Solution-Processed Self-Assembling Charge-Transfer Cocrystal/TIPS-Pentacene Heterojunctions for Artificial Synapses

Abstract

Artificial synapses have gained considerable attention in modeling artificial visual systems. Facile and efficient p-n heterojunction, acting as the essential component, plays a critical role in configuration optimization and processing capabilities. Herein, we introduced a novel charge-transfer cocrystal that consisted of 5,8-dihydroindolo[2,3-c]carbazole (DDCB) and 7,7,8,8-tetracyanoquinodimethane (TCNQ) via solution-process, which demonstrated good crystallinity and typical n-type charge transport characteristics. To realize good charge storage ability, crystalline p-n heterojunctions with a phase-separated heterostructure were one-step prepared by drop-casting TIPS-pentacene and DDCB/TCNQ solutions onto the substrate. The as-prepared artificial synaptic devices exhibited remarkable paired-pulse facilitation (PPF), spike-duration dependent plasticity, spike-intensity dependent plasticity, and learning-experience behaviors similar to those of biological synapses in response to light pulses. Furthermore, based on the light potentiation and electrical depression modulation properties of these synaptic devices, we constructed artificial neural networks for image recognition, achieving a validation accuracy of over 97% on the modified national institute of standards and technology (MNIST) dataset. This work provides a new simple approach in establishing p-n heterojunction based artificial synapses for applications in light information processing, artificial vision, and memory simulation.