神经形态工程学
记忆电阻器
材料科学
非易失性存储器
要素(刑法)
纳米技术
光电子学
电子工程
人工智能
人工神经网络
计算机科学
工程类
政治学
法学
作者
Ungbin Byun,Hyesung Na,Sungjun Kim
标识
DOI:10.1002/adfm.202519431
摘要
Abstract This study investigates the multifunctional resistive switching behaviors of W/NbO x /Pt devices, highlighting their potential for integrated neuromorphic computing. The device exhibits both volatile and non‐volatile resistive switching characteristics, enabling its dual use in reservoir computing and synaptic weight modulation. Gradual I–V responses in the volatile switching allow for temporal signal processing and short‐term memory functionalities, while abrupt switching in the non‐volatile switching supports long‐term potentiation and depression (PD). The application of the incremental step pulse with verify algorithm (ISPVA) enhances PD linearity and precision of synaptic weight modulation, enabling multi‐level conductance states with improved retention and endurance. Furthermore, by tuning the compliance current, the device exhibits threshold switching behavior, allowing the implementation of leaky integrate and fire (LIF) neuron circuits. These multiple characteristics allow the W/NbO x /Pt device to act as a reservoir layer, readout layer, and spiking neuron, thereby forming a compact and unified platform for on‐chip learning. This work demonstrates the feasibility of using a single resistive device architecture to implement both memory and computation, paving the way for highly integrated and energy‐efficient neuromorphic systems.
科研通智能强力驱动
Strongly Powered by AbleSci AI