Abstract: The penetration of reactive oxygen and nitrogen species (RONS) across the stratum corneum (SC) is a necessary and crucial process in many skin‐related plasma medical applications. To gain more insights into this penetration behavior, we combined experimental measurements of the permeability of dry and moist SC layers with computer simulations of model lipid membranes. We measured the permeation of relatively stable molecules, which are typically generated by plasma, namely H2O2, NO3−, and NO2−. Furthermore, we calculated the permeation free energy profiles of the major plasma‐generated RONS and their derivatives (i.e., H2O2, OH, HO2, O2, O3, NO, NO2, N2O4, HNO2, HNO3, NO2−, and NO3−) across native and oxidized SC lipid bilayers, to understand the mechanisms of RONS permeation across the SC. Our results indicate that hydrophobic RONS (i.e., NO, NO2, O2, O3, and N2O4) can translocate more easily across the SC lipid bilayer than hydrophilic RONS (i.e., H2O2, OH, HO2, HNO2, and HNO3) and ions (i.e., NO2− and NO3−) that experience much higher permeation barriers. The permeability of RONS through the SC skin lipids is enhanced when the skin is moist and the lipids are oxidized. These findings may help to understand the underlying mechanisms of plasma interaction with a biomaterial and to optimize the environmental parameters in practice in plasma medical applications.

Abstract: The autoregressive neural networks are emerging as a powerful computational tool to solve relevant problems in classical and quantum mechanics. One of their appealing functionalities is that, after they have learned a probability distribution from a dataset, they allow exact and efficient sampling of typical system configurations. Here we employ a neural autoregressive distribution estimator (NADE) to boost Markov chain Monte Carlo (MCMC) simulations of a paradigmatic classical model of spin-glass theory, namely, the two-dimensional Edwards-Anderson Hamiltonian. We show that a NADE can be trained to accurately mimic the Boltzmann distribution using unsupervised learning from system configurations generated using standard MCMC algorithms. The trained NADE is then employed as smart proposal distribution for the Metropolis-Hastings algorithm. This allows us to perform efficient MCMC simulations, which provide unbiased results even if the expectation value corresponding to the probability distribution learned by the NADE is not exact. Notably, we implement a sequential tempering procedure, whereby a NADE trained at a higher temperature is iteratively employed as proposal distribution in a MCMC simulation run at a slightly lower temperature. This allows one to efficiently simulate the spin-glass model even in the low-temperature regime, avoiding the divergent correlation times that plague MCMC simulations driven by local-update algorithms. Furthermore, we show that the NADE-driven simulations quickly sample ground-state configurations, paving the way to their future utilization to tackle binary optimization problems.

Abstract: The Darcy–Forchheimer method is used for modelling the airflow through vegetation. Seven tree and shrub species with contrasting leaf morphologies were installed in a wind tunnel to allow pressure loss measurements across the plant section. Aerodynamic parameters derived from this experiment were inserted into a COMSOL Multiphysics computational fluid dynamics model. The model was confirmed to be a good predictor for airflow through vegetation (R2 = 0.98), regardless of plant morphology. Moreover, supplementing these data with results from a previous study (which considered herbaceous species) revealed a pattern of pressure loss data, that was already been normalised for plant area density. Although we propose further research into kinetic energy transfer in vegetation, this study provides sufficient interesting information for further applications and modelling to describe and predict urban ecology.

Abstract: When approaching the atomically thin limit, defects and disorder play an increasingly important role in the properties of two-dimensional (2D) materials. While defects are generally thought to negatively affect superconductivity in 2D materials, here we demonstrate the contrary in the case of oxygenation of ultrathin tantalum disulfide (TaS2). Our first-principles calculations show that incorporation of oxygen into the TaS2 crystal lattice is energetically favorable and effectively heals sulfur vacancies typically present in these crystals, thus restoring the electronic band structure and the carrier density to the intrinsic characteristics of TaS2. Strikingly, this leads to a strong enhancement of the electron-phonon coupling, by up to 80% in the highly oxygenated limit. Using transport measurements on fresh and aged (oxygenated) few-layer TaS2, we found a marked increase of the superconducting critical temperature (T-c) upon aging, in agreement with our theory, while concurrent electron microscopy and electron-energy loss spectroscopy confirmed the presence of sulfur vacancies in freshly prepared TaS2 and incorporation of oxygen into the crystal lattice with time. Our work thus reveals the mechanism by which certain atomic-scale defects can be beneficial to superconductivity and opens a new route to engineer T-c in ultrathin materials.

Abstract: Blue energy converts the chemical potential difference from salinity gradients into electricity via reverse electrodialysis and provides a renewable source of clean energy. To achieve high energy conversion efficiency and power density, nanoporous membrane materials with both high ionic conductivity and ion selectivity are required. Here, we report ion transport through a network of holey-graphene-like sheets made by bottom-up polymerization. The resulting ultrathin membranes provide controlled pores of <10 angstrom in diameter with an estimated density of about 10(12) cm(-2). The pores' interior contains NH2 groups that become electrically charged with varying pH and allow tunable ion selectivity. Using the holey-graphene-like membranes, we demonstrate power outputs reaching hundreds of watts per square meter. The work shows a viable route toward creating membranes with high-density angstrom-scale pores, which can be used for energy generation, ion separation, and related technologies.

Abstract: Tapered specimens were used for an accelerated test technique to study the crack initiation of high Si stainless steel by means of constant elongation rate tensile testing in a simulated pressurised water reactor environment. Detailed crack density distributions were obtained by applying an advanced crack detection algorithm on iteratively displaced scanning electron microscopy pictures featuring stress corrosion cracks along the specimen's gauge length. By means of finite-element analysis, prominent peaks in the crack density graphs are demonstrated to be related to stress relief and stress build-up during the crack initiation phase. Intrinsic scatter related to the crack detection suggests that stress corrosion cracking is independent of the strain-rate for strain-rates lower than 10(-6 )s(-1). Based on the extrapolation to constant load conditions, the critical threshold value for the duplex high Si stainless steel is estimated to be around 580 MPa.

Abstract: Prolonged drought is considered as a creeping natural hazard, which has created a financial burden and unsustainable environment in Iran. Moreover, the effect of drought phenomenon in rural areas is more extensive, causing significant challenges to the rural economy in general and agricultural production in particular. A common strategy to manage drought is based on crisis management (ex-ante). However, for effective drought management, risk management seems to be more in line with drought early warning systems. This quantitative study used risk assessment, which is the function of two elements such as hazard (SPI and SDI indices) and vulnerability (exposure, sensitivity, and adaptive capacity). This study aims to build the foundations for drought early warning systems in limited resource areas such as Kermanshah Township in the northwestern part of Iran. The population of this study comprised of wheat farmers in which 293 farmers were selected using multistage cluster sampling method. In the next step, the drought risk map for Kermanshah Township was developed, which revealed that the majority of villages are at intense environmental risk. The result of this study has implications for drought management practitioners. For example, the results can aid policymakers in the design of an early warning system in order to reduce risk and thus empower farmers toward resilient farming.

Abstract: Polycyclic aromatic compounds such as acridine and phenazine are popular molecular partners used in cocrystal synthesis. The intermolecular interactions occurring between coformers and their molecular partners dominate the cocrystal packing energy, but coformer self-interactions might participate with a constant non-negligible contribution to the overall packing energy stabilization. Two new acridine-based cocrystals have been mechanochemically synthesized, then fully characterized<italic>via</italic>DSC and SCXRD analyses. A statistical analysis in the CSD has been performed to evaluate the recurrent π–π stacking orientation of polycyclic coformers in all deposited acridine-based cocrystals, then extended to phenazine-base analogs. Packing energy calculations were performed on a selected cocrystal subset to quantify the contribution of the π–π interaction to the overall stabilization energy.

Abstract: Ammonia is one of the most produced chemicals, mainly synthesized from fossil fuels for fertilizer applications. Furthermore, ammonia may be one of the energy carriers of the future, when it is produced from renewable electricity. This has spurred research on alternative technologies for green ammonia production. Research on plasma-driven ammonia synthesis has recently gained traction in academic literature. In the current review, we summarize the literature on plasma-driven ammonia synthesis. We distinguish between mechanisms for ammonia synthesis in the presence of a plasma, with and without a catalyst, for different plasma conditions. Strategies for catalyst design are discussed, as well as the current understanding regarding the potential plasma-catalyst synergies as function of the plasma conditions and their implications on energy efficiency. Finally, we discuss the limitations in currently reported models and experiments, as an outlook for research opportunities for further unravelling the complexities of plasma-catalytic ammonia synthesis, in order to bridge the gap between the currently reported models and experimental results.

Abstract: Using first-principles calculations, we study the effect of embedding various atoms into the nanopore sites of both C6N6 and C6N8 monolayers. Our results indicate that the embedded atoms significantly affect the electronic and magnetic properties of C6N6 and C6N8 monolayers and lead to extraordinary and multifarious electronic properties, such as metallic, half-metallic, spin-glass semiconductor and dilute-magnetic semiconductor behaviour. Our results reveal that the H atom concentration dramatically affects the C6N6 monolayer. On increasing the H coverage, the impurity states also increase due to H atoms around the Fermi-level. C6N6 shows metallic character when the H atom concentration reaches 6.25%. Moreover, the effect of charge on the electronic properties of both Cr@C6N6 and C@C6N8 is also studied. Cr@C6N6 is a ferromagnetic metal with a magnetic moment of 2.40 mu(B), and when 0.2 electrons are added and removed, it remains a ferromagnetic metal with a magnetic moment of 2.57 and 2.77 mu(B), respectively. Interestingly, one can observe a semi-metal, in which the VBM and CBM in both spin channels touch each other near the Fermi-level. C@C6N8 is a semiconductor with a nontrivial band gap. When 0.2 electrons are removed, it remains metallic, and under excess electronic charge, it exhibits half-metallic behaviour.

Abstract: Using first-principles calculations we systematically investigate the atomic, electronic and magnetic properties of novel two-dimensional materials (2DM) with a stoichiometry C3N which has recently been synthesized. We investigate how the number of layers affect the electronic properties by considering monolayer, bilayer and trilayer structures, with different stacking of the layers. We find that a transition from semiconducting to metallic character occurs which could offer potential applications in future nanoelectronic devices. We also study the affect of width of C3N nanoribbons, as well as the radius and length of C3N nanotubes, on the atomic, electronic and magnetic properties. Our results show that these properties can be modified depending on these dimensions, and depend markedly on the nature of the edge states. Functionalization of the nanostructures by the adsorption of H adatoms is found induce metallic, half-metallic, semiconducting and ferromagnetic behavior, which offers an approach to tailor the properties, as can the application of strain. Our calculations give insight into this new family of C3N nanostructures, which reveal unusual electronic and magnetic properties, and may have great potential in applications such as sensors, electronics and optoelectronic at the nanoscale.

Abstract: Branched plasmonic nanocrystals (NCs) have attracted much attention due to electric field enhancements at their tips. Seeded growth provides routes to NCs with defined branching patterns and, in turn, near-field distributions with defined symmetries. Here, a systematic analysis was undertaken in which seeds containing different distributions of planar defects were used to grow branched NCs in order to understand how their distributions direct the branching. Characterization of the products by multimode electron tomography and analysis of the NC morphologies at different overgrowth stages indicate that the branching patterns are directed by the seed defects, with the emergence of branches from the seed faces consistent with minimizing volumetric strain energy at the expense of surface energy. These results contrast with growth of branched NCs from single-crystalline seeds and provide a new platform for the synthesis of symmetrically branched plasmonic NCs.

Abstract: Ammonia is an industrial large-volume chemical, with its main application in fertilizer production. It also attracts increasing attention as a green-energy vector. Over the past century, ammonia production has been dominated by the Haber-Bosch process, in which a mixture of nitrogen and hydrogen gas is converted to ammonia at high temperatures and pressures. Haber-Bosch processes with natural gas as the source of hydrogen are responsible for a significant share of the global CO(2)emissions. Processes involving plasma are currently being investigated as an alternative for decentralized ammonia production powered by renewable energy sources. In this work, we present the PNOCRA process (plasma nitrogen oxidation and catalytic reduction to ammonia), combining plasma-assisted nitrogen oxidation and lean NO(x)trap technology, adopted from diesel-engine exhaust gas aftertreatment technology. PNOCRA achieves an energy requirement of 4.6 MJ mol(-1)NH(3), which is more than four times less than the state-of-the-art plasma-enabled ammonia synthesis from N(2)and H(2)with reasonable yield (>1 %).

Abstract: The use of fast pixelated detectors and direct electron detection technology is revolutionizing many aspects of scanning transmission electron microscopy (STEM). The widespread adoption of these new technologies is impeded by the technical challenges associated with them. These include issues related to hardware control, and the acquisition, real-time processing and visualization, and storage of data from such detectors. We discuss these problems and present software solutions for them, with a view to making the benefits of new detectors in the context of STEM more accessible. Throughout, we provide examples of the application of the technologies presented, using data from a Medipix3 direct electron detector. Most of our software are available under an open source licence, permitting transparency of the implemented algorithms, and allowing the community to freely use and further improve upon them.

Abstract: The photoelectrochemical quantification of phenolic compounds such as hydroquinone (HQ) and 4-aminophenol (4-AP) is accomplished by integrating a photoelectrochemical cell into a flow injection analysis (FIA) setup. It is a well-known fact that during the electroanalysis of phenolic compounds, the electrode surface is susceptible to poisoning. However, electrode fouling can be reduced significantly by using the FIA system with periodic washing of the electrode. Reactive oxygen species (ROS), which are generated on the surface of TiO2 under UV light, can oxidize phenolic compounds such as 4-AP. The oxidized form of 4-AP is reduced back at the electrode surface, generating a measurable signal proportional to its concentration. The factors influencing the perfor-mance of the sensor, such as flow rate, applied potential for back reduction and pH, are investigated in detail. In the concentration range 0.0125-1.0 mu M, a linear correlation between the photocurrent and the concentration of 4-AP was observed with a sensitivity of 0.6 A M-1 cm(-2) and a limit of detection of 18 nM. A straightforward analytical methodology for the on-site, highly sensitive and low-cost quantification of phenolic compounds is presented, based on the use of TiO2 in a photoelectrochemical flow cell.