Multimodal optoelectronic neuromorphic electronics based on lead-free perovskite-mixed carbon nanotubes

Abstract

It is of great significance to develop multifunction-integrated photoelectric synaptic devices with the simple structure to imitate the functions of eyes. In this work, we reported the multimodal photoelectric neuromorphic thin film transistors (TFTs) with single gate and two input terminals using sorted semiconducting single-walled carbon nanotubes (sc-SWCNTs) mixed with lead-free perovskite (CsBi3I10) and lightly n-doped silicon as active layers and gate electrodes. The results showed that optical and electrical responses of SWCNT TFTs could increase 26 and 23 times after addition of CsBi3I10 under the same pulse sequence stimulation, respectively. Apart from emulating a series of typical synaptic functionalities, an artificial neural network based on SWCNT phototransistors was simulated to be trained for the recognition of handwritten digits in the Modified National Institute of Standards and Technology with the maximum accuracy of about 85.46%. Moreover, our synaptic devices can imitate traditional Pavlovian conditioning, and show NOR logic, reproducible flash memory functions under the optical and electrical programming stimulations. It is noted that the erasing voltage (3 V, 0.2 s) is one of the best value among the reported phototransistor memory. Furthermore, our synaptic devices can work well after more than 150 programming/erasing operation cycles and over 40 days testing.