Memristors with rich interior dynamics of ion migration are promising for mimicking various biological synaptic functions in neuromorphic hardware systems. A graphene-based memristor shows an extremely low energy consumption of less than a femtojoule per spike, by taking advantage of weak surface van der Waals interaction of graphene. The device also shows an intriguing programmable metaplasticity property in which the synaptic plasticity depends on the history of the stimuli and yet allows rapid reconfiguration via an immediate stimulus. This graphene-based memristor could be a promising building block toward designing highly versatile and extremely energy efficient neuromorphic computing systems.

The industrialization of lithium–sulfur (Li–S) batteries is simultaneously impeded by the shuttle effect of lithium polysulfides and dendrites growth on lithium anode. To address both issues, a novel sulfiphilic and lithiophilic interlayer of Mo2N quantum dots decorated N‐doped graphene‐nanosheet (Mo2N@NG) are presented on polypropylene separator via a facile scalable method. Benefiting from the strong chemisorption ability, eminent electrocatalysis for LiPSs, and high chemical affinity with lithium‐ion (Li+), Mo2N@NG can efficiently catalyze the rapid transformation of LiPSs and induce uniform deposition of Li+. Theoretical calculation and in situ Raman synergistically elucidate the inhibition of shuttle effect and alleviation of dendrite growth. As a result, the assembled Li–S cell with Mo2N@NG/PP separator exhibits remarkable rate performance (860.2 mA h g–1 at 4 C), good cycling stability (0.039% capacity decay per cycle after 800 cycles at 2 C), a high areal capacity of 3.89 mA h cm–2 of Li–S pouch cell (4.5 mg cm–2 and 6 µL mg–1 at 0.2 C), and steady performance in protecting the lithium anode (at 5 mA cm–2 for 1500 h). This present strategy of quantum dots in a hybrid framework has great potential to be generalized to other transition metal‐based catalysts for advanced Li–S batteries.

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SUMMARYThis paper is the first endeavour to present the local domain-free discretization (DFD) method for the solution of compressible Navier-Stokes/Euler equations in conservative form. The discretization strategy of DFD is that for any complex geometry, there is no need to introduce coordinate transformation and the discrete form of governing equations at an interior point may involve some points outside the solution domain. The functional values at the exterior dependent points are updated at each time step to impose the wall boundary condition by the approximate form of solution near the boundary. Some points inside the solution domain are constructed for the approximate form of solution, and the flow variables at constructed points are evaluated by the linear interpolation on triangles. The numerical schemes used in DFD are the finite element Galerkin method for spatial discretization and the dual-time scheme for temporal discretization. It is well known that the analytical method takes two separate steps to get the closed-form solution of a PDE. In the first step, a general solution is pursued which is only based on the given PDE. Then in the second step, the expression of the general solution is substituted into the boundary conditions to determine the unknown coefficients in the general solution. Clearly, the first step does not involve the solution domain. The solution domain (geometry of the problem) is * Correspondence to: C. Shu, Department of Mechanical Engineering, National University of Singapore, Singapore 119260, Singapore. † E-mail: mpeshuc@nus.edu.sg only involved in the second step when the boundary condition is implemented. So the analytical method can be well applied to both regular and irregular domain problems.In contrast, the conventional numerical method solves the PDE by directly coupling it with the boundary condition. In other words, the numerical solution is obtained in just one step. In this step, the PDE is discretized on the solution domain with proper implementation of the boundary condition. We can see clearly that the discretization of the PDE in a numerical method is problem dependent. Due to this feature, some numerical methods such as finite difference schemes can only be applied to regular domain problems. When they are applied to solve irregular domain problems, the coordinate transformation is a must. In general, the process of coordinate transformation is very complicated, and problem dependent. To overcome the drawbacks of conventional numerical methods that strongly couple the PDE with the solution domain, the DFD method was developed from the process of analytical method.In the DFD, the implementation of the boundary condition and discretization of the governing equation are treated separately. The selected point for numerical discretization of PDE is inside the solution domain, but the discrete form of the PDE at the selected point may involve some points outside the solution domain, which serve as the role to implement the boundary condition. The key process in the...