中文摘要：

三电极碳纳米管传感器各电极之间的间距大小是影响检测精度的关键因素之一。在用传感器阵列检测多组分气体混合物时,各传感器的极间距很难确定。为三电极碳纳米管气体传感器提出一种基于粒子群算法（PSO）的极间距优化方法。该方法包括设计极间距、组建由不同极间距的多个传感器组成的传感器阵列、建立包括极间距及检测离子电流的数据库、建立混合气体定量分析模型及极间距优化等步骤。采用多组由不同极间距的三个碳纳米管传感器构成的传感器阵列对NO和SO2混合气体进行测量,其中各传感器的极间距均采用上述方法优化。实验结果显示,上述极间距优化方法能够有效地选择电极之间的最佳间距,优化极间距后的传感器也获得了更高的检测灵敏度。

英文摘要：

For triple-electrode carbon nanotube sensor, the electrode separation between electrodes is one of the key factors to influence the accuracy of detection. It is very difficult to decide the sensors＇ electrode separations when detecting the multi-component gas mixture using sensor array. A electrode separation optimization method for triple-electrode carbon nanotube gas sensor was presented. The method is based on particle swarm optimization （PSO） and includes following procedures： designing electrode separation, constructing sensor array using multi-sensor with different electrode separations, building data base including electrode separation and detection ionic current, creating quantitative analysis model of mixed gas, and optimizing electrode separation. The NO and SO2 gas mixtures were detected by multi- group sensor array, which were composed of three carbon nanotube sensors with different electrode separations. The electrode separations of three sensors was optimized using above-mentioned method. The experimental results show that the proposed method is able to select the optimal distances between electrodes effectively and the sensor with optimized electrode separation achieve higher detection accuracy.