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Sensitivity Modelling of Graphene Nanoscroll-Based NO2 Gas Sensors

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Abstract

Graphene nanoscrolls (GNSs) as a new category of quasi one-dimensional (1D) belong to the carbon-based nanomaterials, which have recently captivated the attention of researchers. The latest discoveries of exceptional structural and electronic properties of GNSs like high mobility, controllable band gap, and tunable core size have become a great stimuli for graphene researchers. Due to the importance and critical role of nanoscale sensors and biosensors in medical facilities and human life, using a promising material like graphene has been widely studied to achieve better accuracy and sensitivity in these devices. Up until now, the majority of surveys conducted previously have focused on experimental studies for sensors family. Therefore, there is lake of analytical models in comparison to experimental surveys. In order to start and understand about the modelling of gas sensors structure, the field effect transistor(FET)-based structure is employed as a basic. In this study, graphene nanoscroll conductivity has been evaluated under the impacts which is induced by the adsorption of different values of NO2 gas concentration on GNS surface. So that, when GNS-gas sensor is exposed to NO2 gas molecules, the carrier concentration of GNS is changed which leads to the changes in the conductance, and consequently, in the current, this phenomenon is considered as sensing mechanism. The I–V characteristic of graphene nanoscroll-based gas sensor has been considered as a criterion to detect the effect of gas adsorption. In order to verify the accuracy of the proposed model, the results have been compared with the existing experimental works.

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Acknowledgments

The authors would like to acknowledge the financial support from the Research University grant of the Ministry of Higher Education (MOHE), Malaysia, under project Q.J130000.2523.04H99. Also, we would like to thank the Research Management Center (RMC) of the Universiti Teknologi Malaysia (UTM) for providing an excellent research environment where we completed this work.

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  1. Department of Electronic Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310, Skudai, Johor Darul Takzim, Malaysia

    M. Khaledian, Razali Ismail, M. Saeidmanesh & M. Ghadiry

  2. Centre for Artificial Intelligence and Robotics (CAIRO), Universiti Teknologi Malaysia, 81300, Skudai, Johor Bahru, Malaysia

    E. Akbari

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  1. M. Khaledian
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Correspondence to Razali Ismail.

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Khaledian, M., Ismail, R., Saeidmanesh, M. et al. Sensitivity Modelling of Graphene Nanoscroll-Based NO2 Gas Sensors. Plasmonics 10, 1133–1140 (2015). https://doi.org/10.1007/s11468-015-9905-6

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