Structure optimization of carbon nanotube ionization sensor based on fluid model

Abstract

Compared with the traditional ionization sensor, triple electrode ionization gas sensor based on carbon nanotubes features excellent performances of small size and low operation voltage, and plays an important role in developing smart grids and the ubiquitous Internet of Things. However, they exhibit the disadvantages of small collecting current and low sensitivity, and need to be optimized in structure. Based on the Townsend discharge mechanism and three governing equations of particle mass conservation, electron energy conservation and Poisson equations, a two-dimensional plasma discharge fluid simulation model of the sensor is established by using the COMSOL Multiphysics software. According to gas composition, component concentration, structure of the sensor and voltage applied to the electrodes, we determine the chemical reaction, reaction rate coefficient, field control equation, initial values and boundary conditions. In order to calculate the interior distribution of charged particles inside the boundary, the inter-electrode space region is meshed. Initial values of mesh are set, such as a dense mesh of nano-meter length around the electrode having micro-nano structure, and a rough mesh of micro-meter length in the other region of inter-electrode space. The initial values of time-step are set for each mesh grid, and the discharge model of each mesh grid is numerically solved by the finite volume method. The three linkage governing equations are discretized and calculated iteratively in time and space, and the mesh values and time-steps are adjusted to make the results converged. The electrostatic field distribution and the average collecting current density of the eight kinds of sensors are obtained in the background gas of nitrogen. The optimal sensor structure is obtained by comparing the electric field intensities and current densities under different structure parameters. The eight kinds of the sensors are prepared for experimentally verifying the optimization method. The optimal structure of the 7# sensor has the highest collecting current density in the eight kind structures, which is consistent with the simulation results, and proves the feasibility of the structure optimization method proposed in the paper. Based on the optimal structure, the sensors, respectively with the electrode spacings of 100 and 120 μm, are fabricated, and the response characteristics of NO/SO<sub>2</sub> mixture gas are obtained. Compared with other technologies, the sensor with optimal structure exhibits 1－2 orders of sensitivity higher than the others. The optimized triple electrode ionization sensor based on carbon nanotubes exhibits many potential applications.