Improving multifunctional monolithic nano-device by single (Al,Ga)N nanowire/graphene van der Waals heterostructure for neuromorphic computing, photodetection and imaging

作者：Min Zhou, Min Jiang, Chaoyun Song, Kai Xu, Zexin Yu, Lifeng Bian, Liubin Yang, Jianya Zhang, Shulong Lu, Yukun Zhao · 发表于：Communications Materials · 年份：2025 · DOI：10.1038/s43246-025-00803-5 · 被引用次数：6 · 研究领域：Advanced Memory and Neural Computing、Graphene research and applications、2D Materials and Applications

Integrating neuromorphic computing, photodetection and imaging in single devices remains challenging due to the inherent trade-off between the transient photoresponse speeds of artificial synapses and photodetectors. This study develops a dual-mode monolithic device using a (Al,Ga)N nanowire/graphene heterojunction, operating as a photodetector under negative bias and a neuromorphic sensor under positive bias. Graphene strengthens the built-in electric field, enhancing carrier separation and photocurrent for both functions. The device consumes ultralow energy (3.19 × 10−11 J) with demonstrated synaptic plasticity features like spike-dependent learning and accelerated memory reinforcement. Leveraging this synaptic plasticity, the device achieves over 90% accuracy in image processing tasks. This work introduces a multifunctional integration strategy that advances neuromorphic computing efficiency and optoelectronic device design, demonstrating the feasibility of simultaneous imaging and brain-inspired computation in compact systems. The integration of multiple functionalities, such as neuromorphic computing, photodetection and imaging, within a single optoelectronic device is challenging due to the trade-off between the transient photoresponse speeds of artificial synapses and photodetectors. Here, a multifunctional monolithic nano-device based on the heterojunction between a single (Al,Ga)N nanowire and graphene is proposed, providing a dual-mode operation that integrates phot...