Whale Optimization Algorithm for Performance Improvement of Silicon-On-Insulator FinFETs
Geometry parameters, fin height (HFin) and fin width (WFin), critically affect the performance of FinFET devices. These parametric variations have been assessed in the present work by designing silicon-on-insulator (SOI) fin-shaped field effect transistor (FinFET) device with optimum metrics. In this work, the designed devices show diminished Short channel effects and ameliorated analog parameters for the different range of HFin, Lg, and WFin orLg using 3D Visual Technology Computer-Aided Design (TCAD) simulator. Further after training the artificial neural network with a set of parameters and delineating the fitness function, genetic algorithm (GA) and Whale optimization algorithm (WOA) have been implemented. Corresponding to the minimal fitness function, a pair of optimized metrics has been provided in less time using the weighted sum approach. It is observed that the taller and wider fins serve the need of high ION, larger intrinsic gain and a better early voltage whereas narrow fin provides SCEs immunity for device. The results seized through optimization techniques are in good reconciliation with the results of Physical device simulator’s with a deviation less than 7%.
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