A Novel Ternary Composite of Polyurethane/Polyaniline/Nanosilica with Antistatic Property and Excellent Mechanical Strength: Preparation and Mechanism

Chinese Journal of Polymer Science - Antistatic and strength properties are of vital importance for polyurethane rubber used in moving parts of many industrial instruments. Herein, polyurethane was...     

In situ confinement of iron-based active sites within high porosity carbon frameworks with enhanced activity for rechargeable Zn–air battery

Non-noble bifunctional electrocatalysts with robust activity and stability toward oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) are greatly significant but challenging for Zn-air batteries. Here, in situ confinement of FeN_x active sites in high porosity carbon framework (FeN_x/CMCC) derived from chelate of carboxymethylcellulose (CMC) and iron ions were synthesized. Particularly, construction of FeN_x within porous carbon framework accelerates the electron transfer and the sufficient utilization of active centers, and then expedites the reaction kinetics of ORR and OER. As expected, the optimized FeN_x/CMCC exhibits superior ORR activity with a larger half-wave potential of 0.869 V. The rechargeable Zn-air battery delivers a higher power density of 99.6 mW/cm² and a special capacity of 781.9 mA h/g_Zn at 10 mA/cm², together with excellent durability of over 335 h. Remarkably, the as-assembled solid-state battery exhibits a higher open circuit voltage (OCV) of 1.5 V, a special capacity of 709.7 mA h/g_Zn, as well as prolonged cycling stability (90 h). Moreover, the flexible solid-state battery displays negligible loss of electrochemical performance under various bending angles, illustrating its potential application in flexible electronic devices.     

The effects of learning in production and group size on the lot-sizing problem

One of the lot-sizing problem extensions that received noticeable attention in the literature is the one that investigated the effects of learning in production. The studies along this line of research assumed learning to improve with the number of repetitions following a power form. There is evidence also that the group size, i.e., the number of workers learning in a group affects performance (time per unit). This note revisits the problem and modifies it by incorporating the group size, along with cumulative production, as a proxy for measuring performance. Numerical examples are provided to illustrate the behavior of the modified model. The results of the two models are also compared to draw some meaningful insights and conclusions. Although the results favor using a simple univariate learning curve, considering group size when modeling lot-sizing problems can significantly affect the unit production cost.     

A modified SPH method to model the coalescence of colliding non-Newtonian liquid droplets

This paper develops a modified smoothed particle hydrodynamics (SPH) method to model the coalescence of colliding non-Newtonian liquid droplets. In the present SPH, a van der Waals (vdW) equation of state is particularly used to represent the gas-to-liquid phase transition similar to that of a real fluid. To remove the unphysical behavior of the particle clustering, also known as tensile instability, an optimized particle shifting technique is implemented in the simulations. To validate the numerical method, the formation of a Newtonian vdW droplet is first tested, and it clearly demonstrates that the tensile instability can be effectively removed. The method is then extended to simulate the head-on binary collision of vdW liquid droplets. Both Newtonian and non-Newtonian fluid flows are considered. The effect of Reynolds number on the coalescence process of droplets is analyzed. It is observed that the time up to the completion of the first oscillation period does not always increase as the Reynolds number increases. Results for the off-center binary collision of non-Newtonian vdW liquid droplets are lastly presented. All the results enrich the simulations of the droplet dynamics and deepen understandings of flow physics. Also, the present SPH is able to model the coalescence of colliding non-Newtonian liquid droplets without tensile instability.     

Multi-stable quantum droplets in optical lattices

Nonlinear Dynamics - We address the nonlinear dynamics of binary Bose-Einstein condensates with mutually symmetric spinor components trapped in an optical lattice. The interaction between the...     

Unravelling the Enigma of Nonoxidative Conversion of Methane on Iron Single-Atom Catalysts

The direct, nonoxidative conversion of methane on a silica-confined single-atom iron catalyst is a landmark discovery in catalysis, but the proposed gas-phase reaction mechanism is still open to discussion. Here, we report a surface reaction mechanism by computational modeling and simulations. The activation of methane occurs at the single iron site, whereas the dissociated methyl disfavors desorption into gas phase under the reactive conditions. In contrast, the dissociated methyl prefers transferring to adjacent carbon sites of the active center (Fe₁©SiC₂), followed by C−C coupling and hydrogen transfer to produce the main product (ethylene) via a key −CH−CH₂ intermediate. We find a quasi Mars–van Krevelen (quasi-MvK) surface reaction mechanism involving extracting and refilling the surface carbon atoms for the nonoxidative conversion of methane on Fe₁©SiO₂ and this surface process is identified to be more plausible than the alternative gas-phase reaction mechanism.     

Video deraining via nonlocal low-rank regularization

Outdoor videos captured in rainy weather may be significantly corrupted by the undesired rain streaks, which severely affect the video processing tasks in outdoor computer vision systems. In this paper, we propose a tensor-based video rain streaks removal method using the nonlocal low-rank regularization. Specifically, we first divide videos into overlapped spatial–temporal patches. Then for each patch, we group its nonlocal similar spatial–temporal patches to form a third-order tensor. To model the clean videos, we characterize the wealth redundancy by adopting the tensor nuclear norm to regularize the low-rankness of the third-order tensors formed by similar spatial–temporal patches of clean videos. We also consider the piecewise smoothness and the temporal continuity of clean videos and utilize the unidirectional total variation to enhance the smoothness and continuity. Moreover, as rain streaks are sparse and smooth along the rain direction, we model the rain streaks by employing an ℓ₁ norm and the unidirectional total variation penalty to boost the sparsity and directional smoothness, respectively. We develop an efficient alternating direction method of multipliers to solve the proposed model. Experimental results on both synthetic and real rainy videos show that our method outperforms the state-of-the-art methods quantitatively and qualitatively.     

Novel biogeography-based optimization algorithm with hybrid migration and global-best Gaussian mutation

The Biogeography-Based Optimization algorithm and its variants have been used widely for optimization problems. To get better performance, a novel Biogeography-Based Optimization algorithm with Hybrid migration and global-best Gaussian mutation is proposed in this paper. Firstly, a linearly dynamic random heuristic crossover strategy and an exponentially dynamic random differential mutation one are presented to form a hybrid migration operator, and the former is used to get stronger local search ability and the latter strengthen the global search ability. Secondly, a new global-best Gaussian mutation operator is put forward to balance exploration and exploitation better. Finally, a random opposition learning strategy is merged to avoid getting stuck in local optima. The experiments on the classical benchmark functions and the complexity functions from CEC-2013 and CEC-2017 test sets, and the Wilcoxon, Bonferroni-Holm and Friedman statistical tests are used to evaluate our algorithm. The results show that our algorithm obtains better performance and faster running speed compared with quite a few state-of-the-art competitive algorithms. In addition, experimental results on Minimum Spanning Tree and K-means clustering optimization show that our algorithm can cope with these two problems better than the comparison algorithms.     

Numerical solution of bed load transport equations using discrete least squares meshless (DLSM) method

The discrete least squares meshless (DLSM) method is extended in this paper for solving coupled bedload sediment transport equations. The mathematical formulation of this model consists of shallow water equations for the hydrodynamical component and an Exner equation expressing sediment continuity for the bedload transport. This method uses the moving least squares (MLS) function approximation to construct the shape functions and the minimizing least squares functional method to discretize the system of equations. The method can be viewed as a truly meshless method as it does not need any mesh for both field variable approximation and the construction of system matrices; it also provides the symmetric coefficient matrix. In the present work, several benchmark problems are studied and compared with the work of other researchers; the proposed method shows good accuracy, high convergence rate, and high efficiency, even for irregularly distributed nodes. At the end, a real test problem is performed to show and verify the main benefit and applicability of the proposed method to cope with complex geometry in practical problems.     

正电子冲击下氦电离三重微分截面的理论计算

我们发展了一种正电子碰撞原子电离的畸变波Born近似方法， 在这个方法中，正负电子偶素通道通过一个ab initio的光学势附加到入射粒子和靶的相互作用势上，且通道对电离作用被第一次被考虑在正电子碰撞原子电离的过程中. 应用这个方法计算了在50 eV入射能量范围氦的电离的三重微分截面，计算结果和实验数据很好的符合.