Flexible Electrolyte-Gated Transistor Based on Inznsno Nanowires for Self-Adaptive Applications

A pivotal characteristic of neuromorphic systems lies in their inherent capacity for self-adaptation, facilitating environmental adaptation through the attenuation of response to repetitive stimuli. Existing electrolyte-gated synaptic transistors face challenges in simulating these self-adaptive behaviors of the brain. In this work, we fabricated a flexible indium zinc tin oxide (IZTO) nanowires-based synaptic transistor by employing an ion migration mechanism to achieve these self-adaptive functions. The prepared transistors replicate typical synaptic functions by continuously modulating the conductance, including excitatory/inhibitory postsynaptic current and short/long term potentiation. These properties are well maintained under a bending radius of 12 mm. Additionally, the neuromorphic system built from IZTO nanowires-based transistors achieves a high recognition accuracy exceeding 90% for handwriting digit recognition. The synaptic transistor exhibits obvious self-adaptive behavior and a low energy consumption reduction of 8.2%. Self-adaptive neuromorphic flexible transistors can not only enhance their resemblance to biological systems, but also advance the development of wearable devices and neuromorphic calculation.