Two-dimensional materials for next-generation computing technologies
Rapid digital technology advancement has resulted in a tremendous increase in computing tasks imposing stringent energy efficiency and area efficiency requirements on next-generation computing. To meet the growing data-driven demand, in-memory computing and transistor-based computing have emerged as...
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| Published in | Nature nanotechnology Vol. 15; no. 7; pp. 545 - 557 |
|---|---|
| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
01.07.2020
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Rapid digital technology advancement has resulted in a tremendous increase in computing tasks imposing stringent energy efficiency and area efficiency requirements on next-generation computing. To meet the growing data-driven demand, in-memory computing and transistor-based computing have emerged as potent technologies for the implementation of matrix and logic computing. However, to fulfil the future computing requirements new materials are urgently needed to complement the existing Si complementary metal–oxide–semiconductor technology and new technologies must be developed to enable further diversification of electronics and their applications. The abundance and rich variety of electronic properties of two-dimensional materials have endowed them with the potential to enhance computing energy efficiency while enabling continued device downscaling to a feature size below 5 nm. In this Review, from the perspective of matrix and logic computing, we discuss the opportunities, progress and challenges of integrating two-dimensional materials with in-memory computing and transistor-based computing technologies.
This Review discusses the recent progress and future prospects of two-dimensional materials for next-generation nanoelectronics. |
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| AbstractList | Rapid digital technology advancement has resulted in a tremendous increase in computing tasks imposing stringent energy efficiency and area efficiency requirements on next-generation computing. To meet the growing data-driven demand, in-memory computing and transistor-based computing have emerged as potent technologies for the implementation of matrix and logic computing. However, to fulfil the future computing requirements new materials are urgently needed to complement the existing Si complementary metal-oxide-semiconductor technology and new technologies must be developed to enable further diversification of electronics and their applications. The abundance and rich variety of electronic properties of two-dimensional materials have endowed them with the potential to enhance computing energy efficiency while enabling continued device downscaling to a feature size below 5 nm. In this Review, from the perspective of matrix and logic computing, we discuss the opportunities, progress and challenges of integrating two-dimensional materials with in-memory computing and transistor-based computing technologies.Rapid digital technology advancement has resulted in a tremendous increase in computing tasks imposing stringent energy efficiency and area efficiency requirements on next-generation computing. To meet the growing data-driven demand, in-memory computing and transistor-based computing have emerged as potent technologies for the implementation of matrix and logic computing. However, to fulfil the future computing requirements new materials are urgently needed to complement the existing Si complementary metal-oxide-semiconductor technology and new technologies must be developed to enable further diversification of electronics and their applications. The abundance and rich variety of electronic properties of two-dimensional materials have endowed them with the potential to enhance computing energy efficiency while enabling continued device downscaling to a feature size below 5 nm. In this Review, from the perspective of matrix and logic computing, we discuss the opportunities, progress and challenges of integrating two-dimensional materials with in-memory computing and transistor-based computing technologies. Rapid digital technology advancement has resulted in a tremendous increase in computing tasks imposing stringent energy efficiency and area efficiency requirements on next-generation computing. To meet the growing data-driven demand, in-memory computing and transistor-based computing have emerged as potent technologies for the implementation of matrix and logic computing. However, to fulfil the future computing requirements new materials are urgently needed to complement the existing Si complementary metal–oxide–semiconductor technology and new technologies must be developed to enable further diversification of electronics and their applications. The abundance and rich variety of electronic properties of two-dimensional materials have endowed them with the potential to enhance computing energy efficiency while enabling continued device downscaling to a feature size below 5 nm. In this Review, from the perspective of matrix and logic computing, we discuss the opportunities, progress and challenges of integrating two-dimensional materials with in-memory computing and transistor-based computing technologies.This Review discusses the recent progress and future prospects of two-dimensional materials for next-generation nanoelectronics. Rapid digital technology advancement has resulted in a tremendous increase in computing tasks imposing stringent energy efficiency and area efficiency requirements on next-generation computing. To meet the growing data-driven demand, in-memory computing and transistor-based computing have emerged as potent technologies for the implementation of matrix and logic computing. However, to fulfil the future computing requirements new materials are urgently needed to complement the existing Si complementary metal-oxide-semiconductor technology and new technologies must be developed to enable further diversification of electronics and their applications. The abundance and rich variety of electronic properties of two-dimensional materials have endowed them with the potential to enhance computing energy efficiency while enabling continued device downscaling to a feature size below 5 nm. In this Review, from the perspective of matrix and logic computing, we discuss the opportunities, progress and challenges of integrating two-dimensional materials with in-memory computing and transistor-based computing technologies. Rapid digital technology advancement has resulted in a tremendous increase in computing tasks imposing stringent energy efficiency and area efficiency requirements on next-generation computing. To meet the growing data-driven demand, in-memory computing and transistor-based computing have emerged as potent technologies for the implementation of matrix and logic computing. However, to fulfil the future computing requirements new materials are urgently needed to complement the existing Si complementary metal–oxide–semiconductor technology and new technologies must be developed to enable further diversification of electronics and their applications. The abundance and rich variety of electronic properties of two-dimensional materials have endowed them with the potential to enhance computing energy efficiency while enabling continued device downscaling to a feature size below 5 nm. In this Review, from the perspective of matrix and logic computing, we discuss the opportunities, progress and challenges of integrating two-dimensional materials with in-memory computing and transistor-based computing technologies. This Review discusses the recent progress and future prospects of two-dimensional materials for next-generation nanoelectronics. |
| Author | Liu, Chunsen Liu, Ming Jiang, Yu-Gang Wang, Shuiyuan Chen, Huawei Zhang, David Wei Zhou, Peng Liu, Qi |
| Author_xml | – sequence: 1 givenname: Chunsen surname: Liu fullname: Liu, Chunsen organization: State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, School of Computer Science, Fudan University – sequence: 2 givenname: Huawei surname: Chen fullname: Chen, Huawei organization: State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University – sequence: 3 givenname: Shuiyuan surname: Wang fullname: Wang, Shuiyuan organization: State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University – sequence: 4 givenname: Qi orcidid: 0000-0001-7062-831X surname: Liu fullname: Liu, Qi organization: Frontier Institute of Chip and System, Fudan University, Key Laboratory of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences – sequence: 5 givenname: Yu-Gang surname: Jiang fullname: Jiang, Yu-Gang organization: School of Computer Science, Fudan University – sequence: 6 givenname: David Wei surname: Zhang fullname: Zhang, David Wei organization: State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University – sequence: 7 givenname: Ming surname: Liu fullname: Liu, Ming organization: Frontier Institute of Chip and System, Fudan University, Key Laboratory of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences – sequence: 8 givenname: Peng orcidid: 0000-0002-7301-1013 surname: Zhou fullname: Zhou, Peng email: pengzhou@fudan.edu.cn organization: State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32647168$$D View this record in MEDLINE/PubMed |
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