Performance comparison and analysis of silicon-based and carbon-based integrated circuits under VLSI

Jianhao Wu

doi:10.54254/2755-2721/39/20230605

Research Article

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Published on 21 February 2024

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Wu,J. (2024). Performance comparison and analysis of silicon-based and carbon-based integrated circuits under VLSI. Applied and Computational Engineering,39,244-250.

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Performance comparison and analysis of silicon-based and carbon-based integrated circuits under VLSI

Jianhao Wu *^,1,

¹ Huaibei Institute of Technology

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/39/20230605

Abstract

Since 1960, the semiconductor industry has invented Metal Oxide Semiconductor Field Effect Transistor (MOSFET) and Complementary Metal Oxide Semiconductor (CMOS) technologies. Subsequently, the semiconductor-based integrated circuit industry has led a new generation of information revolution, driving the rapid development of various electronic circuit technologies worldwide. With the physical limitations of the silicon semiconductor process, Moore’s Law is also approaching its physical limit. In the search for new semiconductor materials, carbon nanotube semiconductors have become one of the candidate materials for new semiconductor materials due to their many advantages, and their many characteristic parameters are even better than those of silicon semiconductors of the same size. This article introduces the research status, performance characteristics, and comparison of silicon-based and carbon-based integrated circuits, as well as the current application scenarios of silicon-based and carbon-based integrated circuits in the industry, and the many problems encountered. Finally, this article analyses the future development direction of the integrated circuit industry and the possible challenges it may face.

Keywords

Semiconductor, Carbon Nanotube, Carbon-based Integrated Circuits, CMOS, Integrated Circuits

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Cite this article

Wu,J. (2024). Performance comparison and analysis of silicon-based and carbon-based integrated circuits under VLSI. Applied and Computational Engineering,39,244-250.

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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation

Conference website: https://2023.confmla.org/

ISBN：978-1-83558-303-6(Print) / 978-1-83558-304-3(Online)

Conference date: 18 October 2023

Editor：Mustafa İSTANBULLU

Series: Applied and Computational Engineering

Volume number: Vol.39

ISSN：2755-2721(Print) / 2755-273X(Online)

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