Abstract: The effect of pore size on plasma catalysis is crucial but still unclear. Studies have shown plasma cannot enter micropores and mesopores, so catalysts for traditional thermocatalysis may not fit plasma catalysis. Here, 3D porous Cu and CuO with different pore sizes were prepared using uniform silica particles (10–2000 nm) as templates, and compared in plasma-catalytic dry reforming. In most cases, the smaller the pore size, the higher the conversion of CH4 and CO2. Large pores reachable by more electrons did not improve the reaction efficiency. We attribute this to the small surface area and large crystallite size, as indicated by N2-sorption, mercury intrusion and XRD. While the smaller pores might not be reachable by electrons, due to the sheath formed in front of them, as predicted by modeling, they can still be reached by radicals formed in the plasma, and ions can even be attracted into these pores. An exception are the samples synthesized from 1 μm silica, which show better performance. We believe this is due to the electric field enhancement for pore sizes close to the Debye length. The performances of CuO and Cu with different pore sizes can provide references for future research on oxide supports and metal components of plasma catalysts.

Abstract: Heterogeneous photocatalysis can be used as an advanced oxidation technology frequently studied for application in photoreactors for air and water treatment. Extensive experimental investigation entails high costs and is also time consuming. Multiphysics modelling, a relatively new numerical method, provides a cost-effective and valuable alternative. By reconstructing the reactor geometry in dedicated software, meshing it and solving for occurring physical and chemical phenomena, Multiphysics models can be used to evaluate the performance of different reactor designs, increase insight into the occurring phenomena and study the influence of operational parameters on reactor performance. Finally, Multiphysics models are also developed for various applications like optimising the operational parameters, creating the ideal reactor design or scaling up a lab-scale reactor to a realistic prototype.

Abstract: Dual active sites from acidic zeolite and Pd are not only capable of catalyzing multiple type of reactions, but could also generate unique functions owing to the synergy between metals and acidic sites. However, there are only a few reports on the investigation of the synergy of acid/Pd dual sites in TS-1. Herein, TS-1 confined Pd catalyst with mesoporous silica shell (Pd@TS-1 @meso-SiO2) has been successfully synthesized and its synergy effect contributes to the enhanced conversion rate (19.2%) and selectivity (74.7%) on styrene oxidation. The interaction between Pd and TS-1 has been investigated by EPR and 1H NMR techniques, the experimental measurements show an obvious change in the signal distribution of weakly acidic terminal hydroxyls and hydrogen-bonding silanols. The schematic illustration of selective styrene oxidation in the model of Pd@TS-1 @meso-SiO2 is proposed to clarify the synergistic effect on styrene oxidation between TS-1 and Pd nanoparticles at an atomic-/nanoscale.

Abstract: The goal of this study is to provide a rigorous tool to quantify the inequality of the leaf size distribution of an individual plant, thereby serving as a reference trait for quantifying plant adaptations to local environmental conditions. The tool to be presented and tested employs three components: (1) a performance equation (PE), which can produce flexible asymmetrical and symmetrical bell-shaped curves, (2) the Lorenz curve (i.e., the cumulative proportion of leaf size vs. the cumulative proportion of number of leaves), which is the basis for calculating, and (3) the Gini index, which measures the inequality of leaf size distribution. We sampled 12 individual plants of a dwarf bamboo and measured the area and dry mass of each leaf of each plant. We then developed a generalized performance equation (GPE) of which the PE is a special case and fitted the Lorenz curve to leaf size distribution using the GPE and PE. The GPE performed better than the PE in fitting the Lorenz curve. We compared the Gini index of leaf area distribution with that of leaf dry mass distribution and found that there was a significant difference between the two indices that might emerge from the scaling relationship between leaf dry mass and area. Nevertheless, there was a strong correlation between the two Gini indices (r2 = 0.9846). This study provides a promising tool based on the GPE for quantifying the inequality of leaf size distributions across individual plants and can be used to quantify plant adaptations to local environmental conditions.

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: Purple phototrophic bacteria (PPB) show an underexplored potential for resource recovery from wastewater. Raceway reactors offer a more affordable full-scale solution on wastewater and enable useful additional aerobic processes. Current mathematical models of PPB systems provide useful mechanistic insights, but do not represent the full metabolic versatility of PPB and thus require further advancement to simulate the process for technology development and control. In this study, a new modelling approach for PPB that integrates the photoheterotrophic, and both anaerobic and aerobic chemoheterotrophic metabolic pathways through an empirical parallel metabolic growth constant was proposed. It aimed the modelling of microbial selection dynamics in competition with aerobic and anaerobic microbial community under different operational scenarios. A sensitivity analysis was carried out to identify the most influential parameters within the model and calibrate them based on experimental data. Process perturbation scenarios were simulated, which showed a good performance of the model.

Abstract: The colloidal synthesis of functional nanoparticles has gained tremendous scientific attention in the last decades. In parallel to these advancements, another rapidly growing area is the self-assembly or self-organization of these colloidal nanoparticles. First, the organization of nanoparticles into ordered structures is important for obtaining functional interfaces that extend or even amplify the intrinsic properties of the constituting nanoparticles at a larger scale. The synthesis of large-scale interfaces using complex or intricately designed nanostructures as building blocks, requires highly controllable self-assembly techniques down to the nanoscale. In certain cases, for example, when dealing with plasmonic nanoparticles, the assembly of the nanoparticles further enhances their properties by coupling phenomena. In other cases, the process of self-assembly itself is useful in the final application such as in sensing and drug delivery, amongst others. In view of the growing importance of this field, this review provides a comprehensive overview of the recent developments in the field of nanoparticle self-assembly and their applications. For clarity, the self-assembled nanostructures are classified into two broad categories: finite clusters/patterns, and infinite films. Different state-of-the-art techniques to obtain these nanostructures are discussed in detail, before discussing the applications where the self-assembly significantly enhances the performance of the process.

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: Natural deep eutectic solvents (NADES) show great promise as media for enzymatic reactions in areas where (bio)compatibility with natural or medicinal products is a must. While in theory they can be tailored to the intended reaction to ensure optimized yields, the knowledge to date is predominantly empirical, with some mechanistic reports providing a fragmented view at best. Therefore, it is not easy to explain experimental observations, let alone make predictions. The aim of this study was to develop a structured, holistic understanding of the effects of NADES media on enzymatic reactions, distinguishing between effects on solubility, solvation, viscosity, inhibition and denaturation. Experimental and computational chemistry methods were combined to separately study the interactions between enzyme, substrate, and NADES as reaction media. The initial enzyme activity and the final conversion of vinyl laurate transesterification by immobilized Candida antarctica lipase were studied experimentally. The direct effect of NADES on the same enzyme was modeled by molecular dynamics simulation. The effect of solubility was studied by both experimental and computational methods. To predict the solubility and viscosity of NADES, data-driven models were developed by combining group contribution and machine learning methods, based on the accumulated experimental knowledge on NADES found in the literature. Finally, the composed relationships and prediction models were applied to the practical example of deacetylation of mannosylerythritol lipids (MELs). The experimental findings show that the chosen NADES system has a significant effect on both the apparent initial activity and the final conversion. However, in the simulations, the enzyme retains its original structure; moreover, NADES has an additional stabilizing effect on the enzyme. In addition, changes in the molar ratio of the compounds in NADES do not show a significant effect on the stability of the enzyme. These results indicate that the main effect of NADES on the reaction is mainly related to the substrate-solvent interactions (solvation energy) and the viscosity of the system. On the other hand, the experimental results only confirmed the significance of solvation, viscosity did not show a clear correlation with the studied reaction parameters. The machine learning models built for solubility and viscosity gave quantitative predictions of these properties. The accumulated knowledge was used to optimize the yield in the deacetylation reaction of MELs. The combination of these methods provides fundamental knowledge about the effect of NADES on biocatalysis, but the results are also applicable to other uses of NADES.

Abstract: Methane (CH4) clathrate hydrates have gained much attention in the ever-growing search for novel energy storage methods; however, they are currently limited due to their poor water-to-hydrate conversions and slow formation kinetics. To surmount these bottlenecks, significant research has been centered on the design of novel methods (porous media). In this vein, the present work explores two hydrophobic mesoporous solids, an alkyl-grafted mesoporous silica (SBA-15 C8) and a periodic mesoporous organosilica (Ring-PMO), in their ability to promote CH4 clathrates. Both materials have shown to facilitate CH4 clathrate formation at mild operating conditions (6 MPa and 269–276 K). The study revealed that the maximal CH4 storage capacities are strongly linked to the critical/optimal quantity of water in the system which was determined to be at 130% and 200% of the pore volume for SBA-15 C8 and Ring-PMO, respectively. Up to 90% and 95% of the maximum water-to-hydrate conversions were achieved in 90 min at the lowest experimental temperature and critical water content for SBA-15 C8 and Ring-PMO, respectively. At these conditions, SBA-15 C8 and Ring-PMO showed a maximum gas uptake of 98.2 and 101.2 mmol CH4/mol H2O, respectively. Both the materials exhibited no chemical or morphological changes post-clathrate formations (characterized using FT-IR, N2 sorption, XRD, and TEM), inferring their viability as clathrate promoters for multiple cycles. An integrated multistep model was considered adequate for representing the hydrate crystallization kinetics and fits well with the experimental kinetic data with a low average absolute deviation in water-to-hydrate conversions among the three distinct kinetic models analyzed. Overall, the results from this study demonstrate hydrophobic porous materials as effective promoters of CH4 clathrates, which could make clathrate-based CH4 storage and transport technology industrially viable.

Abstract: To gain insights into the underlying mechanisms of NTP therapy sensitivity and resistance, using the firstever
NTP-resistant cell line derived from sensitive melanoma cells (A375).
Methods: Melanoma cells were exposed to NTP and re-cultured for 12 consecutive weeks before evaluation
against the parental control cells. Whole transcriptome sequencing analysis was performed to identify differentially
expressed genes and enriched molecular pathways. Glucose uptake, extracellular lactate, media acidification,
and mitochondrial respiration was analyzed to determine metabolic changes. Cell death inhibitors were
used to assess the NTP-induced cell death mechanisms, and apoptosis and ferroptosis was further validated via
Annexin V, Caspase 3/7, and lipid peroxidation analysis.
Results: Cells continuously exposed to NTP became 10 times more resistant to NTP compared to the parental cell
line of the same passage, based on their half-maximal inhibitory concentration (IC50). Sequencing and metabolic
analysis indicated that NTP-resistant cells had a preference towards aerobic glycolysis, while cell death analysis
revealed that NTP-resistant cells exhibited less apoptosis but were more vulnerable to lipid peroxidation and
ferroptosis.
Conclusions: A preference towards aerobic glycolysis and ferroptotic cell death are key physiological changes in
NTP-resistance cells, which opens new avenues for further, in-depth research into other cancer types.

Abstract: Electromagnetic design problems involve optimizing multiple parameters that are nonlinearly related to objective functions. Traditional optimization techniques require significant computational resources that grow exponentially as the problem size increases. Therefore, a method that can produce good results with moderate memory and computational resources is desirable. Bioinspired optimization methods, such as particle swarm optimization (PSO), are known for their computational efficiency and are commonly used in various scientific and technological fields. In this article we explore the potential of advanced PSO-based algorithms to tackle challenging electromagnetic design and analysis problems faced in real-life applications. It provides a detailed comparison between conventional PSO and its quantum-inspired version regarding accuracy and computational costs. Additionally, theoretical insights on convergence issues and sensitivity analysis on parameters influencing the stochastic process are reported. The utilization of a novel quantum PSO-based algorithm in advanced scenarios, such as reconfigurable and shaped lens antenna synthesis, is illustrated. The hybrid modeling approach, based on the unified geometrical description enabled by the Gielis Transformation, is applied in combination with a suitable quantum PSO-based algorithm, along with a geometrical tube tracing and physical optics technique for solving the inverse problem aimed at identifying the geometrical parameters that yield optimal antenna performance.

Abstract: Utilizing ammonia as a storage medium for hydrogen is currently receiving increased attention. A possible method to retrieve the hydrogen is by plasma-catalytic decomposition. In this work, we combined an experimental study, using a dielectric barrier discharge plasma reactor, with a plasma kinetic model, to get insights into the decomposition mechanism. The experimental results revealed a similar effect on the ammonia conversion when changing the flow rate and power, where increasing the specific energy input (higher power or lower flow rate) gave an increased conversion. A conversion as high as 82 % was achieved at a specific energy input of 18 kJ/Nl. Furthermore, when changing the discharge volume from 31 to 10 cm3, a change in the plasma distribution factor from 0.2 to 0.1 was needed in the model to best describe the conversions of the experiments. This means that a smaller plasma volume caused a higher transfer of energy through micro-discharges (non-uniform plasma), which was found to promote the decomposition of ammonia. These results indicate that it is the collisions between NH3 and the high-energy electrons that initiate the decomposition. Moreover, the rate of ammonia destruction was found by the model to be in the order of 1022 molecules/(cm3 s) during the micro-discharges, which is 5 to 6 orders of magnitude higher than in the afterglows. A considerable re-formation of ammonia was found to take place in the afterglows, limiting the overall conversion. In addition, the model revealed that implementation of packing material in the plasma introduced high concentrations of surface-bound hydrogen atoms, which introduced an additional ammonia re-formation pathway through an Eley-Rideal reaction with gas phase NH2. Furthermore, a more uniform plasma is predicted in the presence of MgAl2O4, which leads to a lower average electron energy during micro-discharges and a lower conversion (37 %) at a comparable residence time for the plasma alone (51 %).

Abstract: In this work, we have fabricatedan aryl amino-substitutedgraphiticcarbon nitride (g-C3N4) catalyst with atomicallydispersed Mn capable of generating hydrogen peroxide (H2O2) directly from seawater. This new catalyst exhibitedexcellent reactivity, obtaining up to 2230 & mu;M H2O2 in 7 h from alkaline water and up to 1800 & mu;Mfrom seawater under identical conditions. More importantly, the catalystwas quickly recovered for subsequent reuse without appreciable lossin performance. Interestingly, unlike the usual two-electron oxygenreduction reaction pathway, the generation of H2O2 was through a less common two-electron water oxidation reaction(WOR) process in which both the direct and indirect WOR processesoccurred; namely, photoinduced h(+) directly oxidized H2O to H2O2 via a one-step 2e(-) WOR, and photoinduced h(+) first oxidized a hydroxide (OH-) ion to generate a hydroxy radical ((OH)-O-& BULL;), and H2O2 was formed indirectly by thecombination of two (OH)-O-& BULL;. We have characterized thematerial, at the catalytic sites, at the atomic level using electronparamagnetic resonance, X-ray absorption near edge structure, extendedX-ray absorption fine structure, high-resolution transmission electronmicroscopy, X-ray photoelectron spectroscopy, magic-angle spinningsolid-state NMR spectroscopy, and multiscale molecular modeling, combiningclassical reactive molecular dynamics simulations and quantum chemistrycalculations.

Abstract: Many advanced nanomaterials rely on carefully designed morphology and elemental distribution to achieve their functionalities. Among the few experimental techniques that can directly visualise the 3D elemental distribution on the nanoscale are approaches based on electron tomography in combination with energy-dispersive X-ray spectroscopy (EDXS) and electron energy loss spectroscopy (EELS). Unfortunately, these highly informative methods are severely limited by the fundamentally low signal-to-noise ratio, which makes long experimental times and high electron irradiation doses necessary to obtain reliable 3D reconstructions. Addressing these limitations has been the major research question for the development of these techniques in recent years. This short review outlines the latest progress on the methods to reduce experimental time and electron irradiation dose requirements for 3D elemental distribution analysis and gives an outlook on the development of this field in the near future.