Emulation of Synaptic Plasticity on a Cobalt-Based Synaptic Transistor for Neuromorphic Computing

Area of Science:

• Materials Science
• Neuroscience
• Computer Engineering

Background:

• Neuromorphic computing (NC) aims to emulate the human brain for low-power artificial intelligence.
• Hardware elements like synaptic devices are crucial for realizing NC.
• Electrolyte gating effectively emulates biological synapses, but metallic channel-based synaptic transistors are underexplored.

Purpose of the Study:

• To demonstrate a synaptic transistor using a metallic cobalt thin film for neuromorphic computing.
• To investigate the device's ability to emulate biological synaptic functions and cognitive behaviors.

Main Methods:

• Fabrication of a three-terminal electrolyte gating-modulated synaptic transistor with a metallic cobalt channel.
• Characterization of gating-controlled, non-volatile, multilevel conductance states.
• Emulation of synaptic plasticity (short-term and long-term memory) and cognitive behaviors (learning, forgetting, re-learning).

Main Results:

• Successful demonstration of a metallic cobalt thin-film synaptic transistor.
• Achieved distinct multilevel conductance states controlled by electrolyte gating.
• Emulated essential synaptic functions, including transitions from short-term to long-term memory.
• Demonstrated cognitive behaviors like learning, forgetting, and re-learning, mimicking the human brain.
• Implemented dynamic filtering behavior.

Conclusions:

• Metallic channel-based synaptic transistors are viable for neuromorphic computing.
• The demonstrated device emulates key brain functions, offering a new pathway for AI hardware.
• Further research into metallic channel materials can advance neuromorphic engineering.