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A Scalable Artificial Neuron Based on Ultrathin Two-Dimensional Titanium Oxide.
Wang, Jingyun; Teng, Changjiu; Zhang, Zhiyuan; Chen, Wenjun; Tan, Junyang; Pan, Yikun; Zhang, Rongjie; Zhou, Heyuan; Ding, Baofu; Cheng, Hui-Ming; Liu, Bilu.
Afiliação
  • Wang J; Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, People's Republic of China.
  • Teng C; Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, People's Republic of China.
  • Zhang Z; Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, People's Republic of China.
  • Chen W; Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, People's Republic of China.
  • Tan J; Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, People's Republic of China.
  • Pan Y; Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, People's Republic of China.
  • Zhang R; Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, People's Republic of China.
  • Zhou H; Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, People's Republic of China.
  • Ding B; Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, People's Republic of China.
  • Cheng HM; Shenzhen Geim Graphene Center, Tsinghua-Berkeley Shenzhen Institute and Institute of Materials Research, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, People's Republic of China.
  • Liu B; Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, Shenyang 110016, People's Republic of China.
ACS Nano ; 15(9): 15123-15131, 2021 09 28.
Article em En | MEDLINE | ID: mdl-34534433
ABSTRACT
A spiking neural network consists of artificial synapses and neurons and may realize human-level intelligence. Unlike the widely reported artificial synapses, the fabrication of large-scale artificial neurons with good performance is still challenging due to the lack of a suitable material system and integration method. Here, we report an ultrathin (less than10 nm) and inch-size two-dimensional (2D) oxide-based artificial neuron system produced by a controllable assembly of solution-processed 2D monolayer TiOx nanosheets. Artificial neuron devices based on such 2D TiOx films show a high on/off ratio of 109 and a volatile resistance switching phenomenon. The devices can not only emulate the leaky integrate-and-fire activity but also self-recover without additional circuits for sensing and reset. Moreover, the artificial neuron arrays are fabricated and exhibited good uniformity, indicating their large-area integration potential. Our results offer a strategy for fabricating large-scale and ultrathin 2D material-based artificial neurons and 2D spiking neural networks.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Modelos Neurológicos Limite: Humans Idioma: En Revista: ACS Nano Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Modelos Neurológicos Limite: Humans Idioma: En Revista: ACS Nano Ano de publicação: 2021 Tipo de documento: Article