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

Authors Yasir Hashim1, Waheb A. Jabbar2

1Department of Computer Engineering, Tishk International University (TIU), Erbil, Iraq

2Faculty of Electrical and Electronics Engineering Technology, Universiti Malaysia Pahang (UMP), Malaysia


Е-mail yasir.hashim@ieee.org
Issue Volume 12, Year 2020, Number 5
Dates Received 27 June 2020; revised manuscript received 15 October 2020; published online 25 October 2020
Citation Yasir Hashim, Waheb A. Jabbar, J. Nano- Electron. Phys. 12 No 5, 05020 (2020)
DOI https://doi.org/10.21272/jnep.12(5).05020
PACS Number(s) 62.23.Hj, 87.85.Dh
Keywords SRAM (4) , SiNWT (2) , Nanowire (12) , N-MOS, Memory cell.

In nowadays technology, the primary memory structure widely used in many digital circuit applications 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 (KD/KL) 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 KD/KL will 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 Vdd/2 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 KD/KL  4. The increase in KD/KL leads to a continuous increase in NMH, acceptable NML and low percentage increment of static power consumption (ΔP %) at KD/KL  4.

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