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Polymer Analog Memristive Synapse with Atomic-Scale Conductive Filament for Flexible Neuromorphic Computing System
Byung Chul Jang1, Sungkyu Kim2, Sang Yoon Yang1
1School of Electrical Engineering , Graphene/2D Materials Research Center, KAIST , Daejeon 34141 , Korea.
Nano Letters
|January 5, 2019
Summary
Researchers developed a flexible memristor using poly(1,3,5-trivinyl-1,3,5-trimethyl cyclotrisiloxane) (pV3D3) that mimics brain synapses. This artificial intelligence component shows promise for advanced neuromorphic computing systems.
Area of Science:
- Materials Science
- Neuroscience
- Computer Science
Background:
- Artificial intelligence (AI) drives demand for efficient neuromorphic systems.
- Memristors are key synaptic components for mimicking neural functions.
- Analog switching and multilevel conductance states are crucial for synaptic memristors.
Purpose of the Study:
- To demonstrate analog switching in poly(1,3,5-trivinyl-1,3,5-trimethyl cyclotrisiloxane) (pV3D3)-based flexible memristors.
- To achieve multilevel conductance states for synaptic applications.
- To evaluate the memristor's potential in artificial neural networks.
Main Methods:
- Fabrication of flexible memristors using pV3D3.
- Controlled reduction of filament size to transition from binary to analog switching.
- Utilizing atomic copper filament growth and dissolution for potentiation and depression.
- Simulating face classification using an artificial neural network with pV3D3 memristor synapses.
Main Results:
- Successfully demonstrated the transition from binary to analog switching in pV3D3 memristors by controlling filament size.
- Observed quantized conductance states enabling analog potentiation and depression.
- Achieved analog synaptic behavior through controlled filament growth and dissolution.
- Simulations showed effective face classification capabilities.
Conclusions:
- pV3D3-based flexible memristors can achieve analog synaptic functions.
- Filament size control is a viable method for tuning memristor operation.
- These findings support the development of soft neuromorphic intelligent systems.
Keywords:
Flexible memristorartificial neural network (ANN)electrochemical metallization (ECM)neuromorphic systemquantized conductanceMore Related Videos
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