Atomically thin optomemristive feedback neurons
Ghazi Sarwat Syed1,2, Yingqiu Zhou3,4, Jamie Warner5,6
1IBM Research - Europe, Rüschlikon, Switzerland. ghs@zurich.ibm.com.
Nature Nanotechnology
|May 4, 2023
Summary
Researchers developed a novel optomemristive neuron using layered 2D materials. This device mimics brain functions by integrating and broadcasting excitatory and inhibitory signals, advancing neuromorphic computing and machine learning applications.
Area of Science:
- Neuromorphic Engineering
- Materials Science
- Computational Neuroscience
Background:
- Mammalian brain learning relies on complex neuronal circuits with feed-forward and feedback connections.
- Existing neuromorphic computing struggles to create nanoscale devices that simultaneously handle excitatory and inhibitory signals.
Purpose of the Study:
- To introduce a novel nanoscale device capable of combining and broadcasting both excitatory and inhibitory signals.
- To demonstrate the device's utility in machine learning, specifically in unsupervised and cooperative learning paradigms.
Main Methods:
- Fabrication of a type-II, two-dimensional heterojunction optomemristive neuron using MoS2, WS2, and graphene.
- Utilizing optoelectronic charge-trapping mechanisms to achieve dual signal modulation.
- Simulating winner-take-all networks for data partitioning and combinatorial optimization.
Main Results:
- The developed optomemristive neuron successfully integrates and broadcasts both excitatory and inhibitory signals.
- The device exhibits nonlinear and rectified information integration.
- Simulations demonstrated effective unsupervised competitive learning and cooperative learning.
Conclusions:
- The new optomemristive neuron represents a significant advancement for neuromorphic computing.
- This technology enables efficient information processing and has broad applications in machine learning and artificial intelligence.
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