Self-Powered Optoelectronic Synaptic Devices Based on In₂Se₃/MoS₂ Ferroelectric Heterojunction with Boosted Performance

Neuromorphic computing systems are based on new architecture inspired by biological learning behavior and biological structure to overcome the shortcomings of the von Neumann system, such as high energy consumption and generation of excessive redundant data. However, common synaptic-device designs are still need to carry an external power source, which is detrimental to both the miniaturization of smart devices and the further reduction of energy consumption. Therefore, self-powered optoelectronic synapses hold great promise for achieving energy-efficient artificial intelligence applications. Given the advantages of heterogeneous integration and ferroelectric performance, the 2D ferroelectric In2Se3 has become a typical candidate material for biological synaptic devices and neuromorphic computing. Although, various structures of ferroelectric synaptic devices are developed, most of which are controlled by optical or electrical pulses, hardly any reports discuss the operation in self-powered mode. In this work, an In2Se3/MoS2 ferroelectric lateral heterojunction-type optoelectronic synaptic device is fabricated to mimic biological synaptic functions in voltage mode or self-driven mode. In addition, two simplified image pre-processing methods based on device arrays are shown to improve the recognition accuracy of a back-end neural network. The proposed approach suggests a new route for designing and applying high-performance synaptic devices.