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Photothermally Activated Artificial Neuromorphic Synapses.
Blankenship, Brian W; Li, Runxuan; Guo, Ruihan; Zhao, Naichen; Shin, Jaeho; Yang, Rundi; Ko, Seung Hwan; Wu, Junqiao; Rho, Yoonsoo; Grigoropoulos, Costas.
Afiliação
  • Blankenship BW; Laser Thermal Laboratory, Department of Mechanical Engineering, University of California, Berkeley, California 94720, United States.
  • Li R; Laser Thermal Laboratory, Department of Mechanical Engineering, University of California, Berkeley, California 94720, United States.
  • Guo R; Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States.
  • Zhao N; Laser Thermal Laboratory, Department of Mechanical Engineering, University of California, Berkeley, California 94720, United States.
  • Shin J; Applied Nano and Thermal Science Lab, Department of Mechanical Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea.
  • Yang R; Laser Thermal Laboratory, Department of Mechanical Engineering, University of California, Berkeley, California 94720, United States.
  • Ko SH; Applied Nano and Thermal Science Lab, Department of Mechanical Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea.
  • Wu J; Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States.
  • Rho Y; Laser Thermal Laboratory, Department of Mechanical Engineering, University of California, Berkeley, California 94720, United States.
  • Grigoropoulos C; Physical & Life Sciences and NIF & Photon Sciences, Lawrence Livermore National Laboratory, Livermore, California 94550, United States.
Nano Lett ; 23(19): 9020-9025, 2023 Oct 11.
Article em En | MEDLINE | ID: mdl-37724920
Biological nervous systems rely on the coordination of billions of neurons with complex, dynamic connectivity to enable the ability to process information and form memories. In turn, artificial intelligence and neuromorphic computing platforms have sought to mimic biological cognition through software-based neural networks and hardware demonstrations utilizing memristive circuitry with fixed dynamics. To incorporate the advantages of tunable dynamic software implementations of neural networks into hardware, we develop a proof-of-concept artificial synapse with adaptable resistivity. This synapse leverages the photothermally induced local phase transition of VO2 thin films by temporally modulated laser pulses. Such a process quickly modifies the conductivity of the film site-selectively by a factor of 500 to "activate" these neurons and store "memory" by applying varying bias voltages to induce self-sustained Joule heating between electrodes after activation with a laser. These synapses are demonstrated to undergo a complete heating and cooling cycle in less than 120 ns.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article