Abstract
The development of a reliable optoelectronic memristor is crucial for the success of neuromorphic vision systems, but current devices are limited by stochastic resistance switching and uncontrollable ion dynamics. To address these challenges, a core–shell nanosphere composite was synthesized using CsPbBr3 quantum dots and block copolymer polystyrene-poly2-vinyl pyridine. This memristor exhibits both negative differential resistance and resistive switching memory behavior and has demonstrated exceptional stability, withstanding over 5000 cycles and remaining stable for over 5 million seconds. It is also tunable by light irradiation, making it ideal for optoelectronic logic operations and multi-derivative state applications. The memory behavior is attributed to an electrochemical metalization mechanism involving the formation and annihilation of pyridine groups, conductive metal filaments, and bromide ion vacancies in S2VP filaments. This work presents an effective method for fabricating robust multi-derivative perovskite optoelectronic devices for neuromorphic computing systems. Additionally, machine learning algorithms have demonstrated accurate digital image classification and recognition using photoelectric pulse-driven neuromorphic computation with an accuracy of over 97%.
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