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The refraction of surface gravity waves by currents leads to spatial modulations in the wave field and, in particular, in the significant wave height. We examine this phenomenon in the case of waves scattered by a localised current feature, assuming (i) the smallness of the ratio between current velocity and wave group speed, and (ii) a swell-like, highly directional wave spectrum. We apply matched asymptotics to the equation governing the conservation of wave action in the four-dimensional position–wavenumber space. The resulting explicit formulas show that the modulations in wave action and significant wave height past the localised current are controlled by the vorticity of the current integrated along the primary direction of the swell. We assess the asymptotic predictions against numerical simulations using WAVEWATCH III for a Gaussian vortex. We also consider vortex dipoles to demonstrate the possibility of ‘vortex cloaking’ whereby certain currents have (asymptotically) no impact on the significant wave height. We discuss the role of the ratio of the two small parameters characterising assumptions (i) and (ii) above, and show that caustics are significant only for unrealistically large values of this ratio, corresponding to unrealistically narrow directional spectra.

 

Abstract Direct ethanol fuel cells have been widely investigated as nontoxic and low-corrosive energy conversion devices with high energy and power densities. It is still challenging to develop high-activity and durable catalysts for a complete ethanol oxidation reaction on the anode and accelerated oxygen reduction reaction on the cathode. The materials’ physics and chemistry at the catalytic interface play a vital role in determining the overall performance of the catalysts. Herein, we propose a Pd/Co@N-C catalyst that can be used as a model system to study the synergism and engineering at the solid-solid interface. Particularly, the transformation of amorphous carbon to highly graphitic carbon promoted by cobalt nanoparticles helps achieve the spatial confinement effect, which prevents structural degradation of the catalysts. The strong catalyst-support and electronic effects at the interface between palladium and Co@N-C endow the electron-deficient state of palladium, which enhances the electron transfer and improved activity/durability. The Pd/Co@N-C delivers a maximum power density of 438 mW cm −2 in direct ethanol fuel cells and can be operated stably for more than 1000 hours. This work presents a strategy for the ingenious catalyst structural design that will promote the development of fuel cells and other sustainable energy-related technologies. 

Materials keeping thickness in atomic scale but extending primarily in lateral dimensions offer properties attractive for many emerging applications. However, compared to crystalline counterparts, synthesis of atomically thin films in the highly disordered amorphous form, which avoids nonuniformity and defects associated with grain boundaries, is challenging due to their metastable nature. Here we present a scalable and solution-based strategy to prepare large-area, freestanding quasi-2D amorphous carbon nanomembranes with predominant sp²bonding and thickness down to 1–2 atomic layers, from coal-derived carbon dots as precursors. These atomically thin amorphous carbon films are mechanically strong with modulus of 400 ± 100 GPa and demonstrate robust dielectric properties with high dielectric strength above 20 MV cm⁻¹and low leakage current density below 10⁻⁴ A cm⁻²through a scaled thickness of three-atomic layers. They can be implemented as solution-deposited ultrathin gate dielectrics in transistors or ion-transport media in memristors, enabling exceptional device performance and spatiotemporal uniformity.

 

Memristive devices can offer dynamic behaviour, analogue programmability, and scaling and integration capabilities. As a result, they are of potential use in the development of information processing and storage devices for both conventional and unconventional computing paradigms. Their memristive switching processes originate mainly from the modulation of the number and position of structural defects or compositional impurities—what are commonly referred to as imperfections. While the underlying mechanisms and potential applications of memristors based on traditional bulk materials have been extensively studied, memristors based on van der Waals materials have only been considered more recently. Here we examine imperfection-enabled memristive switching in van der Waals materials. We explore how imperfections— together with the inherent physicochemical properties of the van der Waals materials—create different switching mechanisms, and thus provide a range of opportunities to engineer switching behaviour in memristive devices. We also discuss the challenges involved in terms of material selection, mechanism investigation and switching uniformity control, and consider the potential of van der Waals memristors in system-level implementations of efficient computing technologies. 

Federated learning is a framework for distributed optimization that places emphasis on communication efficiency. In particular, it follows a client-server broadcast model and is appealing because of its ability to accommodate heterogene- ity in client compute and storage resources, non-i.i.d. data assumptions, and data privacy. Our contribution is to offer a new federated learning algorithm, FedADMM, for solving non-convex composite optimization problems with non-smooth regularizers. We prove the convergence of FedADMM for the case when not all clients are able to participate in a given communication round under a very general sampling model.