Abstract: The recent energy crisis revealed that there is a strong need to replace hydrocarbon-fueled industrial nitrogen fixation processes by alternative, more sustainable methods. In light of this, plasma-based nitrogen fixation remains one of the most promising options, considering both theoretical and experimental aspects. Lately, plasma interacting with water has received considerable attention in nitrogen fixation applications as it can trigger a unique gas- and liquid-phase chemistry. Within this context, a critical exploration of plasma-assisted nitrogen fixation with or without water presence is of great interest with an emphasis on energy costs, particularly in plasma reactors which have potential for large-scale industrial application. In this work, the presence of water in a multi-pin plasma system on nitrogen oxidation is experimentally investigated by comparing two pulsed negative DC voltage plasmas in metal–metal and metal–liquid electrode configurations. The plasma setups are designed to create similar plasma properties, including plasma power and discharge regime in both configurations. The system energy cost is calculated, considering nitrogen-containing species generated in gas and liquid phases as measured by a gas analyzer, nitrate sensor, and a colorimetry method. The energy cost profile as a function of specific energy input showed a strong dependency on the plasma operational frequency and the gas flow rate, as a result of different plasma operation regimes and initiated reverse processes. More importantly, the presence of the plasma/liquid interface increased the energy cost up to 14 ± 8%. Overall, the results showed that the presence of water in the reaction zone has a negative impact on the nitrogen fixation process.

Abstract: Air quality currently poses a major risk for human health. Currently, diesel is widely used as fuel and is a significant source of nitrogen oxides (NOx) and particulate matter (PM), both hazardous to human health. A good alternative for mineral diesel is biodiesel, not only for the improvement of hazardous components in the exhaust gases but also because it can be produced in view of a circular economy. Biodiesel consists of a mix of different fatty acid methyl esters, which can react with oxygen. As a consequence, the oxidation stability of biodiesel has to be studied, because the oxidation of biodiesel could affect the performance of the engine due to the wear of injectors and fuel pumps. The oxidation stability could also affect the quality of the exhaust gases due to increases in NOx and PM. The basic question we try to answer in this communication is: 'Can we find an optimal fatty acid composition in order to have a maximal oxidation stability?' In this article, we try to find the optimal fatty acid composition according to the five most common fatty acid methyl esters present in biodiesel in order to reach a maximal oxidation stability. The measurements and statistical analysis show, however, that there is no useful regression model because there are statistically significant two- and three-way interactions among the different fatty acids.

Abstract: Silicon-based materials are attractive for thermoelectric applications due to their thermal stability, chemical inertness, and natural abundance of silicon. Here, using a combination of first-principles and Boltzmann transport calculations we report the thermoelectric properties of the recently synthesized compound Mg3Si2Te6. Our analysis reveals that Mg3Si2Te6 is a direct bandgap semiconductor with a bandgap of 1.6 eV. The combination of heavy and light valence bands, along with a high valley degeneracy, results in a large power factor under p-type doping. We also find that Mg is weakly bonded both within and between the layers, leading to low phonon group velocities. The vibrations of the Mg atoms are localized and make a significant contribution to phonon-phonon scattering. This high anharmonicity, coupled with low phonon group velocity, results in a low lattice thermal conductivity of & kappa;(l) = 0.5 W m(-1) K-1 at room temperature, along the cross-plane direction. Combining excellent electronic transport properties and low & kappa;(l), p-type Mg3Si2Te6 achieves figure-of-merit (zT) values greater than 1 at temperatures above 600 K. Specifically, a zT of 2.0 is found at 900 K along the cross-plane direction. Our findings highlight the importance of structural complexity and chemical bonding in electronic and phonon transport, providing guiding insights for further design of Si-based thermoelectrics.

Abstract: Hydrogen (H2) storage, in the form of clathrate hydrates, has emerged as an attractive alternative to classical storage methods like compression or liquefaction. Nevertheless, the sluggish enclathration kinetics along with low gas storage capacities in bulk systems is currently impeding the progress of this technology. To this end, unstirred systems coupled with porous materials have been shown to tackle the aforementioned drawbacks. In line with this approach, the present study explores the use of hydrophobic periodic organosilica nanoparticles, later denoted as hollow ring-PMO (HRPMO), for H2 storage as clathrate hydrates under mild operating conditions (5.56 mol% THF, 7 MPa, and 265–273 K). The surface of the HRPMO nanoparticles was carefully decorated/functionalized with THF-like moieties, which are well-known promoter agents in clathrate formation when applied in classical, homogeneous systems. The study showed that, while the non-functionalized HRPMO can facilitate the formation of binary H2-THF clathrates, the incorporation of surface-bound promotor structures enhances this process. More intriguingly, tuning the concentration of these surface-bound promotor agents on the HRPMO led to a notable effect on solid-state H2 storage capacities. An increase of 3% in H2 storage capacity, equivalent to 0.26 wt%, along with a substantial increase of up to 28% in clathrate growth kinetics, was observed when an optimal loading of 0.14 mmol g−1 of promoter agent was integrated into the HRPMO framework. Overall, the findings from this study highlight that such tuning effects in the solid-state have the potential to significantly boost hydrate formation/growth kinetics and H2 storage capacities, thereby opening new avenues for the ongoing development of H2 clathrates in industrial applications.

Abstract: In the last decades, non-thermal plasma has been extensively investigated as a relevant tool for various biomedical applications, ranging from tissue decontamination to regeneration and from skin treatment to tumor therapies. This high versatility is due to the different kinds and amount of reactive oxygen and nitrogen species that can be generated during a plasma treatment and put in contact with the biological target. Some recent studies report that solutions of biopolymers with the ability to generate hydrogels, when treated with plasma, can enhance the generation of reactive species and influence their stability, resulting thus in the ideal media for indirect treatments of biological targets. The direct effects of the plasma treatment on the structure of biopolymers in water solution, as well as the chemical mechanisms responsible for the enhanced generation of RONS, are not yet fully understood. In this study, we aim at filling this gap by investigating, on the one hand, the nature and extent of the modifications induced by plasma treatment in alginate solutions, and, on the other hand, at using this information to explain the mechanisms responsible for the enhanced generation of reactive species as a consequence of the treatment. The approach we use is twofold: (i) investigating the effects of plasma treatment on alginate solutions, by size exclusion chromatography, rheology and scanning electron microscopy and (ii) study of a molecular model (glucuronate) sharing its chemical structure, by chromatography coupled with mass spectrometry and by molecular dynamics simulations. Our results point out the active role of the biopolymer chemistry during direct plasma treatment. Short-lived reactive species, such as OH radicals and O atoms, can modify the polymer structure, affecting its functional groups and causing partial fragmentation. Some of these chemical modifications, like the generation of organic peroxide, are likely responsible for the secondary generation of long-lived reactive species such as hydrogen peroxide and nitrite ions. This is relevant in view of using biocompatible hydrogels as vehicles for storage and delivery reactive species for targeted therapies.

Abstract: LNMO (LiNi0.5Mn1.5O4-delta) is a high-energy density positive electrode material for lithium ion batteries. Unfortunately, it suffers from capacity loss and impedance rise during cycling due to electrolyte oxidation and electrode/electrolyte interface instabilities at high operating voltages. Here, a solution-gel synthesis route was used to coat 0.5-2.5 mu m LNMO particles with amorphous Li-Ti-O (LTO) for improved Li conduction, surface structural stability and cyclability. High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) analysis coupled with energy dispersive X-ray (EDX) showed Ti-rich amorphous coatings/islands or Ti-rich spinel layers on many of the LTO-modified LNMO facets, with a thickness varying from about 1 to 10 nm. The surface modification in the form of amorphous islands was mostly possible on high-energy crystal facets. Physicochemical observations were used to propose a molecular mechanism for the surface modification, combining insights from metalorganic chemistry with the crystallographic properties of LNMO. The improvements in functional properties were investigated in half cells. The cell impedance increased faster for the bare LNMO compared to amorphous LTO modified LNMO, resulting in R-ct values as high as 1247 Omega (after 1000 cycles) for bare LNMO, against 216 Omega for the modified material. At 10C, the modified material boosted a 15% increase in average discharge capacity. The improvements in electrochemical performance were attributed to the increase in electrochemically active surface area, as well as to improved HF-scavenging, resulting in the formation of protective byproducts, generating a more stable interface during prolonged cycling.

Abstract: Electron energy loss spectroscopy (EELS) is a well established technique in electron microscopy that yields information on the elemental content of a sample in a very direct manner. One of the persisting limitations of EELS is the requirement for manual identification of core-loss edges and their corresponding elements. This can be especially bothersome in spectrum imaging, where a large amount of spectra are recorded when spatially scanning over a sample area. This paper introduces a synthetic dataset with 736,000 labeled EELS spectra, computed from available generalized oscillator strength tables, that represents 107 K, L, M or N core-loss edges and 80 chemical elements. Generic lifetime broadened peaks are used to mimic the fine structure due to band structure effects present in experimental core-loss edges. The proposed dataset is used to train and evaluate a series of neural network architectures, being a multilayer perceptron, a convolutional neural network, a U-Net, a residual neural network, a vision transformer and a compact convolutional transformer. An ensemble of neural networks is used to further increase performance. The ensemble network is used to demonstrate fully automated elemental mapping in a spectrum image, both by directly mapping the predicted elemental content and by using the predicted content as input for a physical model-based mapping.

Abstract: The dehydrogenation of long-chain alkanes to olefins and alkylaromatics is a challenging endothermic reaction, typically requiring harsh conditions which can lead to low selectivity and coking. More favorable thermodynamics can be achieved by using a hydrogen acceptor, such as ethylene. In this work, the potential of heterogeneous platinum catalysts for the transfer dehydrogenation of long-chain alkanes is investigated, using ethylene as a convenient hydrogen acceptor. Pt/C and Pt–Sn/C catalysts were prepared<italic>via</italic>a simple polyol method and characterized with CO pulse chemisorption, HAADF-STEM, and EDX measurements. Conversion of ethylene was monitored<italic>via</italic>gas-phase FTIR, and distribution of liquid products was analyzed<italic>via</italic>GC-FID, GC-MS, and 1H-NMR. Compared to unpromoted Pt/C, Sn-promoted catalysts show lower initial reaction rates, but better resistance to catalyst deactivation, while increasing selectivity towards alkylaromatics. Both reaction products and ethylene were found to inhibit the reaction significantly. At 250 °C for 22 h, TON up to 28 and 86 mol per mol Pt were obtained for Pt/C and PtSn₂/C, respectively, with olefin selectivities of 94% and 53%. The remaining products were mainly unbranched alkylaromatics. These findings show the potential of simple heterogeneous catalysts in alkane transfer dehydrogenation, for the preparation of valuable olefins and alkylaromatics, or as an essential step in various tandem reactions.

Abstract: Understanding chemical reactivity and magnetism of 3<italic>d</italic>transition metal nanoparticles is of fundamental interest for applications in fields ranging from spintronics to catalysis. Here, we present an atomistic picture of the early stage of the oxidation mechanism and its impact on the magnetism of Co nanoparticles. Our experiments reveal a two-step process characterized by (i) the initial formation of small CoO crystallites across the nanoparticle surface, until their coalescence leads to structural completion of the oxide shell passivating the metallic core; (ii) progressive conversion of the CoO shell to Co₃O₄and void formation due to the nanoscale Kirkendall effect. The Co nanoparticles remain highly reactive toward oxygen during phase (i), demonstrating the absence of a pressure gap whereby a low reactivity at low pressures is postulated. Our results provide an important benchmark for the development of theoretical models for the chemical reactivity in catalysis and magnetism during metal oxidation at the nanoscale.

Abstract: Topochemistry enables step-by-step conversions of solid-state materials often leading to metastable structures that retain initial structural motifs. Recent advances in this field revealed many examples where relatively bulky anionic constituents were actively involved in redox reactions during (de)intercalation processes. Such reactions are often accompanied by anion-anion bond formation, which heralds possibilities to design novel structure types disparate from known precursors, in a controlled manner. Here we present the multistep conversion of layered oxychalcogenides Sr(2)MnO(2)Cu(1.5)Ch(2) (Ch=S, Se) into Cu-deintercalated phases where antifluorite type [Cu(1.5)Ch(2)](2.5-) slabs collapsed into two-dimensional arrays of chalcogen dimers. The collapse of the chalcogenide layers on deintercalation led to various stacking types of Sr(2)MnO(2)Ch(2) slabs, which formed polychalcogenide structures unattainable by conventional high-temperature syntheses. Anion-redox topochemistry is demonstrated to be of interest not only for electrochemical applications but also as a means to design complex layered architectures. Low temperature chemical transformations of solids using high-energy intermediates have enabled the synthesis of a new series of layered oxide chalcogenide containing oxidised chalcogenide dimers promising a new range of solids.

Abstract: Recent experiments demonstrated that proton transport through graphene electrodes can be accelerated by over an order of magnitude with low intensity illumination. Here we show that this photo-effect can be suppressed for a tuneable fraction of the infra-red spectrum by applying a voltage bias. Using photocurrent measurements and Raman spectroscopy, we show that such fraction can be selected by tuning the Fermi energy of electrons in graphene with a bias, a phenomenon controlled by Pauli blocking of photo-excited electrons. These findings demonstrate a dependence between graphene's electronic and proton transport properties and provide fundamental insights into molecularly thin electrode-electrolyte interfaces and their interaction with light. Recent experiments have shown that proton transport through graphene electrodes can be promoted by light, but the understanding of this phenomenon remains unclear. Here, the authors report the electrical tunability of this photo-effect, showing a connection between graphene electronic and proton transport properties.

Abstract: Farmers should increasingly adopt more water‐efficient irrigation technologies—such as drip irrigation—as a result of climate warming and aggravating water scarcity. We analyze how Italian farmers adapt to climate change by changing their irrigation technology mix. We apply a two‐stage econometric model to data from 5876 Italian farms. We find that farmers' initial reaction to increasing temperatures is reducing their surface‐irrigated fractions. When temperatures increase further, farmers switch toward more sprinkler irrigation. Our results show that farmers are not autonomously moving to drip irrigation in response to climate change, suggesting that government incentives are needed to encourage this transition.

Abstract: Cluster beam deposition is employed for fabricating well-defined bimetallic plasmonic photocatalysts to enhance their activity while facilitating a more fundamental understanding of their properties. AuxAg1-x clusters with compositions (x = 0, 0.1, 0.3, 0.5, 0.7, 0.9 and 1) spanning the metals' miscibility range were produced in the gas-phase and soft-landed on TiO2 P25-coated silicon wafers with an optimal coverage of 4 atomic monolayer equivalents. Electron microscopy images show that at this coverage most clusters remain well dispersed whereas EXAFS data are in agreement with the finding that the deposited clusters have an average size of ca. 5 nm and feature the same composition as the ablated alloy targets. A composition-dependant electron transfer from Au to Ag that is likely to impart chemical stability to the bimetallic clusters and protect Ag atoms against oxidation is additionally evidenced by XPS and XANES. Under simulated solar light, AuxAg1-x clusters show a remarkable composition-dependent volcano-type enhancement of their photocatalytic activity towards degradation of stearic acid, a model compound for organic fouling on surfaces. The Formal Quantum Efficiency (FQE) is peaking at the Au0.3Ag0.7 composition with a value that is twice as high as that of the pristine TiO2 P25 under solar simulator. Under UV the FQE of all compositions remains similar to that of pristine TiO2. A classical electromagnetic simulation study confirms that among all compositions Au0.3Ag0.7 features the largest near-field enhancement in the wavelength range of maximal solar light intensity, as well as sufficient individual photon energy resulting in a better photocatalytic self-cleaning activity. This allows ascribing the mechanism for photocatalysis mostly to the plasmonic effect of the bimetallic clusters through direct electron injection and near-field enhancement from the resonant cluster towards the conduction band of TiO2. These results not only demonstrate the added value of using well-defined bimetallic nanocatalysts to enhance their photocatalytic activity but also highlights the potential of the cluster beam deposition to design tailored noble metal modified photocatalytic surfaces with controlled compositions and sizes without involving potentially hazardous chemical agents.

Abstract: Two-dimensional materials (2DMs) continue to attract a lot of attention, particularly for their extreme flexibility and superior thermal properties. Molecular dynamics simulations are among the most powerful methods for computing these properties, but their reliability depends on the accuracy of interatomic interactions. While first principles approaches provide the most accurate description of interatomic forces, they are computationally expensive. In contrast, classical force fields are computationally efficient, but have limited accuracy in interatomic force description. Machine learning interatomic potentials, such as Gaussian Approximation Potentials, trained on density functional theory (DFT) calculations offer a compromise by providing both accurate estimation and computational efficiency. In this work, we present a systematic procedure to develop Gaussian approximation potentials for selected 2DMs, graphene, buckled silicene, and h-XN (X = B, Al, and Ga, as binary compounds) structures. We validate our approach through calculations that require various levels of accuracy in interatomic interactions. The calculated phonon dispersion curves and lattice thermal conductivity, obtained through harmonic and anharmonic force constants (including fourth order) are in excellent agreement with DFT results. HIPHIVE calculations, in which the generated GAP potentials were used to compute higher-order force constants instead of DFT, demonstrated the first-principles level accuracy of the potentials for interatomic force description. Molecular dynamics simulations based on phonon density of states calculations, which agree closely with DFT-based calculations, also show the success of the generated potentials in high-temperature simulations.

Abstract: Electron tomography is a widely used technique for 3D structural analysis of nanomaterials, but it can cause damage to samples due to high electron doses and long exposure times. To minimize such damage, researchers often reduce beam exposure by acquiring fewer projections through tilt undersampling. However, this approach can also introduce reconstruction artifacts due to insufficient sampling. Therefore, it is important to determine the optimal number of projections that minimizes both beam exposure and undersampling artifacts for accurate reconstructions of beam-sensitive samples. Current methods for determining this optimal number of projections involve acquiring and post-processing multiple reconstructions with different numbers of projections, which can be time-consuming and requires multiple samples due to sample damage. To improve this process, we propose a protocol that combines golden ratio scanning and quasi-3D reconstruction to estimate the optimal number of projections in real-time during a single acquisition. This protocol was validated using simulated and realistic nanoparticles, and was successfully applied to reconstruct two beam-sensitive metal–organic framework complexes.