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

  • Navneet Kaur I. K. Gujral Punjab Technical University, Jalandhar, Punjab, India
  • Munish Rattan Guru Nanak Dev Engineering College, Ludhiana, Punjab, India
  • Sandeep Singh Gill Guru Nanak Dev Engineering College, Ludhiana, Punjab, India
Keywords: 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.


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.


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How to Cite
Kaur, N., Rattan, M., & Gill, S. (2018). Performance Optimization of Broadwell-Y Shaped Transistor Using Artificial Neural Network and Moth-Flame Optimization Technique. Majlesi Journal of Electrical Engineering, 12(1), 61-69. Retrieved from