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Environmentally Stable and Reconfigurable Ultralow-Power Two-Dimensional Tellurene Synaptic Transistor for Neuromorphic Edge Computing.
Yoon, Jeechan; You, Bolim; Kim, Yuna; Bak, Jina; Yang, Mino; Park, Jihyang; Hahm, Myung Gwan; Lee, Moonsang.
Afiliação
  • Yoon J; Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea.
  • You B; Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea.
  • Kim Y; Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea.
  • Bak J; Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea.
  • Yang M; Korea Basic Science Institute Seoul, 145 anam-ro Seongbuk-gu, Seoul 02841, Republic of Korea.
  • Park J; Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea.
  • Hahm MG; Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea.
  • Lee M; Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea.
ACS Appl Mater Interfaces ; 15(14): 18463-18472, 2023 Apr 12.
Article em En | MEDLINE | ID: mdl-36881815
ABSTRACT
While neuromorphic computing can define a new era for next-generation computing architecture, the introduction of an efficient synaptic transistor for neuromorphic edge computing still remains a challenge. Here, we envision an atomically thin 2D Te synaptic device capable of achieving a desirable neuromorphic edge computing design. The hydrothermally grown 2D Te nanosheet synaptic transistor apparently mimicked the biological synaptic nature, exhibiting 100 effective multilevel states, a low power consumption of ∼110 fJ, excellent linearity, and short-/long-term plasticity. Furthermore, the 2D Te synaptic device achieved reconfigurable MNIST recognition accuracy characteristics of 88.2%, even after harmful detergent environment infection. We believe that this work serves as a guide for developing futuristic neuromorphic edge computing.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ACS Appl Mater Interfaces Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ACS Appl Mater Interfaces Ano de publicação: 2023 Tipo de documento: Article