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Amorphous metal-oxide semiconductor thin-film neuron, synapse, and neuromorphic system
Mutsumi Kimura1,2, Yuji Miyato3, Michihiro Shintani4
1Ryukoku University, Otsu, Japan. mutsu@rins.ryukoku.ac.jp.
Scientific Reports
|June 4, 2026
Summary
Researchers developed amorphous metal-oxide semiconductor (AOS) thin-film neurons and synapses for compact, energy-efficient neuromorphic systems. These components enable feasible neuromorphic systems with 94.1% recognition accuracy on MNIST data.
Area of Science:
- Materials Science
- Computer Engineering
- Artificial Intelligence
Background:
- Artificial intelligence (AI) demands compact and energy-efficient solutions, with neuromorphic systems offering a promising approach.
- Thin-film semiconductor technologies, particularly amorphous metal-oxide semiconductors (AOS), are crucial for developing advanced microelectronics.
Purpose of the Study:
- To research and develop amorphous metal-oxide semiconductor (AOS) thin-film neurons, synapses, and integrated neuromorphic systems.
- To evaluate the feasibility and performance of these thin-film components for AI applications.
Main Methods:
- Fabrication and experimental evaluation of AOS thin-film transistors (TFTs), memristors, and Schottky diodes.
- Design and simulation of thin-film neurons and synapses using fabricated AOS components.
- Integration of thin-film neurons and synapses into a neuromorphic system for logic simulation and training.
Main Results:
- AOS thin-film transistors (TFTs) were fabricated, evaluated, and simulated successfully.
- Thin-film neurons and synapses, utilizing AOS TFTs, memristors, and Schottky diodes, demonstrated desired circuit behaviors.
- The developed neuromorphic system achieved 94.1% recognition accuracy on the MNIST dataset through circuit-aware training.
Conclusions:
- Amorphous metal-oxide semiconductor (AOS) thin-film technology is a viable solution for creating compact and energy-efficient neuromorphic systems.
- The fabricated thin-film neurons, synapses, and integrated neuromorphic system are feasible for practical AI applications.
- This research paves the way for advanced, large-scale neuromorphic computing using thin-film electronics.
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