Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Optimizing the Development Process in Direct Photolithography for Efficient PeLEDs.

Small methods·2026
Same author

Morphology-controlled copper nanostructures: synthesis, anti-oxidation strategy, and applications.

Nanoscale·2026
Same author

Quantifying the Electrical Excitation Level of Quantum Dots for Mitigating Electroluminescent Efficiency Roll-Off.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

Memristive Physical Reservoir Computing.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Healing Intercrystalline Defects of ZIF-8 Membrane by Hydrophobic and Sterically Hindered Ionic Liquid for Humid Propylene/Propane Separation.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Lattice-constant engineering of RuO<sub>2</sub><i>via</i> Gd incorporation for active and stable water splitting.

Chemical communications (Cambridge, England)·2026

Related Experiment Video

Updated: Aug 26, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

7.9K

Optoelectronic Artificial Synaptic Device Based on Amorphous InAlZnO Films for Learning Simulations.

Ruqi Yang1, Lei Yin1, Jianguo Lu1,2

  • 1State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China.

ACS Applied Materials & Interfaces
|October 4, 2022
PubMed
Summary

Neuromorphic computing utilizes light-stimulated artificial synapses for efficient brain-like processing. These InAlZnO devices show promising synaptic plasticity and low energy consumption for next-generation computing.

Keywords:
amorphous oxide semiconductorindium aluminum zinc oxide (InAlZnO)learning simulationoptoelectronic artificial synaptic devicesynaptic plasticity

More Related Videos

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

10.0K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K

Related Experiment Videos

Last Updated: Aug 26, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

7.9K
A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

10.0K
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K

Area of Science:

  • Neuromorphic computing
  • Optoelectronics
  • Materials Science

Background:

  • Traditional von Neumann computing faces limitations.
  • Neuromorphic computing offers a brain-inspired alternative.
  • Optically controlled artificial synapses promise low power and high stability.

Purpose of the Study:

  • To demonstrate amorphous InAlZnO-based light-stimulated artificial synaptic devices.
  • To investigate their synaptic properties and energy efficiency.
  • To explore their potential for neuromorphic computing applications.

Main Methods:

  • Fabrication of InAlZnO-based thin-film transistor synaptic devices.
  • Characterization of synaptic properties like excitatory postsynaptic current and paired-pulse facilitation (PPF) under light stimulation.
  • Simulation of learning-forgetting behavior by modulating gate voltage.

Main Results:

  • Devices exhibited essential synaptic functions including PPF (155.9% at 0.1s interval with 375 nm light).
  • Achieved ultra-low energy consumption of 2.3 pJ per synaptic event.
  • Demonstrated significant synaptic plasticity with a relaxation time constant of 277 s after 10 light spikes.
  • Simulated human-like learning-forgetting behavior modulated by gate voltage.

Conclusions:

  • Amorphous InAlZnO devices show excellent optoelectronic synaptic properties.
  • These devices offer a promising platform for low-power, high-performance neuromorphic computing.
  • The demonstrated synaptic plasticity and behavior simulation pave the way for advanced artificial intelligence hardware.