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Analysis and optimization of carbon nanotubes and graphene sensors based on adsorption-desorption kinetics

机译:基于吸附-解吸动力学的碳纳米管和石墨烯传感器的分析和优化

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摘要

Single-walled carbon nanotubes mats and graphene have shown great potential as gas sensors. We analyze NO adsorption/sensing experiments with the kinetic Langmuir model adapted to include adsorption sites from which the molecule does not desorb. The model reproduces the available experimental data. Its fitting parameters provide information on the microscopic phenomena governing adsorption, and variation of these parameters allows the optimization of the sensitivity, detection limit, and time response of the sensors. The result reveals an optimal operating temperature before thermal desorption becomes dominant at high temperature, the potential improvement of selectivity by tuning the gate voltage in a field effect transistor configuration, and quantifies the benefits of reducing the density of defects in the sensing materials.
机译:单壁碳纳米管垫和石墨烯已显示出作为气体传感器的巨大潜力。我们使用动力学Langmuir模型分析NO吸附/传感实验,该模型适用于包括分子不会解吸的吸附位点。该模型会复制可用的实验数据。它的拟合参数提供了有关控制吸附的微观现象的信息,这些参数的变化可以优化传感器的灵敏度,检测极限和时间响应。结果揭示了在高温下热脱附成为主导之前的最佳工作温度,通过调节场效应晶体管配置中的栅极电压来选择性提高的潜在潜力,并量化了降低传感材料中缺陷密度的益处。

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