Mimic Drug Dosage Modulation for Neuroplasticity Based on Charge-Trap Layered Electronics

  • Caifang Gao
  • , Mu Pai Lee
  • , Mengjiao Li
  • , Ko Chun Lee
  • , Feng Shou Yang
  • , Che Yi Lin
  • , Kenji Watanabe
  • , Takashi Taniguchi
  • , Po Wen Chiu
  • , Chen Hsin Lien
  • , Wen Wei Wu
  • , Shu Ping Lin*
  • , Wenwu Li*
  • , Yen Fu Lin*
  • , Junhao Chu
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

The human brain is often likened to an incredibly complex and intricate computer, rather than electrical devices, consisting of billions of neuronal cells connected by synapses. Different brain circuits are responsible for coordinating and performing specific functions. The reward pathway of the synaptic plasticity in the brain is strongly related to the features of both drug addiction and relief. In the current study, a synaptic device based on layered hafnium disulfide (HfS2) is developed for the first time, to emulate the behavioral mechanisms of drug dosage modulation for neuroplasticity. A strong gate-dependent persistent photocurrent is observed, arising from the modulation of substrate-trapping events. By controlling the polarity of gate voltage, the basic functions of biological synapses are realized under a range of light spiking conditions. Furthermore, under the control of detrapping/trapping events at the HfS2/SiO2 interface, positive/negative correlations of the An/A1 index, which significantly reflected the weight change of synaptic plasticity, are realized under the same stimulation conditions for the emulation of the drug-related addition/relief behaviors in the brain. The findings provide a new advance for mimicking human brain plasticity.

Original languageEnglish
Article number2005182
JournalAdvanced Functional Materials
Volume31
Issue number5
DOIs
StatePublished - 27 Jan 2021
Externally publishedYes

Keywords

  • charge trapping
  • drug addiction
  • gate-dependent modulations
  • layered HfS synaptic device
  • neuroplasticity

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