Stability Improvement of an Efficient Graphene Nanoribbon Field-Effect Transistor-Based SRAM Design
The development of the nanoelectronics semiconductor devices leads to the shrinking of transistors channel into nanometer dimension. However, there are obstacles that appear with downscaling of the transistors primarily various short-channel effects. Graphene nanoribbon field-effect transistor (GNRF...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Nanotechnology |
| Online Access: | http://dx.doi.org/10.1155/2020/7608279 |
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| author | Mathan Natarajamoorthy Jayashri Subbiah Nurul Ezaila Alias Michael Loong Peng Tan |
| author_facet | Mathan Natarajamoorthy Jayashri Subbiah Nurul Ezaila Alias Michael Loong Peng Tan |
| author_sort | Mathan Natarajamoorthy |
| collection | DOAJ |
| description | The development of the nanoelectronics semiconductor devices leads to the shrinking of transistors channel into nanometer dimension. However, there are obstacles that appear with downscaling of the transistors primarily various short-channel effects. Graphene nanoribbon field-effect transistor (GNRFET) is an emerging technology that can potentially solve the issues of the conventional planar MOSFET imposed by quantum mechanical (QM) effects. GNRFET can also be used as static random-access memory (SRAM) circuit design due to its remarkable electronic properties. For high-speed operation, SRAM cells are more reliable and faster to be effectively utilized as memory cache. The transistor sizing constraint affects conventional 6T SRAM in a trade-off in access and write stability. This paper investigates on the stability performance in retention, access, and write mode of 15 nm GNRFET-based 6T and 8T SRAM cells with that of 16 nm FinFET and 16 nm MOSFET. The design and simulation of the SRAM model are simulated in synopsys HSPICE. GNRFET, FinFET, and MOSFET 8T SRAM cells give better performance in static noise margin (SNM) and power consumption than 6T SRAM cells. The simulation results reveal that the GNRFET, FinFET, and MOSFET-based 8T SRAM cells improved access static noise margin considerably by 58.1%, 28%, and 20.5%, respectively, as well as average power consumption significantly by 97.27%, 99.05%, and 83.3%, respectively, to the GNRFET, FinFET, and MOSFET-based 6T SRAM design. |
| format | Article |
| id | doaj-art-a94251ecf7734abf9acc3b1e8bcb1158 |
| institution | Kabale University |
| issn | 1687-9503 1687-9511 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Nanotechnology |
| spelling | doaj-art-a94251ecf7734abf9acc3b1e8bcb11582025-02-03T06:05:15ZengWileyJournal of Nanotechnology1687-95031687-95112020-01-01202010.1155/2020/76082797608279Stability Improvement of an Efficient Graphene Nanoribbon Field-Effect Transistor-Based SRAM DesignMathan Natarajamoorthy0Jayashri Subbiah1Nurul Ezaila Alias2Michael Loong Peng Tan3Faculty of Electronics Engineering, Sathyabama Institute of Science and Technology, Chennai, IndiaDepartment of ECE, Adhiparasakthi Engineering College, Melmaruvathur, IndiaSchool of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, MalaysiaSchool of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, MalaysiaThe development of the nanoelectronics semiconductor devices leads to the shrinking of transistors channel into nanometer dimension. However, there are obstacles that appear with downscaling of the transistors primarily various short-channel effects. Graphene nanoribbon field-effect transistor (GNRFET) is an emerging technology that can potentially solve the issues of the conventional planar MOSFET imposed by quantum mechanical (QM) effects. GNRFET can also be used as static random-access memory (SRAM) circuit design due to its remarkable electronic properties. For high-speed operation, SRAM cells are more reliable and faster to be effectively utilized as memory cache. The transistor sizing constraint affects conventional 6T SRAM in a trade-off in access and write stability. This paper investigates on the stability performance in retention, access, and write mode of 15 nm GNRFET-based 6T and 8T SRAM cells with that of 16 nm FinFET and 16 nm MOSFET. The design and simulation of the SRAM model are simulated in synopsys HSPICE. GNRFET, FinFET, and MOSFET 8T SRAM cells give better performance in static noise margin (SNM) and power consumption than 6T SRAM cells. The simulation results reveal that the GNRFET, FinFET, and MOSFET-based 8T SRAM cells improved access static noise margin considerably by 58.1%, 28%, and 20.5%, respectively, as well as average power consumption significantly by 97.27%, 99.05%, and 83.3%, respectively, to the GNRFET, FinFET, and MOSFET-based 6T SRAM design.http://dx.doi.org/10.1155/2020/7608279 |
| spellingShingle | Mathan Natarajamoorthy Jayashri Subbiah Nurul Ezaila Alias Michael Loong Peng Tan Stability Improvement of an Efficient Graphene Nanoribbon Field-Effect Transistor-Based SRAM Design Journal of Nanotechnology |
| title | Stability Improvement of an Efficient Graphene Nanoribbon Field-Effect Transistor-Based SRAM Design |
| title_full | Stability Improvement of an Efficient Graphene Nanoribbon Field-Effect Transistor-Based SRAM Design |
| title_fullStr | Stability Improvement of an Efficient Graphene Nanoribbon Field-Effect Transistor-Based SRAM Design |
| title_full_unstemmed | Stability Improvement of an Efficient Graphene Nanoribbon Field-Effect Transistor-Based SRAM Design |
| title_short | Stability Improvement of an Efficient Graphene Nanoribbon Field-Effect Transistor-Based SRAM Design |
| title_sort | stability improvement of an efficient graphene nanoribbon field effect transistor based sram design |
| url | http://dx.doi.org/10.1155/2020/7608279 |
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