Abstract: In nature, the two-dimensional (2D) profiles of fruits from many plants often resemble ellipses. However, it remains unclear whether these profiles strictly adhere to the ellipse equation, as many natural shapes resembling ellipses are actually better described as superellipses. The superellipse equation, which includes an additional parameter n compared to the ellipse equation, can generate a broader range of shapes, with the ellipse being just a special case of the superellipse. To investigate whether the 2D profiles of fruits are better described by ellipses or superellipses, we collected a total of 751 mature and undamaged fruits from 31 naturally growing plants of Cucumis melo L. var. agrestis Naud. Our analysis revealed that most adjusted root-mean-square errors (> 92% of the 751 fruits) for fitting the superellipse equation to the fruit profiles were consistently less than 0.0165. Furthermore, there were 638 of the 751 fruits (ca. 85%) with the 95% confidence intervals of the estimated parameter n in the superellipse equation not including 2. These findings suggest that the profiles of C. melo var. agrestis fruits align more closely with the superellipse equation than with the ellipse equation. This study provides evidence for the existence of the superellipse in fruit profiles, which has significant implications for studying fruit geometries and estimating fruit volumes using the solid of revolution formula. Furthermore, this discovery may contribute to a deeper understanding of the mechanisms driving the evolution of fruit shapes.

Abstract: Electrification and carbon capture technologies are essential for achieving net-zero emissions in the chemical sector. A crucial strategy involves converting captured CO2 into CO, a valuable chemical feedstock. This study evaluates the feasibility of two innovative methods: plasma activation and electrolysis, using clean electricity and captured CO2. Specifically, it compares a gliding arc plasma reactor with an embedded novel carbon bed system to a modern zero-gap type low-temperature electrolyser. The plasma method stood out with an energy cost of 19.5 GJ per tonne CO, marking a 43% reduction compared to electrolysis and conventional methods. CO production costs for plasma- and electrolysis-based plants were $671 and $962 per tonne, respectively. However, due to high uncertainty regarding electrolyser costs, the CO production costs in electrolysis-based plants may actually range from $570 to $1392 per tonne. The carbon bed system in the plasma method was a key factor in facilitating additional CO generation from O-2 and enhancing CO2 conversion, contributing to its cost-effectiveness. Challenges for electrolysis included high costs of equipment and low current densities. Addressing these limitations could significantly decrease production costs, but challenges arise from the mutual relationship between intrinsic parameters, such as CO2 conversion, CO2 input flow, or energy cost. In a future scenario with affordable feedstocks and equipment, costs could drop below $500 per tonne for both methods. While this may be more challenging for electrolysis due to complexity and expensive catalysts, plasma-based CO production appears more viable and competitive.

Abstract: Oxocarbons, known for over two centuries, have recently revealed a long-awaited facet: two-dimensional crystalline structures. Employing an intelligent global optimization algorithm (IGOA) alongside densityfunctional calculations, we unearthed a quasi -flat oxocarbon (C 6 0 6 ), featuring an oxygen -decorated hole, and a novel 3D-borocarbon. Comparative analyses with recently synthesized isostructures, such as 2D -porous carbon nitride (C 6 N 6 ) and 2D -porous boroxine (B 6 0 6 ), highlight the unique attributes of these compounds. All structures share a common stoichiometry of X 6 Y 6 (which we call COF-66), where X = B, C, and Y = B, N, O (with X not equal Y), exhibiting a 2D -crystalline structure, except for borocarbon C 6 B 6 , which forms a 3D crystal. In our comprehensive study, we conducted a detailed exploration of the electronic structure of X 6 Y 6 compounds, scrutinizing their thermodynamic properties and systematically evaluating phonon stability criteria. With expansive surface areas, diverse pore sizes, biocompatibility, pi-conjugation, and distinctive photoelectric properties, these structures, belonging to the covalent organic framework (COF) family, present enticing prospects for fundamental research and hold potential for biosensing applications.

Abstract: We have developed a comprehensive kinetic model to study the O atom kinetics in an O₂plasma and its afterglow. By adopting a pseudo-1D plug-flow formalism within the kinetic model, our aim is to assess how far the O atoms travel in the plasma afterglow, evaluating its potential as a source of O atoms for post-plasma gas conversion applications. Since we could not find experimental data for pure O₂plasma at atmospheric pressure, we first validated our model at low pressure (1–10 Torr) where very good experimental data are available. Good agreement between our model and experiments was achieved for the reduced electric field, gas temperature and the densities of the dominant neutral species, i.e. O₂(a), O₂(b) and O. Subsequently, we confirmed that the chemistry set is consistent with thermodynamic equilibrium calculations at atmospheric pressure. Finally, we investigated the O atom densities in the O₂plasma and its afterglow, for which we considered a microwave O₂plasma torch, operating at a pressure between 0.1 and 1 atm, for a flow rate of 20 slm and an specific energy input of 1656 kJ mol⁻¹. Our results show that for both pressure conditions, a high dissociation degree of ca. 92% is reached within the discharge. However, the O atoms travel much further in the plasma afterglow for<italic>p</italic>= 0.1 atm (9.7 cm) than for<italic>p</italic>= 1 atm (1.4 cm), attributed to the longer lifetime (3.8 ms at 0.1 atm vs 1.8 ms at 1 atm) resulting from slower three-body recombination kinetics, as well as a higher volumetric flow rate.

Abstract: The evolution of the uranium chemical state in uranium compounds, principally in the oxides, is of concern in the context of nuclear fuel degradation under storage and repository conditions, and in accident scenarios. The U–O system shows complicated phase relations between single-valence uranium dioxide (UO₂) and different mixed-valence compounds (<italic>e.g.</italic>U₄O₉, U₃O₇and U₃O₈). To try resolving the electronic structure associated with unique atomic positions, a combined application of diffraction and spectroscopic techniques, such as diffraction anomalous fine structure (DAFS), can be considered. Reported here is the application of two newly developed routines for assessing a DAFS data set, with the aim of refining the uranium X-ray dispersion corrections. High-resolution anomalous diffraction data were acquired from polycrystalline powder samples of UO₂(containing tetravalent uranium) and potassium uranate (KUO₃, containing pentavalent uranium) using synchrotron radiation in the vicinity of the U<italic>L</italic>₃edge (17.17 keV). Both routines are based on an iterative refinement of the dispersion corrections, but they differ in either using the intensity of a selection of reflections or doing a full-pattern (Rietveld method) refinement. The uranium dispersion corrections obtained using either method are in excellent agreement with each other, and they show in great detail the chemical shifts and differences in fine structure expected for tetravalent and pentavalent uranium. This approach may open new possibilities for the assessment of other, more complicated, materials such as mixed-valence compounds. Additionally, the DAFS methodology can offer a significant resource optimization because each data set contains both structural (diffraction) and chemical (spectroscopy) information, which can avoid the requirement to use multiple experimental stations at synchrotron sources.

Abstract: Seminal Goodenough-Kanamori-Anderson (GKA) rules provide an inceptive understanding of the superexchange interaction of two magnetic metal ions bridged with an anion, and suggest fostered ferromagnetic interaction for orthogonal bridging bonds. However, there are no examples of two-dimensional (2D) materials with structure that optimizes the GKA arguments towards enhanced ferromagnetism and its critical temperature. Here we reveal that an ideally planar GKA ferromagnetism is indeed stable in selected tetragonal transition-metal xenes (tTMXs), with Curie temperature above 300 K found in CrC and MnC. We provide the general orbitally-resolved analysis of magnetic interactions that supports the claims and sheds light at the mechanisms dominating the magnetic exchange process in these structures. Furthermore, we propose the set of three GKA-like rules that will guarantee room temperature ferromagetnism. With recent advent of epitaxially-grown tetragonal 2D materials, our findings earmark tTMXs for facilitated spintronic and magnonic applications, or as a desirable magnetic constituent of functional 2D heterostructures.

Abstract: In this study, we conducted a systematic density functional theory (DFT) investigation of the interaction between Ti3C2-MXene monolayer and biological molecules dopamine (DA) and serine (Ser) as neurotransmitter and amino acid, respectively. Our calculations show good agreement with previous literature findings for the optimized Ti3C2 monolayer. We found that DA and Ser molecules bind to the Ti3C2 surface with adsorption energies of -2.244 eV and -3.960 eV, respectively. The adsorption of Ser resulted in the dissociation of one H atom. Electronic density of states analyses revealed little changes in the electronic properties of the Ti3C2-MXene monolayer upon adsorption of the biomolecules. We further investigated the interaction of DA and Ser with Ti3C2 monolayers featuring surface -termination with OH functional group, and Ti -vacancy. Our calculations indicate that the adsorption energies significantly decrease in the presence of surface termination, with adsorption energies of -0.097 eV and -0.330 eV for DA and Ser, respectively. Adsorption energies on the Ti -vacancy surface, on the other hand, are calculated to be -3.584 eV and -3.856 eV for DA and Ser, respectively. Our results provide insights into the adsorption behavior of biological molecules on Ti3C2-MXene, demonstrating the potential of this material for biosensing and other biomedical applications. These findings highlight the importance of surface modifications in the development of functional materials and devices based on Ti3C2-MXene, and pave the way for future investigations into the use of 2D materials for biomedical applications.

Abstract: A thorough and quantitative understanding of the fate of excitons in covalent–organic frameworks (COFs) after photoexcitation is essential for their augmented optoelectronic and photocatalytic applications via precise structure tuning. The synthesis of a library of COFs having identical chemical backbone with impeded conjugation, but varied morphology and surface topography to study the effect of these physical properties on the photophysics of the materials is herein reported. The variation of crystallite size and surface topography substantified different aggregation pattern in the COFs, which leads to disparities in their photoexcitation and relaxation properties. Depending on aggregation, an inverse correlation between bulk luminescence decay time and exciton binding energy of the materials is perceived. Further transient absorption spectroscopic analysis confirms the presence of highly localized, immobile, Frenkel excitons (of diameter 0.3–0.5 nm) via an absence of annihilation at high density, most likely induced by structural torsion of the COF skeletons, which in turn preferentially relaxes via long‐lived (nanosecond to microsecond) excimer formation (in femtosecond scale) over direct emission. These insights underpin the importance of structural and topological design of COFs for their targeted use in photocatalysis.

Abstract: The structure-property relationship at interfaces is difficult to probe for thermoelectric materials with a complex interfacial microstructure. Designing thermoelectric materials with a simple, structurally-uniform interface provides a facile way to understand how these interfaces influence the transport properties. Here, we synthesized Bi2-xSbxTe3 (x = 0, 0.1, 0.2, 0.4) nanoflakes using a hydrothermal method, and prepared Bi2-xSbxTe3 thin films with predominantly (0001) interfaces by stacking the nanoflakes through spin coating. The influence of the annealing temperature and Sb content on the (0001) interface structure was systematically investigated at atomic scale using aberration-corrected scanning transmission electron microscopy. Annealing and Sb doping facilitate atom diffusion and migration between adjacent nanoflakes along the (0001) interface. As such it enhances interfacial connectivity and improves the electrical transport properties. Interfac reactions create new interfaces that increase the scattering and the Seebeck coefficient. Due to the simultaneous optimization of electrical conductivity and Seebeck coefficient, the maximum power factor of the Bi1.8Sb0.2Te3 nanoflake films reaches 1.72 mW m(-1) K-2, which is 43% higher than that of a pure Bi2Te3 thin film.

Abstract: Despite the recent promising potential of plasma-based nitrogen fixation, the technology faces significant challenges in efficient upscaling. To tackle this challenge, we investigate two reactors, i.e., a small one, operating in a flow rate range of 5-20 ln min-1 and current range of 200-500 mA, and a larger one, operating at higher flow rate (100-300 ln min-1) and current (400-1000 mA). Both reactors operate in a pin-to-pin configuration and are powered by direct current (DC) from the same power supply unit, to allow easy comparison and evaluate the effect of upscaling. In the small reactor, we achieve the lowest energy cost (EC) of 2.8 MJ mol-1, for a NOx concentration of 1.72%, at a flow rate of 20 ln min-1, yielding a production rate (PR) of 33 g h-1. These values are obtained in air; in oxygen-enriched air, the results are typically better, at the cost of producing oxygen-enriched air. In the large reactor, the higher flow rates reduce the NOx concentration due to lower SEI, while maintaining a similar EC. This stresses the important effect of the geometrical configuration of the arc, which is typically concentrated in the center of the reactor, resulting in limited coverage of the reacting gas flow, and this is identified as the limiting factor for upscaling. However, our experiments reveal that by changing the reactor configuration, and thus the plasma geometry and power deposition mechanisms, the amount of gas treated by the plasma can be enhanced, leading to successful upscaling. To obtain more insights in our experiments, we performed thermodynamic equilibrium calculations. First of all, they show that our measured lowest EC closely aligns with the calculated minimum thermodynamic equilibrium at atmospheric pressure. In addition, they reveal that the limited NOx production in the large reactor results from the contracted nature of the plasma. To solve this limitation, we let the large reactor operate in so-called torch configuration. Indeed, the latter enhances the NOx concentrations compared to the pin-to-pin configuration, yielding a PR of 80 g h-1 at an EC of 2.9 MJ mol-1 and NOx concentration of 0.31%. This illustrates the importance of reactor design in upscaling. With the focus on feasibility evaluation of scaling-up plasma-based nitrogen fixation by combined experiments and thermodynamic modelling, we aim to tackle the challenge of design and development of an energy-efficient and scaled-up plasma reactor.

Abstract: Plasma medicine has attracted tremendous interest in a variety of medical conditions, ranging from wound healing to antimicrobial applications, even in cancer treatment, through the interactions of cold atmospheric plasma (CAP) and various biological tissues directly or indirectly. The underlying mechanisms of CAP treatment are still poorly understood although the oxidative effects of CAP with amino acids, peptides, and proteins have been explored experimentally. In this study, machine learning (ML) technology is introduced to efficiently unveil the interaction mechanisms of amino acids and reactive oxygen species (ROS) in seconds based on the data obtained from the reactive molecular dynamics (MD) simulations, which are performed to probe the interaction of five types of amino acids with various ROS on the timescale of hundreds of picoseconds but with the huge computational load of several days. The oxidative reactions typically start with H-abstraction, and the details of the breaking and formation of chemical bonds are revealed; the modification types, such as nitrosylation, hydroxylation, and carbonylation, can be observed. The dose effects of ROS are also investigated by varying the number of ROS in the simulation box, indicating agreement with the experimental observation. To overcome the limits of timescales and the size of molecular systems in reactive MD simulations, a deep neural network (DNN) with five hidden layers is constructed according to the reaction data and employed to predict the type of oxidative modification and the probability of occurrence only in seconds as the dose of ROS varies. The well-trained DNN can effectively and accurately predict the oxidative processes and productions, which greatly improves the computational efficiency by almost ten orders of magnitude compared with the reactive MD simulation. This study shows the great potential of ML technology to efficiently unveil the underpinning mechanisms in plasma medicine based on the data from reactive MD simulations or experimental measurements. In this study, since reactive molecular dynamics simulation can currently only describe interactions between a few hundred atoms in a few hundred picoseconds, deep neural networks (DNN) are introduced to enhance the simulation results by predicting more data efficiently. image

Abstract: Plasma‐based CO₂conversion has attracted increasing interest. However, to understand the impact of plasma operation on post‐plasma processes, we studied the effect of adding N₂, N₂/CH₄and N₂/CH₄/H₂O to a CO₂gliding arc plasmatron (GAP) to obtain valuable insights into their impact on exhaust stream composition and temperature, which will serve as feed gas and heat for post‐plasma catalysis (PPC). Adding N₂improves the CO₂conversion from 4 % to 13 %, and CH₄addition further promotes it to 44 %, and even to 61 % at lower gas flow rate (6 L/min), allowing a higher yield of CO and hydrogen for PPC. The addition of H₂O, however, reduces the CO₂conversion from 55 % to 22 %, but it also lowers the energy cost, from 5.8 to 3 kJ/L. Regarding the temperature at 4.9 cm post‐plasma, N₂addition increases the temperature, while the CO₂/CH₄ratio has no significant effect on temperature. We also calculated the temperature distribution with computational fluid dynamics simulations. The obtained temperature profiles (both experimental and calculated) show a decreasing trend with distance to the exhaust and provide insights in where to position a PPC bed.

Abstract: We investigate the intralayer correlations acting within the layers in a superfluid system of electron -hole spatially separated layers. In this system, superfluidity is predicted to be almost exclusively confined to the Bose-Einstein condensate (BEC) and crossover regimes where the electron -hole pairs are well localized. In this case, Hartree-Fock is an excellent approximation for the intralayer correlations. We find in the BEC regime that the effect of the intralayer correlations on superfluid properties is negligible but in the BCS-BEC crossover regime the superfluid gap is significantly weakened by the intralayer correlations. This is caused by the intralayer correlations boosting the number of low -energy particle -hole excitations that drive the screening. We further find that the intralayer correlations suppress the predicted phenomenon in which the average pair size passes through a minimum as the crossover regime is traversed.

Abstract: The interplay between a magnetic field and the Coulomb potential from a charged vacancy on the electron states in graphene is investigated within the tight-binding model. The Coulomb potential removes locally Landau level degeneracy, while the vacancy introduces a satellite level next to the normal Landau level. These satellite levels are found throughout the positive-energy region, but in the negative-energy region, they turn into atomic collapse resonances. Crossings between Landau levels with different angular quantum number m are found. Unlike the point impurity system in which an anticrossing occurs between Landau levels of the same m, in this work anticrossing is found between the normal Landau level and the vacancy-induced level. The atomic collapse resonance hybridizes with the Landau levels. The charge at which the lowest Landau level m = -1, N = 1 crosses E = 0 increases with enhancing magnetic field. A Landau level scaling anomaly occurs when the charge is larger than the critical charge beta 0.6 and this critical charge is independent of the magnetic field.

Abstract: We assessed the impact of road disturbances on the dominant mycorrhizal types in ecosystems at the global level and how this mechanism can potentially lead to lasting plant community changes. We used a database of coordinated plant community surveys following mountain roads from 894 plots in 11 mountain regions across the globe in combination with an existing database of mycorrhizal-plant associations in order to approximate the relative abundance of mycorrhizal types in natural and disturbed environments. Our findings show that roadside disturbance promotes the cover of plants associated with arbuscular mycorrhizal (AM) fungi. This effect is especially strong in colder mountain environments and in mountain regions where plant communities are dominated by ectomycorrhizal (EcM) or ericoid-mycorrhizal (ErM) associations. Furthermore, non-native plant species, which we confirmed to be mostly AM plants, are more successful in environments dominated by AM associations. These biogeographical patterns suggest that changes in mycorrhizal types could be a crucial factor in the worldwide impact of anthropogenic disturbances on mountain ecosystems. Indeed, roadsides foster AM-dominated systems, where AM-fungi might aid AM-associated plant species while potentially reducing the biotic resistance against invasive non-native species, often also associated with AM networks. Restoration efforts in mountain ecosystems will have to contend with changes in the fundamental make-up of EcM- and ErM plant communities induced by roadside disturbance.