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We report for the first time a zero-strain cathode, Na4Fe7(PO4)6, for sodium–ion batteries (SIBs). This new iron-based polyanionic cathode delivers a reversible capacity of 66.5 mA h g−1 at 5 mA g−1 with almost 100% capacity retention over 1000 cycles under 200 mA g−1, and the outstanding performance benefits from single-phase-transition processes with a tiny volume change of only ∼0.24%.

We report for the first time a zero-strain cathode, Na

Metal borohydrides have received increasing research interests on account of their high hydrogen storage capacities. In this paper, zinc borohydride Zn(BH4)2 was synthesized using NaBH4 and ZnCl2 in THF under room temperature for 72 h, and the crystallographic constitution of the synthesized products were analyzed by XRD. The results showed that the major phase of the products was NaCl, alternatively, NaBH4 or ZnCl2 disappeared. This concluded the formation of Zn(BH4)2. Moreover, both experiment phenomena and fired products further confirmed the synthesis of Zn(BH4)2, which a XRD pattern of Zinc borohydride was obtained.

With the development of cloud computing, big data and other emerging Technology, the integration of cloud technology and multi-robot system makes it possible to make the multi robot system with high performance and high complexity. This paper briefly describes the concept and development process of the cloud robot and the overall architecture of the cloud robot system. In this paper, the major elements of cloud robot are analyzed from the point of view of big data, cloud computing, open source resources and robot cooperative learning. The key problems to be solved in the current cloud robot system are proposed. Finally, we prospect the future development of the cloud robot.

With the development of cloud computing, big data, and other emerging technologies, the integration of cloud technology and multi-robot systems makes it possible to design multi-robot systems with improved energy efficiency, high real-time performance, and low cost. In order to address the potential of clouds in enhancing robotics for industrial systems, this paper describes the basic concepts and development process of cloud robotics and the overall architecture of these systems. Then, the major driving forces behind the development of cloud robotics are carefully analyzed from the point of view of cloud computing, big data, open source resources, robot cooperative learning, and network connectivity. Subsequently, the key issues and challenges in the current cloud robotic systems are proposed, and some possible solutions are also given. Finally, the potential value of cloud robotic systems in different practical applications is discussed.

In recent years, there have been great advances in industrial Internet of Things (IIoT) and its related domains, such as industrial wireless networks (IWNs), big data, and cloud computing. These emerging technologies will bring great opportunities for promoting industrial upgrades and even allow the introduction of the fourth industrial revolution, namely, Industry 4.0. In the context of Industry 4.0, all kinds of intelligent equipment (e.g., industrial robots) supported by wired or wireless networks are widely adopted, and both real-time and delayed signals coexist. Therefore, based on the advancement of software-defined networks technology, we propose a new concept for industrial environments by introducing software-defined IIoT in order to make the network more flexible. In this paper, we analyze the IIoT architecture, including physical layer, IWNs, industrial cloud, and smart terminals, and describe the information interaction among different devices. Then, we propose a software-defined IIoT architecture to manage physical devices and provide an interface for information exchange. Subsequently, we discuss the prominent problems and possible solutions for software-defined IIoT. Finally, we select an intelligent manufacturing environment as an assessment test bed, and implement the basic experimental analysis. This paper will open a new research direction of IIoT and accelerate the implementation of Industry 4.0.