) emissions and associated environmental and health impacts. The EU's farm-to-fork strategy (F2F) demands an agri-food value chain approach to reduce nutrient emissions by 50% and fertilizer use by 20%. Substance flow analysis (SFA) is a method that can be applied to study complex systems such as the agri-food chain. A review of 60 SFA studies shows that they often lack detail by not sufficiently distinguishing between nodes, products and types of emissions. The present study aims to assess the added value of detail in SFAs and to illustrate that valuable indicators can be derived from detailed assessments. This aim will be attained by presenting a highly-detailed SFA for the livestock-intensive region of Flanders, Belgium. The SFA distinguishes 40 nodes and 1827 flows that are classified into eight different categories (e.g. by-products, point source emissions) following life cycle methods. Eight novel indicators were calculated, including indicators that assess the N and P recovery potential. Flanders has a low overall nutrient use efficiency (11% N, 18% P). About 55% of the N and 56% of the P embedded in recoverable streams are reused providing 35% and 37% of the total N and P input. Optimized nutrient recycling could replace 45% of N and 48% of P of the external nutrient input, exceeding the target set by the F2F strategy. Detailed accounting for N and P flows and nodes leads to the identification of more recoverable streams and larger N and P flows. More detailed flow accounting is a prerequisite for the quantification of technological intervention options. Future research should focus on including concentration and quality as a parameter in SFAs.

Abstract: Screening drugs on the street and biological samples pose a challenge to law enforcement agencies due to existing detection methods and instrument limitations. Herein we present a graphene-assisted molecularly imprinted polymer nanoparticle-based sensor for amphetamine. These nanoparticles are electroactive by incorporating ferrocene in their structure. These particles act as specific actuators in electrochemical sensors, and the presence of a ferrocene redox probe embedded in the structure allows the detection of non-electroactive amphetamine. In a control approach, nanoparticles were covalently immobilised onto electrochemical sensors by drop-casting using silanes. Alternatively, nanoparticles were immobilised employing 3D printing and a graphene ink composite. The electrochemical performance of both approaches was evaluated. As a result, 3D printed nanoMIPs/graphene sensors displayed the highest selectivity in spiked human plasma, with sensitivity at 73 nA nM-1, LOD of 68 nM (RSD 2.4%) when compared to the silane drop cast electrodes. The main advantage of the optimised 3D printing technology is that it allows quantitative determination of amphetamine, a nonelectroactive drug, challenging to detect with conventional electrochemical sensors. In addition, the costefficient 3D printing method makes these sensors easy to manufacture, leading to robust, highly selective and sensitive sensors. As proof of concept, sensors were evaluated on the street specimens and clinically relevant samples and successfully validated using UPLC-MS.