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Methane explosion threats the safety in mining, gas recovery and the related downstream industry. The present study examined the suppression effect of KHCO3 (K) modified montmorillonite (K/MMT) inhibitor on reducing the hazard of methane/air mixtures explosion. The characteristic indices of explosion containing the maximum pressure (Pmax), the maximum rate of pressure rise ((dP/dt)max), the time of pressure peak arriving (tmax), were experimentally obtained in a standard 20 L explosion device. The hazard mitigating effect of each modified inhibitor was evaluated. which also elucidated the inhibition mechanism based on the characteristic parameters of K/MMT. Results showed that the K/MMT demonstrates better suppression effect than monomer inhibitor and the maximum decrease of Pmax (34.9 %) and (dP/dt)max (94.4 %) occurs when 45 wt% KHCO3 are loaded (45 wt%-K/MMT). When 45 wt%-K/MMT is used, 0.125 g/L is the optimal concentration to decrease KG to a minimum of 0.849 MPa m/s. This work presents an efficient modified inhibitor by using innovative technology, which is applied to mitigate or prevent disaster. The technology also provides theoretical support and technical guidance for the future development of inhibitors.

As a newly developed material system, graphene-based three-dimensional (3D) architectures have been receiving considerable attention due to their multifunctional properties. Herein, we explore the synergistic effect of combined CdS and graphene hybrids in 3D architectures and investigate their application in electrochemical energy storage. A facile hydrothermal procedure is used to prepare 3D reduced graphene oxide/CdS (RGO/CdS) hydrogels, and three different morphologies of CdS (ball-like, rod-like, needle-like) in the hydrogels are obtained by controlling the synthesis conditions. The results showed that the morphology of CdS significantly affects the electrochemical properties of RGO/CdS. The electrode prepared with needle-like CdS nanoparticles exhibited the highest specific capacitor value of 300 F g−1 at a scan rate of 5 mV s−1, which shows outstanding cycling stability with 94% capacitance retention after 1000 cycles of charge/discharge. These findings demonstrate the possible application of 3D RGO/CdS architectures in energy storage.

Memristor has great application prospects in various high-performance electronic systems, such as memory, artificial intelligence, and neural networks, due to its fast speed, nano-scale dimensions, and low-power consumption. However, traditional nonanalytic models and lately reported analytic models for memristor have the problems of nonconvergence and slow convergence, respectively. These problems lay great obstacles in the analysis, simulation and design of memristor. To address these problems, a modeling methodology for analytic approximate solution of the state variable in memristor is proposed in this work. This methodology solves the governing equation of memristor by adopting the Homotopy Analysis Method (HAM) for the first time, and the convergence performance of the methodology is enhanced by an optimized convergence-control parameter in the HAM. The simulation results, compared with the reported analytic models, demonstrate that the HAM-based modeling methodology achieves faster convergence while guaranteeing sufficient accuracy. Based on the methodology, it can be simultaneously revealed that highly nonlinearity is the potential sources of slow convergence in analytic models, which is beneficial for the analysis and design guidance. In addition, a Spice subcircuit is constructed based on the obtained HAM model, and then it is integrated into an oscillator to verify its applicability. Due to the generality of HAM, this methodology may be easily extended to other memory devices., Comment: 12 pages, 9 figures, 7 tables