Abstract: Ruddlesden-Popper La????Sr2−????MnO4−???? materials are interesting symmetric solid oxide
fuel cell electrodes due to their good redox stability, mixed ionic and electronic conducting behavior and thermal expansion that matches well with common electrolytes. In reducing environments – as at a solid oxide fuel cell anode – the x = 0.5 member, i.e. La0.5Sr1.5MnO4−????, has a much higher total conductivity than compounds with a different La/Sr ratio, although all those compositions have the same K2NiF4-type I4/mmm structure. The origin for this conductivity difference is not yet known in literature. Now, a combination of in-situ and ex-situ 3D electron diffraction, high-resolution imaging, energy-dispersive X-ray analysis and electron energy-loss spectroscopy uncovered clear differences between x=0.25 and x=0.5 in the pristine structure, as well as in the transformations upon high-temperature reduction. In La0.5Sr1.5MnO4−????, Ruddlesden-Popper n=2 layer defects and an amorphous surface layer are present, but not in La0.25Sr1.75MnO4−????. After annealing at 700°C in 5% H2/Ar, La0.25Sr1.75MnO4−???? transforms to a tetragonal 2D incommensurately modulated structure with modulation vectors ⃗????1 = 0.2848(1) · (⃗????* +⃗????*) and ⃗????2 =0.2848(1) · (⃗????* – ⃗????*), whereas La0.5Sr1.5MnO4−???? only partially transforms to an orthorhombic 1D incommensurately modulated structure,
with ⃗???? = 0.318(2) · ⃗????*. Perovskite domains grow at the crystal edge at 700°C in 5%
H2 or vacuum, due to the higher La concentration on the surface compared to the bulk, which leads to a different thermodynamic equilibrium. Since it is known that a lower degree of oxygen vacancy ordering and a higher amount of perovskite blocks enhance oxygen mobility, those differences in defect structure and structural transformation upon reduction, might all contribute to the higher conductivity of La0.5Sr1.5MnO4−???? in solid oxide fuel cell anode conditions compared to other La/Sr ratios.

Abstract: This study investigates the distribution of ultrasound (US) energy in a batch system for solutions with viscosity ranging from 1 to approximately 3000 mPas. Sonication was performed using horn type configurations operating at 20-30 kHz and rated power capacity of 50 or 200 W. Two different tip diameters (3 or 7 mm) and two insertion depths (35 or 25 mm) within vessels of different sizes ( approximate to 60 or 130 ml) were utilized. Additionally, a special conical tip design was employed. For each experimental setup, the calorimetric efficiency was estimated, the cavitationally active regions were visualized using the sonochemiluminescence (SCL) method and bubble cluster formation inside the vessel was macroscopically observed using a high speed camera (HSC). In the viscosity range tested, the calorimetry results showed that the efficiency and continuous operation of the device depend on both the rated power and the horn tip diameter. The ratio between electrical and calorimetric power input remained consistently around 40 to 50% across the different configurations for water, but for the 123.2 mPas solution exhibited significant variation ranging from 40 to 85%. Moreover, the power density in the smaller reactor was found to be nearly double compared to the larger one. The SCL analysis showed multiple cavitationally active zones in all setups, and the zones intensity decreased considerably with increase of the solutions viscosity. The results for the cone tip were not conclusive, but can be used as the basis for further investigation. The current research highlights the importance of thoroughly understanding the impact of each design parameter, and of establishing characterization methodologies to assist in the future development of scaled-up, commercial applications.

Abstract: The reduction of carbon dioxide (CO2) using porphyrin-containing 2D covalent organic frameworks (2D-COFs) catalysts is widely explored nowadays. While these framework materials are normally fabricated as powders followed by their uncontrolled surface heterogenization or directly grown as thin films (thickness >200 nm), very little is known about the performance of substrate-supported single-layered (approximate to 0.5 nm thickness) 2D-COFs films (s2D-COFs) due to its highly challenging synthesis and characterization protocols. In this work, a fast and straightforward fabrication method of porphyrin-containing s2D-COFs is demonstrated, which allows their extensive high-resolution visualization via scanning tunneling microscopy (STM) in liquid conditions with the support of STM simulations. The as-prepared single-layered film is then employed as a cathode for the electrochemical reduction of CO2. Fe porphyrin-containing s2D-COF@graphite used as a single-layered heterogeneous catalyst provided moderate-to-high carbon monoxide selectivity (82%) and partial CO current density (5.1 mA cm(-2)). This work establishes the value of using single-layered films as heterogene ous catalysts and demonstrates the possibility of achieving high performance in CO2 reduction even with extremely low catalyst loadings.

Abstract: The objective of this paper is to examine the recycling rates for mechanical and thermochemical recycling of postconsumer polyethylene flexible packaging after the implementation of different policy instruments. The study uses a supply chain equilibrium model that incorporates market data and techno-economic assessments to simulate market equilibrium. It combines this with a life cycle assessment to explore the environmental implications of implementing different policy instruments. The results show that instruments that do not target a specific technology are more likely to increase thermochemical recycling than mechanical recycling. Furthermore, a higher recycling rate is not equivalent to a better environmental outcome. An increased collection target that ensures a supply of plastic waste would increase the overall recycling rates the most. A recycled content standard for mechanical recycling would lead to the highest increase in mechanical recycling, with top results for environmental indicators, but low results for economic indicators.

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: The McMillan-Ginzburg-Landau (MGL) model for charge density waves (CDW) is employed in a systematic phenomenological study of the different phases that have been probed in recent experiments involving transition metal dichalcogenides. We implemented an efficient imaginary time evolution method to solve the MGL equations, which enabled us to investigate the role of different coupling parameters on the CDW patterns and to perform calculations with different energy functionals that lead to several experimentally observed singularities in the CDW phase profiles. In particular, by choosing the appropriate energy functionals, we were able to obtain phases that go beyond the well-known periodic phase slips (discommensurations), exhibiting also topological defects (i.e., vortex-antivortex pairs), domain walls where the CDW order parameter is suppressed, and even CDW with broken rotational symmetry. Finally, we briefly discuss the effect of these different CDW phases on the profile and critical temperature of the competing superconducting state.

Abstract: Graphene oxide (GO) is one of the most promising candidates for next generation of atomically thin membranes. Nevertheless, one of the major issues for real world application of GO membranes is their undesirable swelling in an aqueous environment. Recently, we demonstrated that generation of H3O+ and OH- ions (e.g., with an external electric field) in the interlayer gallery could impart aqueous stability to the layered GO membranes (A. Gogoi, ACS Appl. Mater. Interfaces, 2022, 14, 34946). This, however, compromises the water flux through the membrane. In this study, we report on reducing the GO nanosheets as a solution to this issue. With the reduction of the GO nanosheets, the water flux through the layered GO membrane initially increases and then decreases again beyond a certain degree of reduction. Here, two key factors are at play. Firstly, the instability of the H-bond network between water molecules and the GO nanosheets, which increases the water flux. Secondly, the pore size reduction in the interlayer gallery of the membranes, which decreases the water flux. We also observe a significant improvement in the salt rejection of the membranes, due to the dissociation of water molecules in the interlayer gallery. In particular, for the case of 10% water dissociation, the water flux through the membranes can be enhanced without altering its selectivity. This is an encouraging observation as it breaks the traditional tradeoff between water flux and salt rejection of a membrane.

Abstract: Restoration of drained peatlands through rewetting has recently emerged as a prevailing strategy to mitigate excessive greenhouse gas emissions and re-establish the vital carbon sequestration capacity of peatlands. Rewetting can help to restore vegetation communities and biodiversity, while still allowing for extensive agricultural management such as paludiculture. Belowground processes governing carbon fluxes and greenhouse gas dynamics are mediated by a complex network of microbial communities and processes. Our understanding of this complexity and its multi-factorial controls in rewetted peatlands is limited. Here, we summarize the research regarding the role of soil microbial communities and functions in driving carbon and nutrient cycling in rewetted peatlands including the use of molecular biology techniques in understanding biogeochemical processes linked to greenhouse gas fluxes. We emphasize that rapidly advancing molecular biology approaches, such as high-throughput sequencing, are powerful tools helping to elucidate the dynamics of key biogeochemical processes when combined with isotope tracing and greenhouse gas measuring techniques. Insights gained from the gathered studies can help inform efficient monitoring practices for rewetted peatlands and the development of climate-smart restoration and management strategies.

Abstract: Symmetry breaking plays a pivotal role in unlocking intriguing properties and functionalities in material systems. For example, the breaking of spatial and temporal symmetries leads to a fascinating phenomenon: the superconducting diode effect. However, generating and precisely controlling the superconducting diode effect pose significant challenges. Here, we take a novel route with the deliberate manipulation of magnetic charge potentials to realize unconventional superconducting flux-quantum diode effects. We achieve this through suitably tailored nanoengineered arrays of nanobar magnets on top of a superconducting thin film. We demonstrate the vital roles of inversion antisymmetry and its breaking in evoking unconventional superconducting effects, namely a magnetically symmetric diode effect and an odd-parity magnetotransport effect. These effects are nonvolatilely controllable through in situ magnetization switching of the nanobar magnets. Our findings promote the use of antisymmetry (breaking) for initiating unconventional superconducting properties, paving the way for exciting prospects and innovative functionalities in superconducting electronics.

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: Metal-based nanoparticles (MNPs) are promoted as effective compounds in the treatment of bacterial infections and as possible alternatives to antibiotics. These MNPs are known to affect a broad spectrum of microorganisms using a multitude of strategies, including the induction of reactive oxygen species and interaction with the inner structures of the bacterial cells. The aim of this review was to summarise the latest studies about the effect of metal-based nanoparticles on pathogenic bacterial biofilm formed in wounds, using the examples of Gram-positive bacterium Staphylococcus aureus and Gram-negative bacterium Pseudomonas aeruginosa, as well as provide an overview of possible clinical applications. Declaration of interest: The authors have no conflicts of interest.

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: 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: Chirality in gold nanostructures offers an exciting opportunity to tune their differential optical response to left- and right-handed circularly polarized light, as well as their interactions with biomolecules and living matter. However, tuning and understanding such interactions demands quantification of the structural features that are responsible for the chiral behavior. Electron tomography (ET) enables structural characterization at the single-particle level and has been used to quantify the helicity of complex chiral nanorods. However, the technique is time-consuming and consequently lacks statistical value. To address this issue, we introduce herein a high-throughput methodology that combines images acquired by secondary electron-based electron beam-induced current (SEEBIC) with quantitative image analysis. As a result, the geometric chirality of hundreds of nanoparticles can be quantified in less than 1 h. When combining the drastic gain in data collection efficiency of SEEBIC with a limited number of ET data sets, a better understanding of how the chiral structure of individual chiral nanoparticles translates into the ensemble chiroptical response can be reached.