Design and Comparative Analysis of 7nm SRAM Cells using Double Gate FinFET Technology for Low- Power Memory Applications

As semiconductor technology scales into the deep nanometer regime, Static Random Access Memory (SRAM) cells encounter increasing challenges such as leakage current, read instability, and degraded performance caused by short-channel effects. This paper presents a 7nm Double-Gate (DG) FinFET-based proposed 8T SRAM cell designed to achieve low power consumption and high-speed operation. The proposed architecture improves the conventional 8T SRAM by incorporating an optimized decoupled differential read path and enhanced transistor sizing while preserving the standard eight-transistor configuration. The differential read architecture employs complementary read bit lines (RBL and RBLB), enabling non-destructive read operations with improved sensing accuracy and enhanced Read Static Noise Margin (RSNM). Furthermore, the use of DG FinFET technology provides superior gate control, reduced leakage current, and improved switching characteristics compared with conventional planar CMOS devices.The proposed SRAM cell was designed and simulated using 7nm FinFET technology in the Cadence Virtuoso environment. Simulation results demonstrate significant improvements over the conventional 8T SRAM. The proposed design reduces the write power from 3.340 µW to 1.756 µW (approximately 47.4% reduction) and the read power from 21.94 µW to 4.80 µW (approximately 78.1% reduction). In addition, the write delay is reduced from 2.44 ns to 8.25 ps, while the read delay is slightly improved from 12.77 fs to 12.71 fs. These improvements are achieved through optimized differential read circuitry and transistor sizing without increasing the transistor count. Therefore, the proposed DG FinFET-based 8T SRAM cell offers an efficient combination of low power consumption, high read stability, and high-speed operation, making it well suited for cache memories, embedded processors, Internet of Things (IoT) devices, and other advanced VLSI applications.