Optoelectronic Synaptic Transistors via Adding Insulator Into Semiconductor for Brain-Inspired Computing

Recent developments in artificial intelligence (AI) have triggered growing studies in artificial synaptic transistors. However, achieving tunable synaptic behaviors and improving synaptic performance by simple processes is still challenging. Herein, a facile regulation strategy by introducing a polymer insulator to a semiconductor was proposed, for the first time, to implement an optoelectronic synaptic transistor (OST) using a solution-based method. The organic OST comprises a biodegradable polyvinyl alcohol (PVA) electret with hydroxyl group dipoles, enabling the effectively coordinated regulation of synaptic weight and the enhancement of synaptic properties. Essential synaptic characteristics were realized, such as paired-pulse facilitation (PPF), excitatory postsynaptic currents (EPSCs), long-term potentiation, and depression (LTP/D). The results indicate that enhanced synaptic performance should be associated with the improvement of thin film quality and surface morphologies due to blending insulators, as well as the carrier migration between semiconductors and PVA. More importantly, the controllable light logical operation was perfectly simulated. Pattern recognition test of MNIST handwritten digits was also researched based on artificial neural networks (ANNs), a high recognition accuracy of 91.38% was achieved using appropriate insulator blending ratios. Therefore, our work should open a new pathway for designing optoelectronic synapse devices and expand their further application in brain-inspired computing.