A coverage optimization method is suggested to improved node coverage in wireless sensor networks (WSNs), decrease node redundancy, and lengthen network lifetime, this method is based on the adaptive grey wolf arithmetic optimization algorithm The exploitation and exploration are first balanced using a cosine acceleration function. Then, to boost the method's performance, the grey wolf optimizer and arithmetic optimization algorithm are combined. In comparison to the conventional coverage optimization algorithm, our simulation results could improve arithmetic optimization algorithm has higher convergence efficiency and coverage rate, decreases network loss, and significantly lengthens the network life cycle.
Organic-inorganic hybrid halide perovskites have great potential in solar cells, but they suffer from moisture-induced instability. In this study, we developed a natural material-- tetracosanoic acid (TA) to modify the surface of CH3NH3PbI3 perovskite films to enhance the moisture stability. The power conversion efficiency (PCE) of the TA modified perovskite solar cells (PSCs) retained ~85% of their initial PCE when stored for 20 days at a relative humidity of 25% at 25°C, whereas a pristine cell only retained 54% of its initial value. Our findings demonstrated a simple, inexpensive, and environmentally friendly method to improve moisture stability of PSCs.
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