Performance Optimization of Broadwell-Y Shaped Transistor Using Artificial Neural Network and Moth-Flame Optimization Technique

Majlesi Journal of Electrical Engineering

مقاله 8، دوره 12، شماره 1، خرداد 2018، صفحه 61-69   

نوع مقاله: Review Article

نویسندگان

Navneet Kaur^{* 1}؛ Munish Rattan²؛ Sandeep Gill²

¹I. K. Gujral Punjab Technical University, Jalandhar, Punjab, India

²Guru Nanak Dev Engineering College, Ludhiana, Punjab, India

چکیده

FinFETs are the emerging 3D-transistor structures due to strong electrostatic control of active channel by gate from more than one side which was not possible in conventional transistor. FinFET structures with rectangular and trapezoidal shape have been excessively analyzed in literature. In this work, FinFET with Broadwell-Y shape proposed by Intel, has been designed and simulated in Technology Computer Aided Design (TCAD). The performance of the designed device was optimized using Moth Flame Optimization (MFO) after the network was trained through Artificial Neural Network (ANN). Results obtained from MATLAB were in close agreement with those obtained from TCAD simulations. Output parameters like leakage current (IOFF) of 2.407e-12, On-Off current ratio (ION/IOFF) of 4.5e06, Subthreshold Swing (SS) of 65.4mV/dec and Drain Induced Barrier Lowering (DIBL) of 37.9mV/V were obtained after optimization. Short channel effects are improved for 20nm gate length as SS is close to ideal value 60mV/dec and DIBL is below 100mV/V which makes this designed structure a good option for nanoscale applications.

کلیدواژه‌ها

FinFET؛ Moth-Flame Optimization (MFO)؛ Artificial Neural Network (ANN)؛ Drain Induced Barrier Lowering (DIBL)؛ Subthreshold Swing (SS)؛ Leakage Current؛ TCAD؛ MATLAB؛ Fin height؛ Gate length

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