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16 April 2016 Graphene nanoribbon field effect transistor for nanometer-size on-chip temperature sensor
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Abstract
Graphene has been extensively investigated as a promising material for various types of high performance sensors due to its large surface-to-volume ratio, remarkably high carrier mobility, high carrier density, high thermal conductivity, extremely high mechanical strength and high signal-to-noise ratio. The power density and the corresponding die temperature can be tremendously high in scaled emerging technology designs, urging the on-chip sensing and controlling of the generated heat in nanometer dimensions. In this paper, we have explored the feasibility of a thin oxide graphene nanoribbon (GNR) as nanometer-size temperature sensor for detecting local on-chip temperature at scaled bias voltages of emerging technology. We have introduced an analytical model for GNR FET for 22nm technology node, which incorporates both thermionic emission of high-energy carriers and band-to-band-tunneling (BTBT) of carriers from drain to channel regions together with different scattering mechanisms due to intrinsic acoustic phonons and optical phonons and line-edge roughness in narrow GNRs. The temperature coefficient of resistivity (TCR) of GNR FET-based temperature sensor shows approximately an order of magnitude higher TCR than large-area graphene FET temperature sensor by accurately choosing of GNR width and bias condition for a temperature set point. At gate bias VGS = 0.55 V, TCR maximizes at room temperature to 2.1×10−2 /K, which is also independent of GNR width, allowing the design of width-free GNR FET for room temperature sensing applications.
Conference Presentation
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yaser M. Banadaki, Ashok Srivastava, and Safura Sharifi "Graphene nanoribbon field effect transistor for nanometer-size on-chip temperature sensor", Proc. SPIE 9802, Nanosensors, Biosensors, and Info-Tech Sensors and Systems 2016, 980203 (16 April 2016); https://doi.org/10.1117/12.2219346
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