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The design, analysis, and cost estimation of a generic adder and subtractor using the layered T (LT) logic reduction methodology with a quantum-dot cellular-automata-based approach

Published: 01 August 2021 Publication History

Abstract

The quantum-dot cellular automata (QCA) is considered to be one of the ground-breaking nanotechnologies developed over the last two decades. A layered T (LT) logic cell library is constructed herein, and the methodology is extended to generic adder and subtractor module designs. The two proposed algorithms lead to more efficient QCA layout designs for an n-bit ripple carry adder (RCA) and subtractor based on an effective clock zone assignment approach. The suggested one-, four-, and eight-bit RCAs and subtractors surpass most of their existing counterparts by offering lower effective area and cell complexity. A comparative analysis is presented regarding the complexity, irreversible power dissipation, and Costα of the proposed n-bit layouts from a cost estimation purview.

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  • (2024)Predicting Energy Dissipation in QCA-Based Layered-T Gates Under Cell Defects and Polarisation: A Study with Machine-Learning ModelsJournal of Electronic Testing: Theory and Applications10.1007/s10836-024-06133-740:4(435-455)Online publication date: 21-Aug-2024

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          Published In

          cover image Journal of Computational Electronics
          Journal of Computational Electronics  Volume 20, Issue 4
          Aug 2021
          176 pages

          Publisher

          Springer-Verlag

          Berlin, Heidelberg

          Publication History

          Published: 01 August 2021
          Accepted: 17 April 2021
          Received: 01 June 2020

          Author Tags

          1. Quantum-dot cellular automata (QCA)
          2. Layered T gate
          3. Adder and subtractor
          4. Complexity
          5. Irreversible power dissipation (IPD)
          6. Costα

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          • (2024)Predicting Energy Dissipation in QCA-Based Layered-T Gates Under Cell Defects and Polarisation: A Study with Machine-Learning ModelsJournal of Electronic Testing: Theory and Applications10.1007/s10836-024-06133-740:4(435-455)Online publication date: 21-Aug-2024

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