Optically modulated dual-mode memristor arrays based on core-shell CsPbBr_(3)@graphdiyne nanocrystals for fully memristive neuromorphic computing hardware

Artificial synapses and neurons are crucial milestones for neuromorphic computing hardware,and memristors with resistive and threshold switching characteristics are regarded as the most promising candidates for the construction of hardware neural networks.However,most of the memristors can only operate in one mode,that is,resistive switching or threshold switching,and distinct memristors are required to construct fully memristive neuromorphic computing hardware,making it more complex for the fabrication and integration of the hardware.Herein,we propose a flexible dual-mode memristor array based on core–shell CsPbBr3@graphdiyne nanocrystals,which features a 100%transition yield,small cycle-to-cycle and device-to-device variability,excellent flexibility,and environmental stability.Based on this dual-mode memristor,homo-material-based fully memristive neuromorphic computing hardware—a power-free artificial nociceptive signal processing system and a spiking neural network—are constructed for the first time.Our dual-mode memristors greatly simplify the fabrication and integration of fully memristive neuromorphic systems.

Synthesis of wafer-scale graphdiyne/graphene heterostructure for scalable neuromorphic computing and artificial visual systems

Graphdiyne(GDY)is emerging as a promising material for various applications owing to its unique structure and fascinating properties.However,the application of GDY in electronics and optoelectronics are still in its infancy,primarily owing to the huge challenge in the synthesis of large-area and uniform GDY film for scalable applications.Here a modified van der Waals epitaxy strategy is proposed to synthesize wafer-scale GDY film with high uniformity and controllable thickness directly on graphene(Gr)surface,providing an ideal platform to construct large-scale GDY/Gr-based optoelectronic synapse array.Essential synaptic behaviors have been realized,and the linear and symmetric conductance-update characteristics facilitate the implementation of neuromorphic computing for image recognition with high accuracy and strong fault tolerance.Logic functions including“NAND”and“NOR”are integrated into the synapse which can be executed in an optical pathway.Moreover,a visible information sensing-memory-processing system is constructed to execute real-time image acquisition,in situ image memorization and distinction tasks,avoiding the time latency and energy consumption caused by data conversion and transmission in conventional visual systems.These results highlight the potential of GDY in applications of neuromorphic computing and artificial visual systems.