Studies of short channel effects and
Performance enhancement of nano-mosfet Based on multi-objective genetic algorithm Approach

Abstract

The nano-scale devices face a major issue i.e Short Channel Effects, as a result of which the performance of the devices degrade. To enhance the performance of such devices, the SCEs should be reduced. This thesis contributes to enhance the performance of nano-scaled DG MOSFET by re-ducing the short channel effects. To approach towards the main objective of the thesis, a study has been done on analytical modeling of undoped symmetric DG MOSFET. Then, to get the picture of SCEs, the electrical parameters such as maximum Drain current(Ion),Leakage current(Ioff ), Sub threshold Swing (SS), Threshold voltage (Vth ), and Drain In-duced Barrier Lowering (DIBL) are analytically derived by solving 2-dimensional Poisson’s equation and the same are studied with the variation of design parameters such as L, tsi and tox. To validate such analytical models, SCEs are studied using ATLAS device simulator. Graded Cannel engineering techniques are used for reduction of SCEs. For further reduction or minimization of SCEs, a multi-objective optimization technique is used to enhance the accuracy with optimum design parameters. To validate the optimized structure, a simulated model is built with those optimized values of the design parameter and the performance of the device is compared with the existing result [32].