Nanoscale channel organic ferroelectric synaptic transistor array for high recognition accuracy neuromorphic computing

Benefiting from solution processability, material diversity and biocompatibility properties of organic semiconductors, organic synaptic transistor is a promising alternative to execute neuromorphic computing. Unfortunately, conventional planner organic synaptic transistors suffer from poor analog weight update and fault tolerance, which limits the pattern recognition accuracy of organic neuromorphic system. Herein, a scalable and reconfigurable nanoscale channel organic ferroelectric synaptic transistor array (NOFST) is firstly demonstrated. Different from planner synaptic devices whose synaptic properties mostly rely on manipulating carrier densities, the operation mechanism of NOFST is associated with the virtual contact formation of pseudo-conductive channel and polarization tuned distribution of carriers, which manipulates the injection of carries into semiconductor. Hence, benefiting from the nanoscale channel length and the above unique operation mechanism, NOFST exhibits excellent gate control ability contributing to the improvement of fault tolerance and weight update properties. Finally, the neuromorphic system built from NOFST achieves 91.38% recognition accuracy of handwriting digit, which is record high for organic field-effect synaptic transistors. The special device structure is wildly applicable for other organic semiconductor materials, providing a new pathway for developing organic neuromorphic hardware systems with high recognition accuracy.