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: Chiral ligands are considered a required ingredient during the synthesis of dissymmetric plasmonic metal nanocrystals. The mechanism behind the generation of chiral structures involves the formation of high Miller index chiral facets, induced by the adsorption of such chiral ligands. We found however that, chirality can also evolve spontaneously, without the involvement of any chiral ligands, during the co-deposition of Au and Ag on Au nanorods. When using a specific Au/Ag ratio, phase segregation of the two metals leads to an interface within the obtained AuAg shell, which can be exposed by removing the Ag component via oxidative etching. Although a close-to-racemic mixture of chiral Au nanorods with right and left handedness is found in solution, electron tomography analysis evidences left- and righthanded helicities, both at the Au-Ag interface and at the exposed surface of Au NRs after Ag etching. The helicity profile of the NRs indicates dominating inclination angles in a range from 30° to 60°. Single-particle optical characterization also reveals random handedness in the plasmonic response of individual nanorods. We hypothesize that, the origin of chirality is related with symmetry breaking during the co-deposition of Au and Ag, through an initial perturbation in a small region on the Au-Ag interface that eventually leads to chiral segregation throughout the nanocrystal.

Abstract: CsPbI3 is a promising perovskite material for photovoltaic applications in its photoactive perovskite or black phase. However, the material degrades to a photovoltaically inactive or yellow phase at room temperature. Various mitigation strategies are currently being developed to increase the lifetime of the black phase, many of which rely on inducing strains in the material that hinder the black-to-yellow phase transition. Physical insight into how these strategies exactly induce strain as well as knowledge of the spatial extent over which these strains impact the material is crucial to optimize these approaches but is still lacking. Herein, we combine machine learning potential-based molecular dynamics simulations with our in silico strain engineering approach to accurately quantify strained large-scale atomic structures on a nanosecond time scale. To this end, we first model the strain fields introduced by atomic substitutions as they form the most elementary strain sources. We demonstrate that the magnitude of the induced strain fields decays exponentially with the distance from the strain source, following a decay rate that is largely independent of the specific substitution. Second, we show that the total strain field induced by multiple strain sources can be predicted to an excellent approximation by summing the strain fields of each individual source. Finally, through a case study, we illustrate how this additive character allows us to explain how complex strain fields, induced by spatially extended strain sources, can be predicted by adequately combining the strain fields caused by local strain sources. Hence, the strain additivity proposed here can be adopted to further our insight into the complex strain behavior in perovskites and to design strain from the atomic level onward to enhance their sought-after phase stability.

Abstract: We report a plasma‐assisted CO₂hydrogenation to CH₃OH over Fe₂O₃/γ‐Al₂O₃catalysts, achieving 12% CO₂conversion and 58% CH₃OH selectivity at a temperature of nearly 80°C atm pressure. We investigated the effect of various supports and loadings of the Fe‐based catalysts, as well as optimized reaction conditions. We characterized catalysts by X‐ray powder diffraction (XRD), hydrogen temperature programmed reduction (H₂‐TPR), CO₂and CO temperature programmed desorption (CO₂/CO‐TPD), high‐resolution transmission electron microscopy (HRTEM), scanning transmission electron microscopy (STEM), x‐ray photoelectron spectroscopy (XPS), Mössbauer, and Fourier transform infrared<bold>(</bold>FTIR). The XPS results show that the enhanced CO₂conversion and CH₃OH selectivity are attributed to the chemisorbed oxygen species on Fe₂O₃/γ‐Al₂O₃. Furthermore, the diffuse reflectance infrared Fourier transform spectroscopy (DRIFTs) and TPD results illustrate that the catalysts with stronger CO₂adsorption capacity exhibit a higher reaction performance.<italic>In situ</italic>DRIFTS gain insight into the specific reaction pathways in the CO₂/H₂plasma. This study reveals the role of chemisorbed oxygen species as a key intermediate, and inspires to design highly efficient catalysts and expand the catalytic systems for CO₂hydrogenation to CH₃OH.

Abstract: Secondary electron emission is an important process that plays a significant role in several plasma‐related applications. As measuring the secondary electron yield experimentally is very challenging, quantitative modelling of this process to obtain reliable yield data is critical as input for higher‐scale simulations. Here, we build upon our previous work combining density functional theory calculations with a model originally developed by Hagstrum to extend its application to metallic surfaces. As plasmonic effects play a much more important role in the secondary electron emission mechanism for metals, we introduce an approach based on Poisson point processes to include both surface and bulk plasmon excitations to the process. The resulting model is able to reproduce the yield spectra of several available experimental results quite well but requires the introduction of global fitting parameters, which describe the strength of the plasmon interactions. Finally, we use an in‐house developed workflow to calculate the electron yield for a list of elemental surfaces spanning the periodic table to produce an extensive data set for the community and compare our results with more simplified approaches from the literature.

Abstract: technologies have been expanding, and one of the most exciting and rapidly growing
applications is in biology and medicine. Most biomedical studies with DBD plasma systems are performed in vitro, which include cells grown on the surface of plastic well plates, or in vivo, which include animal research models (e.g. mice, pigs). Since many DBD systems use the biological target as the secondary electrode for direct plasma generation and treatment, they are sensitive to the surface properties of the target, and thus can be altered based on the in vitro or in vivo system used. This could consequently affect biological response from plasma treatment. Therefore, in this study, we investigated the DBD plasma behavior both in vitro (i.e. 96-well flat bottom plates, 96-well U-bottom plates, and 24-well flat bottom plates), and in vivo (i.e. mouse skin). Intensified charge coupled device (ICCD) imaging was performed and the plasma discharges were visually distinguishable between the different systems. The geometry of the wells did not affect DBD plasma generation for low application distances (≤ 2 mm), but differentially affected plasma uniformity on the bottom of the well at greater distances. Since DBD plasma treatment in vitro is rarely performed in dry wells for plasma medicine experiments, the effect of well wetness was also investigated. In all in vitro cases, the uniformity of the DBD plasma was affected when comparing wet versus dry wells, with the plasma in the wide-bottom wells appearing the most similar to plasma generated on mouse skin. Interestingly, based on quantification of ICCD images, the DBD plasma intensity per surface area demonstrated an exponential one-phase decay with increasing application distance, regardless of the in vitro or in vivo system. This trend is similar to that of the energy per pulse of plasma, which is used to determine the total plasma treatment energy for biological systems. Optical emission spectroscopy performed on the plasma revealed similar trends in radical species generation between the plastic well plates and mouse skin. Therefore, taken together, DBD plasma intensity per surface area may be a valuable parameter to be used as a simple method for in situ monitoring during biological treatment and active plasma treatment control, which can be applied for in vitro and in vivo systems.

Abstract: In this study, the multi-layer self-assembled molecular network formation of an alkylated tetrathiafulvalene compound is studied at the liquid-solid interface between 1-phenyloctane and graphite. A combined theoretical/experimental approach associating force-field and quantum-chemical calculations with scanning tunnelling microscopy is used to determine the two-dimensional self-assembly beyond the monolayer, but also to further the understanding of the molecular adsorption conformation and its impact on the molecular packing within the assemblies at the monolayer and bilayer level.

Abstract: Nanoscale extension and refinement of the Lucas-Washburn model is presented with a detailed analysis of recent experimental data and extensive molecular dynamics simulations to investigate rapid water flow and water imbibition within nanocapillaries. Through a comparative analysis of capillary rise in hydrophilic nanochannels, an unexpected reversal of the anticipated trend, with an abnormal peak, of imbibition length below the size of 3 nm was discovered in hydrophilic nanochannels, surprisingly sharing the same physical origin as the well-known peak observed in flow rate within hydrophobic nanochannels. The extended imbibition model is applicable across diverse spatiotemporal scales and validated against simulation results and existing experimental data for both hydrophilic and hydrophobic

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: Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic-resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state-of-the-art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark-field scanning transmission electron microscopy enables the acquisition of ten high-resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allow resolving the real-time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions. Experimental and computational techniques are bridged to unveil atomic dynamics in gold nanoparticles (NPs), using annular dark-field scanning transmission electron microscopy and molecular dynamics simulations informed by machine learning. The approach provides unprecedented insights into the real-time structural behaviors of NPs, merging state-of-the-art techniques to accurately characterize their dynamics under realistic conditions. image

Abstract: The basal plane of graphene can function as a selective barrier that is permeable to protons but impermeable to all ions and gases, stimulating its use in applications such as membranes, catalysis and isotope separation. Protons can chemically adsorb on graphene and hydrogenate it, inducing a conductor–insulator transition that has been explored intensively in graphene electronic devices. However, both processes face energy barriersand various strategies have been proposed to accelerate proton transport, for example by introducing vacancies, incorporating catalytic metalsor chemically functionalizing the lattice. But these techniques can compromise other properties, such as ion selectivity or mechanical stability. Here we show that independent control of the electric field,<italic>E</italic>, at around 1 V nm⁻¹, and charge-carrier density,<italic>n</italic>, at around 1 × 10¹⁴ cm⁻², in double-gated graphene allows the decoupling of proton transport from lattice hydrogenation and can thereby accelerate proton transport such that it approaches the limiting electrolyte current for our devices. Proton transport and hydrogenation can be driven selectively with precision and robustness, enabling proton-based logic and memory graphene devices that have on–off ratios spanning orders of magnitude. Our results show that field effects can accelerate and decouple electrochemical processes in double-gated 2D crystals and demonstrate the possibility of mapping such processes as a function of<italic>E</italic>and<italic>n</italic>, which is a new technique for the study of 2D electrode–electrolyte interfaces.