Multiple chemical warfare agent simulant decontamination by self-driven microplasma

Low-temperature plasma is a green and high-efficiency technology for chemical warfare agent(CWA)decontamination.However,traditional plasma devices suffer from the problems of highpower composition and large power-supply size,which limit their practical applications.In this paper,a self-driven microplasma decontamination system,induced by a dielectric-dielectric rotary triboelectric nanogenerator(dd-r TENG),was innovatively proposed for the decontamination of CWA simulants.The microplasma was characterized via electrical measurements,optical emission spectra and ozone concentration detection.With an output voltage of-3460 V,the dd-r TENG can successfully excite microplasma in air.Reactive species,such as OH,O(1D),Hαand O3were detected.With input average power of 0.116 W,the decontamination rate of 2-chloroethyl ethyl sulfide reached 100%within 3 min of plasma treatment,while the decontamination rates of malathion and dimethyl methylphosphonate reached(65.92±1.65)%and(60.88±1.92)%after 7 min of plasma treatment,respectively.In addition,the decontamination rates gradually decreased with the increase in the simulant concentrations.Typical products were identified and analyzed.This study demonstrates the broad spectrum and feasibility of the dd-r TENG-microplasma for CWA elimination,which provides significant guidance for their practical applications in the future.

The research of traffic density extraction method under vehicular ad hoc network environment

Purpose–Traffic density is one of the most important parameters to consider in the traffic operationfield.Owing to limited data sources,traditional methods cannot extract traffic density directly.In the vehicular ad hoc network(VANET)environment,the vehicle-to-vehicle(V2V)and vehicle-to-infrastructure(V2I)interaction technologies create better conditions for collecting the whole time-space and refined traffic data,which provides a new approach to solving this problem.Design/methodology/approach–On that basis,a real-time traffic density extraction method has been proposed,including lane density,segment density and network density.Meanwhile,using SUMO and OMNet11 as traffic simulator and network simulator,respectively,the Veins framework as middleware and the two-way coupling VANET simulation platform was constructed.Findings–Based on the simulation platform,a simulated intersection in Shanghai was developed to investigate the adaptability of the model.Originality/value–Most research studies use separate simulation methods,importing trace data obtained by using from the simulation software to the communication simulation software.In this paper,the tight coupling simulation method is applied.Using real-time data and history data,the research focuses on the establishment and validation of the traffic density extraction model.