4.7 Article

Fluoropolymer-based organic memristor with multifunctionality for flexible neural network system

Journal

NPJ FLEXIBLE ELECTRONICS
Volume 5, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41528-021-00132-w

Keywords

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Funding

  1. National Research Foundation of Korea (NRF) - Korea Government (MSIT) [2020R1F1A1075436]
  2. National R&D Program through the National Research Foundation of Korea (NRF) - Ministry of Science and ICT [2021M3F3A2A03017764]
  3. BK21 FOUR - Ministry of Education, Korea [4199990113966]
  4. National Research Foundation of Korea [2020R1F1A1075436, 2021M3F3A2A03017764] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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This study proposes an effective strategy for achieving the flexible 1T-1R synapse using a multifunctional organic memristor, and successfully develops an organic memristor based on hydrophobic fluoropolymer. The flexible synapse exhibits multilevel conductance with high reliability and stability, showing potential for high-density memory systems and practical neural networks. This concept could be a basic platform to realize smart wearable electronics.
In this study, we propose an effective strategy for achieving the flexible one organic transistor-one organic memristor (1T-1R) synapse using the multifunctional organic memristor. The dynamics of the conductive nanofilament (CF) in a hydrophobic fluoropolymer medium is explored and a hydrophobic fluoropolymer-based organic memristor is developed. The flexible 1T-1R synapse can be fabricated using the solution process because the hydrophobic fluorinated polymer layer is produced on the organic transistor without degradation of the underlying semiconductor. The developed flexible synapse exhibits multilevel conductance with high reliability and stability because of the fluoropolymer film, which acts as a medium for CF growth and an encapsulating layer for the organic transistor. Moreover, the synapse cell shows potential for high-density memory systems and practical neural networks. This effective concept for developing practical flexible neural networks would be a basic platform to realize the smart wearable electronics.

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