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Electrical synapses found in all nervous systems play important and unique roles. In these synapses, the presynaptic and postsynaptic membranes are very close together (3.5 nm) and are actually physically connected by channel proteins forming gap junctions.
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A synapse is a specialized structure where two neurons connect, allowing them to pass an electrical or chemical signal to another neuron. It is the point of communication between neurons. The term "synapse" is derived from the Greek word "synapsis," which means "conjunction." The entire process of neural communication revolves around the synapse. When activated, a neuron releases chemicals known as neurotransmitters into the synapse. These neurotransmitters cross the synapse and bind to...
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Chemical synapses are specialized sites between two neurons or between a neuron and a non-neuronal cell like a muscle, glandular or sensory cell.
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Dynamic and Static Switching in ITO/SnOx/ITO and Its Synaptic Application.

Jongmin Park1, Hyunwoong Park1, Daewon Chung1

  • 1Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Korea.

International Journal of Molecular Sciences
|September 9, 2022
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Researchers developed a novel RRAM device mimicking synaptic plasticity. This memristive device exhibits dynamic and static current-voltage characteristics, paving the way for advanced artificial neural networks.

Keywords:
RRAMconduction mechanismdynamicstaticsynaptic application

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Area of Science:

  • Materials Science
  • Neuroscience
  • Computer Science

Background:

  • Artificial neural networks (ANNs) increasingly utilize diverse neural network (NN) architectures like CNNs and RNNs.
  • Resistive random-access memory (RRAM) is a promising candidate for memory devices in these networks.
  • Developing efficient memory devices is crucial for advancing brain-inspired computing.

Purpose of the Study:

  • To investigate the potential of a fabricated ITO/SnOX/TaN device as a synaptic element.
  • To analyze the current-voltage (I-V) characteristics and data retention properties of the RRAM device.
  • To confirm the device's ability to emulate synaptic plasticity, including paired-pulse facilitation (PPF).

Main Methods:

  • Fabrication of an ITO/SnOX/TaN RRAM device.
  • Measurement of current-voltage (I-V) characteristics, distinguishing between dynamic and static behaviors.
  • Data retention tests at room temperature for 10^3 seconds.
  • X-ray photoelectron spectroscopy (XPS) analysis to understand conduction mechanisms.
  • Application of rectangular voltage pulses to assess synaptic plasticity (PPF, STP to LTP transition).

Main Results:

  • The device exhibited two distinct I-V curve types: dynamic and static, post-forming process.
  • Demonstrated data retention capabilities at room temperature.
  • XPS analysis and linear fitting provided insights into the conduction mechanisms responsible for data preservation.
  • The device successfully emulated synaptic plasticity, transitioning from short-term potentiation (STP) to long-term potentiation (LTP) via PPF.

Conclusions:

  • The ITO/SnOX/TaN RRAM device shows potential for implementing synaptic functions in artificial neural networks.
  • The observed dynamic and static I-V characteristics, along with plasticity, are key features for neuromorphic computing.
  • This research contributes to the development of advanced memory devices for next-generation AI.