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Starting from the conventional boundary of complementary metal oxide semiconductor (CMOS), the researcher introduced QCA, an approach to quantizing a cellular automata model. The minimal feature size on an atomic scale, ultralow power consumption, and ultrahigh speed make QCA more lucrative in this field of nano-research world. This nanoscale technique is more prone to errors because of its small size and meticulous construction method. Numerous research publications have addressed defects in QCA circuits, and this work has investigated the defect characterization of QCA logic gates along with predictive modelling. This paper describes how machine learning-based models are being developed to evaluate the dissipated energy of layered T QCA universal logic gates with single-cell displacement defect (SCDD) and cell polarization in a novel method.

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Predictive Modelling of QCA Universal Gate Energy Dissipation on Single-Cell Displacement Defect

  • 会议论文

  • 发表日期：

    2025年

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  • Manali Dhar,
  • Debasmita Manna,
  • Ananya Banerjee,
  • Saradindu Panda,
  • Bansibadan Maji

摘要

Starting from the conventional boundary of complementary metal oxide semiconductor (CMOS), the researcher introduced QCA, an approach to quantizing a cellular automata model. The minimal feature size on an atomic scale, ultralow power consumption, and ultrahigh speed make QCA more lucrative in this field of nano-research world. This nanoscale technique is more prone to errors because of its small size and meticulous construction method. Numerous research publications have addressed defects in QCA circuits, and this work has investigated the defect characterization of QCA logic gates along with predictive modelling. This paper describes how machine learning-based models are being developed to evaluate the dissipated energy of layered T QCA universal logic gates with single-cell displacement defect (SCDD) and cell polarization in a novel method.