A Facile Route to Cotton-Like BiOCl Nanomaterial with Enhanced Dye-Sensitized Visible Light Photocatalytic Efficiency

A facile route is developed to fabricate BiOCI porous cotton-like nanostructure by using Bi203 and hydrochlo- ric acid as raw materials. The BiOCI nanomaterial is actually hierarchically structured by numerous ultrathin nanosheets. The nanosheets are around 50-500 nm in lateral size and 2-12 nm in thickness. High-resolution trans- mission electron microscopy and selected-area electron diffraction analyses indicate that single-crystalline BiOCl nanosheets have the predominant growth direction along [110], the bottom and top surfaces are {001} facets, and four lateral surfaces are {110} facets. The BiOCl nanosheets are dominantly enclosed by {001} facets. From the diffuse reflectance spectroscopy spectrum, the light absorption edge and band gap energy （Eg） are estimated to be 416 nm and 2.98eV, respectively. The BiOCl photocatalyst possesses superior activity for methyl orange （MO） degradation under visible light irradiation and the photodegradation efficiency is up to 91.5%/180 min. The correlation between morphology and microstructure with enhanced MO-sensitized photodegradation performance under visible light is investigated.

Traffic resource allocation for complex networks

In this paper, an optimal resource allocation strategy is proposed to enhance traffic dynamics in complex networks. The network resources are the total node packet-delivering capacity and the total link bandwidth. An analytical method is developed to estimate the overall network capacity by using the concept of efficient betweenness （ratio of algorithmic betweenness and local processing capacity）. Three network structures （scale-free, small-world, and random networks） and two typical routing protocols （shortest path protocol and efficient routing protocol） are adopted to demonstrate the performance of the proposed strategy. Our results show that the network capacity is reversely proportional to the average path length for a particular routing protocol and the shortest path protocol can achieve the largest network capacity when the proposed resource allocation strategy is adopted.

Energy aware hierarchical cluster-based routing protocol for WSNs

Wireless sensor networks（WSNs） are emerging as essential and popular ways of providing pervasive computing environments for various applications. Unbalanced energy consumption is an inherent problem in WSNs, characterized by multi-hop routing and a many-to-one traffic pattern. This uneven energy dissipation can significantly reduce network lifetime. In multi-hop sensor networks, information obtained by the monitoring nodes need to be routed to the sinks, the energy consumption rate per unit information transmission depends on the choice of the next hop node. In an energy-aware routing approach, most proposed algorithms aim at minimizing the total energy consumption or maximizing network lifetime. In this paper, we propose a novel energy aware hierarchical cluster-based（NEAHC） routing protocol with two goals： minimizing the total energy consumption and ensuring fairness of energy consumption between nodes. We model the relay node choosing problem as a nonlinear programming problem and use the property of convex function to find the optimal solution. We also evaluate the proposed algorithm via simulations at the end of this paper.