An ion-gating synaptic memristor based on tri-layer HfOx composition regulation†

In this work, we developed tri-layer HfO_x/HfO₂/HfO_x memristors that exhibit high consistency and good linearity, making them suitable for high-efficiency neuromorphic computing. The HfO₂ intermediate layer serves as an ion-gating layer, enabling the precise localization and shaping of conductive pathways while regulating oxygen vacancy (V_O) migration. By optimizing the V_O difference Δ (Δ = 2 − x) and the ion-gating HfO₂ interlayer, we were able to precisely control the formation and rupture of conductive filaments (CFs) within the HfO₂ interlayer, leading to improved consistency, linearity and continuity of resistance variation. Notably, the HfO_1.7/HfO₂/HfO_1.7 (T-HfO_1.7) device demonstrated the highest low resistance consistency (1.7%) for memory function. Furthermore, this device exhibited essential synaptic functions, including long-term potentiation (LTP), paired-pulse facilitation (PPF), and spike-timing-dependent plasticity (STDP). The conductance modulation process of T-HfO_1.7 achieves high linearity (α_LTP = 1.55). Moreover, a Hopfield Neural Network (HNN) constructed using this device achieved a high image recognition accuracy of 95.6%. This work introduces a straightforward approach to improve the consistency and linearity of memristive behavior, paving the way for enhanced performance in neuromorphic applications.