Research On Molybdenum Disulfide-based Gas Sensor Array And Measurement Model For VOC Gas Detection

In recent years,the problem of gas pollution in indoors and outdoors has become increasingly severe,which has gravely affected people's daily life.Among them,Volatile Organic Compounds?VOC?gases caused widespread concern due to its wide range of species,low concentrations in the air,extensive range of existence and great harm to the human body.Therefore,how to realize component identification and concentration determination of VOC gases,and then take effective measures to control them,which is very important to curb the gas pollution and improve the air quality.This dissertation is devoted to exploring the system of VOC gases detection using nano-modified molybdenum disulfide?MoS₂?sensor array synergy intelligent information processing technology.The paper mainly performed the following research work:on the basis of a one-step hydrothermal route synthesis of metal oxides?MOx?and MoS₂ nanomaterials,nanocomposite film sensors were prepared by two-step hydrothermal method and layer-by-layer assembly techniques.Meanwhile,the surface morphology,lattice structure and specific surface area of the films were analyzed by XRD,SEM,TEM and other characterization techniques.Subsequently,the properties of three kinds of nanocomposite film sensors?Co₃O₄/MoS₂,Pd-TiO₂/MoS₂ and In₂O₃/MoS₂?toward VOC gases?represented by NH₃,HCHO and C₆H₆?were investigated,including the sensitivity,stability,selectivity,etc.Moreover,the sensitive mechanism of the nano-modified MoS₂ composite films to the target gases was analyzed from the band structure of the heterojunction as well as the charge transfer between the films.At the same time,high-performance nano-modified MoS₂ sensing devices were screened to construct sensor array,and obtained the multi-dimensional response data of the sensor array under mixed VOC gas environment.Finally,a VOC gas prediction model based on nano-modified MoS₂ sensor array synergy least squares support vector machine?LSSVM?was constructed.The LSSVM parameters were optimized by two optimization algorithms:Particle swarm optimization?PSO?and Bayesian evidence framework.After evaluating the predictive performances of different models,find that the Bayesian-LSSVM model has achieved satisfactory results in the identification and concentration prediction of mixed VOC gas components.Based on the research route of"new material-new device-new methods-new application",this paper focused on exploring the gas sensing characteristics of the nano-modified MoS₂ sensor.In addition,a synergetic intelligent algorithm model of gas sensing arrays based on nano-modified MoS₂ was constructed and applied to multi-component mixed VOC gas detection,it has opened up new application fields for the film gas sensor and also provided a new idea for developing a novelty VOC gas detection device.