Modulation of Binary Neuroplasticity in a Heterojunction-Based Ambipolar Transistor

Area of Science:

• Materials Science and Engineering
• Neuroscience and Neuromorphic Computing
• Organic Electronics

Background:

• The big-data era necessitates advanced computing paradigms, driving interest in device-level neuromorphic systems.
• Synaptic transistors, particularly those using all-solution processing, are key components for spike-based neuromorphic computing.
• Existing neuromorphic devices face challenges in efficiency and mimicking biological synaptic plasticity.

Purpose of the Study:

• To propose and demonstrate a novel dual-operation mode synaptic transistor.
• To utilize an ambipolar charge-trapping mechanism for analog emulation of synaptic plasticity.
• To explore the potential of this device for pattern recognition in neuromorphic systems.

Main Methods:

• Fabrication of a heterojunction-based synaptic transistor using poly(PDPPBTT)/ZnO layers via all-solution processing.
• Investigation of the ambipolar charge-trapping mechanism to achieve dual operation modes (hole-enhancement and electron-enhancement).
• Configuration of synaptic responses, including paired-pulse facilitation (PPF) and paired-pulse depression (PPD), for functional testing.

Main Results:

• Successful demonstration of a dual-operation mode synaptic transistor based on the PDPPBTT/ZnO heterojunction.
• Emulation of synaptic plasticity through an ambipolar charge-trapping mechanism, enabling analog synaptic behavior.
• Achieved training and recognition of digit image patterns at the device-to-system level, showcasing functional applicability.

Conclusions:

• The developed PDPPBTT/ZnO synaptic transistor exhibits promising dual-mode operation for neuromorphic applications.
• The ambipolar transistor design effectively mimics synaptic plasticity, crucial for intelligent computing systems.
• This research highlights the potential of solution-processed organic/inorganic heterojunctions in advancing future neuromorphic intelligent systems.