The realization of high-quality (Q) resonators regardless of the underpinning material platforms has been a ceaseless pursuit, because the high-Q resonators pro... 相似文献
The solid‐state packing and polymer orientation relative to the substrate are key properties to control in order to achieve high charge carrier mobilities in organic field effect transistors (OFET). Intuitively, shorter side chains are expected to yield higher charge carrier mobilities because of a denser solid state packing motif and a higher ratio of charge transport moieties. However our findings suggest that the polymer chain orientation plays a crucial role in high‐performing diketopyrrolopyrrole‐based polymers. By synthesizing a series of DPP‐based polymers with different branched alkyl side chain lengths, it is shown that the polymer orientation depends on the branched alkyl chain lengths and that the highest carrier mobilities are obtained only if the polymer adopts a mixed face‐on/edge‐on orientation, which allows the formation of 3D carrier channels in an otherwise edge‐on‐oriented polymer chain network. Time‐of‐flight measurements performed on the various polymer films support this hypothesis by showing higher out‐of‐plane carrier mobilities for the partially face‐on‐oriented polymers. Additionally, a favorable morphology is mimicked by blending a face‐on polymer into an exclusively edge‐on oriented polymer, resulting in higher charge carrier mobilities and opening up a new avenue for the fabrication of high performing OFET devices. 相似文献
Maximizing network lifetime is the main goal of designing a wireless sensor network. Clustering and routing can effectively balance network energy consumption and prolong network lifetime. This paper presents a novel cluster-based routing protocol called EECRAIFA. In order to select the optimal cluster heads, Self-Organizing Map neural network is used to perform preliminary clustering on the network nodes, and then the relative reasonable level of the cluster, the cluster head energy, the average distance within the cluster and other factors are introduced into the firefly algorithm (FA) to optimize the network clustering. In addition, the concept of decision domain is introduced into the FA to further disperse cluster heads and form reasonable clusters. In the inter-cluster routing stage, the inter-cluster routing is established by an improved ant colony optimization (ACO). Considering factors such as the angle, distance and energy of the node, the heuristic function is improved to make the selection of the next hop more targeted. In addition, the coefficient of variation in statistics is introduced into the process of updating pheromones, and the path is optimized by combining energy and distance. In order to further improve the network throughput, a polling control mechanism based on busy/idle nodes is introduced during the intra-cluster communication phase. The simulation experiment results prove that under different application scenarios, EECRAIFA can effectively balance the network energy consumption, extend the network lifetime, and improve network throughput.
