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Toward high‐temperature lithium‐ion batteries, adding inorganic materials are proposed as an effective strategy. However, inorganic particles tend to aggregate in the polymer matrix, causing degradation in battery performance. Here, a PVDF‐HFP/colloidal Al2O3 composite separator is prepared with a phase inverse method. The colloidal Al2O3 particles well dispersed in the PVDF‐HFP polymer matrix substantially enhance the mechanical strength of the PVDF‐HFP separator. The PVDF‐HFP/colloidal Al2O3 composite separator owns a high electrolyte uptake of 372%, a high ionic conductivity of 1.3 × 10−3 S cm−1 at 80 °C and delivers high capacity retention of 95.6% after 100 charge–discharge cycles at 0.5 C. In addition, PVDF‐HFP/colloidal Al2O3 separator only has a 4.5% thermal shrinkage at 150 °C and exhibits high electrochemical performances upon annealing at 140 °C.

Gas sensor, as one of the most important devices to detect noxious gases, provides a vital way to monitor the concentration and environmental information of gas in order to guarantee the safety of production. Therefore, researches on high sensitivity, high selectivity, and high stability have become hot issues. Since the discovery of the nanomaterial, it has been increasingly applied to the gas sensor for its distinguishing surface performances. However, 0-D and 1-D nanomaterials, with limited electronic confinement effect and surface effect, cannot reach the requirement for the production of gas sensors. This paper gives an introduction about the current researching progress and development trend of 2-D nanomaterials, analyzes the common forms of 2-D nanoscale structure, and summarizes the mechanism of gas sensing. Then, widely concerned factors including morphological properties and crystalline structure of 2-D nanomaterial, impact of doped metal on the sensibility of gas sensors, impact of symmetry, and working temperature on the selectivity of gas sensors have been demonstrated in detail. In all, the detailed analysis above has pointed out a way for the development of new 2-D nanomaterial and enhancing the sensibility of gas sensors.

In recent years, blockchains have obtained so much attention from researchers, engineers, and institutions; and the implementation of blockchains has started to revive a large number of applications ranging from e-finance, e-healthcare, smart home, Internet of Things, social security, logistics and so forth. In the literature on blockchains, it is found that most articles focused on their engineering implementation, while little attention has been devoted to the exploration of theoretical aspects of the system; however, the existing work is limited to model the mining process only. In this paper, a queuing theory-based model is proposed for understanding the working and theoretical aspects of the blockchain. We validate our proposed model using the actual statistics of two popular cryptocurrencies, Bitcoin and Ethereum, by running simulations for two months of transactions. The obtained performance measures parameters such as the Number of Transactions per block, Mining Time of Each Block, System Throughput, Memorypool count, Waiting Time in Memorypool, Number of Unconfirmed Transactions in the Whole System, Total Number of Transactions, and Number of Generated Blocks; these values are compared with actual statistics. It was found that the results gained from our proposed model are in good agreement with actual statistics. Although the simulation in this paper presents the modeling of blockchain-based cryptocurrencies only, the proposed model can be used to represent a wide range of blockchain-based systems.

Integration of blockchain and Internet of Things (IoT) to build a secure, trusted and robust communication technology is currently of great interest for research communities and industries. But challenge is to identify the appropriate position of blockchain in current settings of IoT with minimal consequences. In this article we propose a blockchain-based DualFog-IoT architecture with three configuration filter of incoming requests at access level, namely: Real Time, Non-Real Time, and Delay Tolerant Blockchain applications. The DualFog-IoT segregate the Fog layer into two: Fog Cloud Cluster and Fog Mining Cluster. Fog Cloud Cluster and the main cloud datacenter work in a tandem similar to existing IoT architecture for real-time and non-real-time application requests, while the additional Fog Mining Cluster is dedicated to deal with only Delay Tolerant Blockchain application requests. The proposed DualFog-IoT is compared with existing centralized datacenter based IoT architecture. Along with the inherited features of blockchain, the proposed model decreases system drop rate, and further offload the cloud datacenter with minimal upgradation in existing IoT ecosystem. The reduced computing load from cloud datacenter doesn't only help in saving the capital and operational expenses, but it is also a huge contribution for saving energy resources and minimizing carbon emission in environment. Furthermore, the proposed DualFog-IoT is also being analyzed for optimization of computing resources at cloud level, the results presented shows the feasibility of proposed architecture under various ratios of incoming RT and NRT requests. However, the integration of blockchain has its footprints in terms of latent response for delay tolerant blockchain applications, but real-time and non-real-time requests are gracefully satisfying the service level agreement. INDEX TERMS Blockchain, Internet of Things, fog layer, DualFog-IoT, quality of service (QoS).