Development of Gas Sensor Model for Detection of NO2 Molecules Adsorbed on Defect-Free and Defective Graphene

Development of Gas Sensor Model for Detection of NO2 Molecules Adsorbed on Defect-Free and Defective Graphene

Meisam Rahmani (Universiti Teknologi Malaysia, Malaysia), Komeil Rahmani (Islamic Azad University, Iran), Mohammad Javad Kiani (Islamic Azad University, Iran), Hediyeh Karimi (Swinburne University of Technology, Australia), Elnaz Akbari (Universiti Teknologi Malaysia, Malaysia), Mohammad Taghi Ahmadi (Universiti Teknologi Malaysia, Malaysia & Urmia University, Iran) and Razali Ismail (Universiti Teknologi Malaysia, Malaysia)
DOI: 10.4018/978-1-5225-0736-9.ch008
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Abstract

A wide popularity has been generated by graphene as a result of fundamental scientific interest in nano-materials. Graphene-based nanostructure then possess a wide range of special physical uniqueness which can be used in many types of applications including some categories of sensors like optical, magnetic, electronic field, strain and mass sensors as well as field-effect, electrochemical and piezoelectric gas sensors. Graphene is believed to be a fantastic sensor material because of its single atomic layer of graphite with surface.
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Introduction

A wide popularity has been generated by graphene as a result of fundamental scientific interest in nano-materials (Zheng, 2008). Graphene-based nanostructure then possess a wide range of special physical uniqueness which can be used in many types of applications including some categories of sensors like optical, magnetic, electronic field, strain and mass sensors as well as field-effect, electrochemical and piezoelectric gas sensors (Hill, 2011; Huang, 2011). As shown in Figure 1, graphene is believed to be a fantastic sensor material because of its single atomic layer of graphite with surface. This assumption is because of the ease with which the electronic features of the graphene can be adjusted by the directly interaction between each atom in the structure and the sensing environment. Therefore, the interaction between the surface dopants and absorbents can be maximized. It is evident to date that graphene-based sensors can be achieved with best sensor-performance out of graphene (Hill, 2011; Huang, 2011; Ko et al., 2010).

Figure 1.

Graphene as a fantastic sensor material

Theoretical study on the adsorption of gas molecules on monolayer graphene has proved that the sensitivity can be improved by doping in carbon nanostructures (Anupama, 2009). This does not only increase the sensitivity of the adsorption process of graphene, but also lowers nonspecific binding and elevates sensitivity for the desired analysis (Ratinac, 2010; Miao, 2011; Dankerl, 2010). Furthermore, a few of the fictionalization method evolved for other set of gas sensors, particularly for single-walled carbon nanotubes, will likely get applications in the graphene-based gas sensors of the future (Yong-Hui et al., 2009). There is a broad knowledge of physics and chemistry behind NO2 physisorptions or chemisorptions on doped graphene; in addition, magnetic pairing between adsorbed paramagnetic molecules is critical for its applications in electronics (Dong, 2009). Graphene is sensitive to the adsorption of NO2 because of its transport properties and the system displays n-type semiconducting property after NO2 adsorption (Tang, 2011; Chen, 2011). Based on quantum transport calculations, NO2 molecules can be differentiated from another gas molecules by the graphene-based sensors (Anupama, 2009; Zhang, 2009). The extraordinary mobility of carriers in graphene has been used to explain its high sensitivity, which provides extremely low noise sensing at room temperature (Jesse, et al., 2009). Figure 2 indicates the schematic diagram of gas sensing used in our study. Small-width graphene field effect transistor (FET) in the structure of NO2 sensor with the assumption of ballistic carrier transportation in channel is supposed. A major strength of adopting graphene as a channel material is due to its strong capability to control the electrostatics and hence expected to reduce the short channel effects that rely on the device electrostatics (Dankerl, 2010; Dong, 2010; Wang, 2010; Cohen-Karni, 2010).

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