Adsorption dynamics of CVD graphene investigated by a contactless microwave method
Adsorption dynamics of CVD graphene investigated by a contactless microwave method
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DOI：
10.1088/2053-1583/aac231
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发表时间：
2018-05
期刊：
影响因子：
5.5
通讯作者：
N. Black;I. Rungger;B. Li;S. A. Maier;L. Cohen;J. Gallop;L. Hao
中科院分区：
文献类型：
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作者：
N. Black;I. Rungger;B. Li;S. A. Maier;L. Cohen;J. Gallop;L. Hao
利用非接触式微波介质谐振腔气体传感平台，研究了空气中NO2气体在石墨烯表面的吸附动力学。微波的使用消除了传统电导率测量所必需的金属触点的需要，因此可以无创地测定NO2浓度至百万分之一。因此，消除了金属触点附近的气体-金属相互作用和局部石墨烯掺杂，其优点是只有石墨烯-气体吸附物相互作用负责测量信号。我们表明，所有考虑浓度的传感器响应可以使用依赖于表面覆盖的Langmuir模型来描述。我们证明，通常被认为是主要参数的NO2结合能的可能变化，与随着NO2覆盖率的增加而上升的吸附能屏障相比，只起次要作用。我们的开尔文探针和拉曼表面分析支持了理论模型中使用的石墨烯吸附位点性质的连续分布。我们的研究结果表明，非侵入式微波方法是一种很有前途的气体传感替代平台。此外，它为理解基于石墨烯的气体传感器中发生的微观过程提供了有价值的见解，这是实现可重复和优化器件性能的关键因素。
We use a contactless microwave dielectric resonator gas sensing platform to study the adsorption dynamics of NO2 gas present in air onto a graphene surface. The use of microwaves removes the need for metal contacts that would otherwise be necessary for traditional conductivity measurements, and therefore allows non-invasive determination of NO2 concentrations to sub parts per million. As a result, gas−metal interactions and localised graphene doping in the vicinity of metal contacts are eliminated, with the advantage that only graphene−gas adsorbate interactions are responsible for the measured signal. We show that the sensor response for all considered concentrations can be described using a surface coverage dependent Langmuir model. We demonstrate that the possible variation of the NO2 binding energy, which is frequently considered as the main parameter, plays only a secondary role compared to the rising adsorption energy barrier with increasing NO2 coverage. The continuous distribution of the properties of the graphene adsorption sites used in the theoretical model is supported by our Kelvin probe and Raman surface analysis. Our results demonstrate that the non-invasive microwave method is a promising alternative platform for gas sensing. Moreover it provides valuable insights towards the understanding of the microscopic processes occurring in graphene based gas sensors, which is a key factor in the realization of reproducible and optimized device properties.