Controlling chaos in a chaotic neural network

The chaotic neural network constructed with chaotic neuron shows the associative memory function, but its memory searching process cannot be stabilized in a stored state because of the chaotic motion of the network. In this paper, a pinning control method focused on the chaotic neural network is proposed. The computer simulation proves that the chaos in the chaotic neural network can be controlled with this method and the states of the network can converge in one of its stored patterns if the control strength and the pinning density are chosen suitable. It is found that in general the threshold of the control strength of a controlled network is smaller at higher pinned density and the chaos of the chaotic neural network can be controlled more easily if the pinning control is added to the variant neurons between the initial pattern and the target pattern

Triboelectrification-Enabled Self-Powered Detection and Removal of Heavy Metal Ions in Wastewater

route that works in a self-powered manner by harnessing the ambient energy using the triboelectrification effect. Relying on modified anodic aluminum oxide (AAO) a nanoporous surface with a layer of appropriate ligand molecules, serving as recognition element, the as-developed tribo-nanosensors can selectively capture and detect Cu 2+ , Pb 2+ , and Cr 3+ , which are commonly existing toxic heavy metal ions in industrial wastewater, in a sensing range of 0-200 × 10 −6 m with a sensitivity of 0.005 × 10 −6 , 0.003 × 10 −6 , and 0.004 × 10 −6 m −1 , respectively. The presented tribo-nanosensors are also proved to possess good stability after continuous working for up to 50,000 cycles. Moreover, the ambient triboelectrification effect was further utilized to develop a water-driven triboelectric nanogenerator (WD-TENG) as a sustainable power source for heavy metal ion removal by recycling the kinetic energy from flowing wastewater. The self-provided electric field can boost the migration and combination of ions as well as the electrolysis effect. The later induced a generation of large amount of OH − at the cathode in the wastewater, which promoted the precipitation of heavy metal ions. By controlling the wastewater pH values, Cu 2+ , Pb 2+ , and Cr 3+ were demonstrated to be fractionally precipitated from the wastewater. Under a fixed water flow rate of 3 L min −1 and initial heavy metal ion concentration of 100 × 10 −6 m, the self-powered cleaning system was capable of removing 97.4% of the heavy metal ions in the wastewater in 100 min. In addition, a further step was taken to recycle and collect the precipitated metals. Through a filtration, acidification, and chemical reduction process, pure metals are respectively obtained, which realizes the clean production and recycling economy. Featured as high detection sensitivity and removal efficiency, cost-effectiveness, simplicity as well as stability, the reported work not only opens a new and innovative pathway to environmentally friendly treatment of the ambient heavy metal ions, but also promotes substantial advancements in the fields of clinical toxicology, immunological surveillance, environmental monitoring, industrial waste management, and recycling economy. The triboelectrification enabled self-powered heavy metal ion treatment systematically consists of two steps, a tribonanosensor for metal ion detection and a water-driven triboelectric nanogenerator for metal ion removal. As demonstrated i