CsPbBr3 quantum dots/PDVT-10 conjugated polymer hybrid film-based photonic synaptic transistors toward high-efficiency neuromorphic computing

Abstract

Photonic synaptic transistors are promising neuromorphic computing systems that are expected to circumvent the intrinsic limitations of von Neumann-based computation. The design and construction of photonic synaptic transistors with a facile fabrication process and high-efficiency information processing ability are highly desired, while it remains a tremendous challenge. Herein, a new approach based on spin coating of a blend of CsPbBr3 perovskite quantum dot (QD) and PDVT-10 conjugated polymer is reported for the fabrication of photonic synaptic transistors. The combination of flat surface, outstanding optical absorption, and remarkable charge transporting performance contributes to high-efficiency photon-to-electron conversion for such perovskite-based synapses. High-performance photonic synaptic transistors are thus fabricated with essential synaptic functionalities, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and long-term memory. By utilizing the photonic potentiation and electrical depression features, perovskite-based photonic synaptic transistors are also explored for neuromorphic computing simulations, showing high pattern recognition accuracy of up to 89.98%, which is one of the best values reported so far for synaptic transistors used in pattern recognition. This work provides an effective and convenient pathway for fabricating perovskite-based neuromorphic systems with high pattern recognition accuracy.