Chunlin Zheng

Bio: Chunlin Zheng is an academic researcher from Hohai University. The author has contributed to research in topics: Materials science & Composite material. The author has an hindex of 1, co-authored 1 publications receiving 467 citations.

Expanded graphite/Co@C composites with dual functions of corrosion resistance and microwave absorption

Abstract: The development of microwave absorption materials with good environmental adaptability is a hot topic in the electromagnetic protection field. In this research, Expanded graphite (EG)/ZIF-67 nanocubes-derived ([email protected]) composites were successfully fabricated by electrostatic assembly and subsequent heat treatment. The results show that the involvement of an appropriate content of [email protected] not only overcomes the problem of single EG impedance mismatch but also introduces additional magnetic loss for the absorber. At the thicknesses of 1.6 mm and 1.5 mm, an effective absorption bandwidth (EAB) of 4.52 GHz and a minimum reflection loss (RLmin) of -48.4 dB were achieved for the Z2-700 sample with a low filling ratio (20 wt%). The enhancement of EMW-absorption performance is attributed to the optimization of impedance matching and the synergistic action between multiple loss mechanisms. Electrochemical corrosion test showed that graphite nanoflakes of EG enhanced the transfer resistance during corrosion, and the corrosion resistance of pure [email protected] was enhanced with the protection of EG. This work provides a reasonable attempt to design and fabricate efficient microwave absorption materials suitable for harsh environments.

Analysis of Energy-Efficient Connected Target Coverage Algorithms for Industrial Wireless Sensor Networks

Abstract: Recent breakthroughs in wireless technologies have greatly spurred the emergence of industrial wireless sensor networks (IWSNs). To facilitate the adaptation of IWSNs to industrial applications, concerns about networks’ full coverage and connectivity must be addressed to fulfill reliability and real-time requirements. Although connected target coverage (CTC) algorithms in general sensor networks have been extensively studied, little attention has been paid to reveal both the applicability and limitations of different coverage strategies from an industrial viewpoint. In this paper, we analyze characteristics of four recent energy-efficient coverage strategies by carefully choosing four representative connected coverage algorithms: 1) communication weighted greedy cover; 2) optimized connected coverage heuristic; 3) overlapped target and connected coverage; and 4) adjustable range set covers. Through a detailed comparison in terms of network lifetime, coverage time, average energy consumption, ratio of dead nodes, etc., characteristics of basic design ideas used to optimize coverage and network connectivity of IWSNs are embodied. Various network parameters are simulated in a noisy environment to obtain the optimal network coverage. The most appropriate industrial field for each algorithm is also described based on coverage properties. Our study aims to provide IWSNs designers with useful insights to choose an appropriate coverage strategy and achieve expected performance indicators in different industrial applications.

Indoor deployment of low-power wide area networks (LPWAN): A LoRaWAN case study

Abstract: The last decade saw the emergence of the Internet of Things (IoT) paradigm, which aims to connect any object to the Internet. In this context, a new type of wireless communication network emerged known as Low-Power Wire-Area Network (LPWAN). By contrast to well-known short range and multi-hop wireless networks, LPWAN networks allow long range communications at a low bit rate. Furthermore, LPWAN networks are considered to be integrated into 5G. Among LPWAN networks, the LoRaWAN technology gains more and more interest from the research and industrial communities. In this article, we have led a thorough experimental performance evaluation of LoRaWAN in an indoor environment. From this study, we quantify the limits of this technology and expose the merits of using LoRaWAN for IoT communications in the context of 5G.

A Tree-Cluster-Based Data-Gathering Algorithm for Industrial WSNs With a Mobile Sink

Abstract: Wireless sensor networks (WSNs) have been widely applied in various industrial applications, which involve collecting a massive amount of heterogeneous sensory data. However, most of the data-gathering strategies for WSNs cannot avoid the hotspot problem in local or whole deployment area. Hotspot problem affects the network connectivity and decreases the network lifetime. Hence, we propose a tree-cluster-based data-gathering algorithm (TCBDGA) for WSNs with a mobile sink. A novel weight-based tree-construction method is introduced. The root nodes of the constructed trees are defined as rendezvous points (RPs). Additionally, some special nodes called subrendezvous points (SRPs) are selected according to their traffic load and hops to root nodes. RPs and SRPs are viewed as stop points of the mobile sink for data collection, and can be reselected after a certain period. The simulation and comparison with other algorithms show that our TCBDGA can significantly balance the load of the whole network, reduce the energy consumption, alleviate the hotspot problem, and prolong the network lifetime.