Optimization of n-MOS 6T Nanowire SRAM Bit Cell Based on Nanowires Ratio of SiNWTs

In nowadays technology, the primary memory structure widely used in many digital circuit applica-tions is a six transistor (6T) Static Random Access Memory (SRAM) bit cell. The main reason for minimizing memory bit cell to nanodimensions is to provide the SRAM integrated circuits (ICs) with the possible largest memory size per one chip, and the main unit in 6T SRAM bit cell is the MOSFET. One of the new MOSFET structures that overcome conventional MOSFET structure problems under minimization towards nanodimension is the silicon nanowire transistor (SiNWT). This study is the first to explore and optimize the nanowire ratio of driver to load (kdikl) for a six n-channel SiNWT-based SRAM bit cell. The MuGFET simulation tool has been used to calculate the output characteristics of each transistor individually, and then these characteristics are implemented in the MATLAB software to produce the final static butterfly and current characteristics of nanowire 6T-SRAM bit cell. The demonstration of the driver to load transistors’ nanowires ratio optimizations of nanoscale n-type SiNWT-based SRAM bit cell has been discussed. In this research, the optimization of kdiklwill strongly depend on inflection voltage and high and low noise margins (NMs) of butterfly characteristics. The improvement of NMs of butterfly characteristics has been done by increasing the drain current (Ids) of the driver transistor. Also, the optimization in principle will depend on whether NMs are equal and high, and the inflection voltage (Vinf) is near to Vddl2 values as possible. These principles have been used as limiting factors for optimization. The results show that the optimization strongly depends on the nanowire ratio, and the best ratio was kdikl= 4. The increase in kdikl leads to a continuous increase in nmh,acceptable nmland low percentage increment of static power consumption (AP %) at kdikl= 4.