Recent progress in periodic patterning fabricated by self-assembly of colloidal spheres for optical applications

Colloidal crystals are periodically ordered arrays of monodisperse colloidal particles which represent a new class of self-assembled materials showing potential applications in many fields.Two-dimensional graphic nanostructures based on colloidal crystals have inherent periodicity from tens of nanometers to several micrometers,which gives them rich and interesting optical properties.This article presents a comprehensive review about the current research activities on the self-assembly of colloidal spheres which is an effective strategy for fabrication of various hierarchical and ordered nanostructures,with particular attention paid to the unique properties and applications of the colloidal crystal-based nanostructures.Three main aspects are elaborated:a)controllable self-assembly of colloidal crystals;b)the functions of the obtained colloidal spheres acting as the patterned mask for successive construction of numerous nanostructures;c)the novel properties and promising optical applications of the patterned nanostructures in various domains,such as plasmonic-related fields,antireflection,photonic crystals,photocatalysis and electronic devices.After that,the current challenges and future perspectives in this area are provided.This review aims to inspire more ingenious designs and exciting research for manufacturing nanostructures utilizing colloidal self-assembly.

End-to-end delay analysis for networked systems

End-to-end delay measurement has been an essential element in the deployment of real-time services in networked systems. Traditional methods of delay measurement based on time domain analysis, however, are not efficient as the network scale and the complexity increase. We propose a novel theoretical framework to analyze the end-to-end delay distributions of networked systems from the frequency domain. We use a signal flow graph to model the delay distribution of a networked system and prove that the end-to-end delay distribution is indeed the inverse Laplace transform of the transfer function of the signal flow graph. ~vo efficient methods, Cramer＇s rule-based method and the Mason gain rule-based method, are adopted to obtain the transfer function. By analyzing the time responses of the transfer function, we obtain the end-to-end delay distribution. Based on our framework, we propose an efficient method using the dominant poles of the transfer function to work out the bottleneck links of the network. Moreover, we use the framework to study the network protocol performance. Theoretical analysis and extensive evaluations show the effectiveness of the proposed approach.