2022
DOI: 10.1088/1742-6596/2327/1/012011
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High Performance Mixed Logic Decoders using MOS like GNRFET in 22nm Technology

Abstract: Graphene nano ribbon field effect transistor is an emerging field of research in VLSI technology beyond 32nm. VLSI main motive is to reduce power consumption and other parameters such as delay, PDP (power delay product) to improve the efficiency. This article discusses the requirement for high-performance applications that use little power. However, employing low-power devices for high-rank applications such as microprocessors, digital signal processors, and static random-access memory (SRAM) is very challengi… Show more

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Cited by 2 publications
(1 citation statement)
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“…The increasing significance of static power dissipation, a by-product of transistor leakage in scaled-down VLSI technologies, necessitates a re-evaluation of conventional design methodologies [4]. A paradigm shifts toward adder architectures that minimize both dynamic and static power is imperative to surmount the escalating power constraints in modern digital circuits [5]. This paper seeks to advance the current state of adder designs by proposing a novel architecture that not only enhances power efficiency but also maintains computational integrity across various operational states which is the drawback of various PTL based adders.…”
Section: Introductionmentioning
confidence: 99%
“…The increasing significance of static power dissipation, a by-product of transistor leakage in scaled-down VLSI technologies, necessitates a re-evaluation of conventional design methodologies [4]. A paradigm shifts toward adder architectures that minimize both dynamic and static power is imperative to surmount the escalating power constraints in modern digital circuits [5]. This paper seeks to advance the current state of adder designs by proposing a novel architecture that not only enhances power efficiency but also maintains computational integrity across various operational states which is the drawback of various PTL based adders.…”
Section: Introductionmentioning
confidence: 99%