Emulation of synaptic functions with low voltage organic memtransistor for hardware oriented neuromorphic computing
Srikrishna Sagar, Kannan Udaya Mohanan, Seongjae Cho, Leszek A. Majewski, Bikas C. Das
Abstract
Abstract Here, various synaptic functions and neural network simulation based pattern-recognition using novel, solution-processed organic memtransistors ( mem Ts) with an unconventional redox-gating mechanism are demonstrated. Our synaptic mem T device using conjugated polymer thin-film and redox-active solid electrolyte as the gate dielectric can be routinely operated at gate voltages ( V GS ) below − 1.5 V, subthreshold-swings ( S ) smaller than 120 mV/dec, and ON/OFF current ratio larger than 10 8 . Large hysteresis in transfer curves depicts the signature of non-volatile resistive switching (RS) property with ON/OFF ratio as high as 10 5 . In addition, our memT device also shows many synaptic functions, including the availability of many conducting-states (> 500) that are used for efficient pattern recognition using the simplest neural network simulation model with training and test accuracy higher than 90%. Overall, the presented approach opens a new and promising way to fabricate high-performance artificial synapses and their arrays for the implementation of hardware-oriented neural network.