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.