Beijing University of Technology

About: Beijing University of Technology is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: Microstructure & Laser. The organization has 31929 authors who have published 31987 publications receiving 352112 citations. The organization is also known as: Běijīng Gōngyè Dàxué & Beijing Polytechnic University.

R-graphyne: a new two-dimensional carbon allotrope with versatile Dirac-like point in nanoribbons

Abstract: A novel two-dimensional carbon allotrope, rectangular graphyne (R-graphyne) with tetra-rings and acetylenic linkages, is proposed by first-principles calculations. Although the bulk R-graphyne exhibits metallic property, the nanoribbons of R-graphyne show distinct electronic structures from the bulk. The most intriguing feature is that band gaps of R-graphyne nanoribbons oscillate between semiconductor and metallic states as a function of width. Particularly, the zigzag edge nanoribbons with half-integer repeating unit cell exhibit unexpected Dirac-like fermions in the band structures. The Dirac-like fermions of the R-graphyne nanoribbons originate from the central symmetry and two sub-lattices. The extraordinary properties of R-graphyne nanoribbons greatly expand our understanding of the origin of Dirac-like points. Such findings uncover a novel fascinating property of nanoribbons, which may have broad potential applications for carbon-based nanoscale electronic devices.

Reliable Pretrip Multipath Planning and Dynamic Adaptation for a Centralized Road Navigation System

Abstract: In this paper, an integrated approach combining offline precomputation of optimal candidate paths with online path retrieval and dynamic adaptation is proposed for a dynamic navigation system in a centralized system architecture. Based on a static traffic data file, a partially disjoint candidate path set is constructed prior to the trip using a heuristic link weight increment method. This method satisfies reasonable path constraints that meet the drivers' preferences, as well as alternative path constraints, that limit the joint failure probability for candidate paths. The characteristics of the proposed algorithm are the following: 1) The response time for online navigation demand is nearly linear with network size and less dependent on system load; 2) the veracity of the pretrip route plan based on the static data file is improved by taking travel time reliability into account; and 3) system optimization can be approximated without sacrificing driver preferences. The algorithm is tested on randomly generated road networks, and the numerical results show the efficiency of the approach