High-performance real-time data processing has become crucial due to the growing need for energy economy and small design in IoT and portable gadgets. This paper describes the design and modeling of a quick and efficient operational transconductance amplifier (OTA) leveraging Carbon Nanotube Field-Effect Transistors (CNTFETs) to meet the demand for rapid signal conditioning in AI-driven sensors. To assess their potential in nanoelectronics, a conventional 32 nm Si-CMOS-based triple cascode OTA (TC-OTA) is thoroughly compared with CNTFET-based designs. The findings demonstrate that the pure CNTFET-TC-OTA version achieves significant performance advantages over its CMOS equivalent, with a 36% reduction in average average power and a 21% improvement in speed. Additionally, with an 84% improve in Power-Delay Product (PDP) and a 124% improvement in Energy-Delay Product (EDP), the CNTFET-based design exhibits exceptional efficiency. The work meticulously evaluates the influence of key design factors on circuit performance, revealing that CNTFET-based circuits exhibit much lower settling times and greater stability. The influences of essential CNT parameters—nanotube diameter (DCNT), pitch (S), number of CNTs (N), Oxide thickness (TOX), and Dielectric constant (KOX) on the OTA energy-delay optimization are systematically and completely examined.
Dinda et al. (Sat,) studied this question.