Influence of chamber design on the gas sensing performance of graphene field-effect-transistor

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Abstract

We report on the influence of chamber design on the gas sensing performance of a graphene field-effect-transistor (GFET). A conventional chamber (V = 400 ml) and a cap chamber (V = 1 ml), were used to perform dynamic measurements on a GFET. To gain a-priori knowledge on the gas flow in the chambers, Naiver–Stokes and convection-diffusion equations were numerically-solved using COMSOL Multiphysics. We numerically and experimentally observed two main factors that can affect the GFET performance: (1) the gas flow direction through the chamber and (2) the chamber volume. At 5-min exposure time, at least 200% higher GFET sensitivity was calculated from the cap chamber, which is expected since the conventional chamber is 400 times larger. Interestingly, even when the conventional chamber is fully saturated (at 90-min exposure time), the GFET sensitivity in the cap chamber is still better by 28.57%. We attributed this behavior to the swirling vapor flow in the cap chamber brought about by the U-shaped path. This effect causes multiple interaction of H2O molecules with the GFET, resulting to higher computed sensitivity. However, at higher relative humidity, the GFET becomes populated, reducing the number of H2O molecules that can re-interact with the sensor. In terms of GFET transient characteristics, a 154% and 86.9% faster response and recovery, respectively, were observed in the cap-design. This was due to its smaller volume that minimized poorly purged region in the chamber. But if the chambers have the same volumes, we may infer a faster GFET response and recovery from the conventional chamber where the gas flow is unperturbed. These results could contribute in designing a time efficient and cost-effective gas sensing system.

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Lopez, L., Copa, V., Hayasaka, T., Faustino-Lopez, M. A., Wu, Y., Liu, H., … Salvador, A. (2020). Influence of chamber design on the gas sensing performance of graphene field-effect-transistor. SN Applied Sciences, 2(7). https://doi.org/10.1007/s42452-020-2676-5

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