Field-driven hybrid filament formation governs switching in Ta–HfO2–Pt memristors

Abstract

Memristive devices have gained significant attention for their potential in next-generation non-volatile memory and neuromorphic computing architectures. Among emerging candidates, transition metal oxides have proven particularly promising. While the switching mechanism in Ta/HfO 2 /Pt devices was long attributed solely to oxygen vacancy based filaments, recent experimental evidence suggests a more complex dual-regime: the diffusion of metal cations also contributes to the formation of a conductive bridge. However, the precise atomistic mechanisms governing this metal cation migration remain poorly understood. Additionally, the role of defects such as oxygen vacancies present in the transition metal oxide in determining the final filament size and shape is also not well understood. Here, we employ molecular dynamics (MD) simulations with dynamic charge transfer to provide a detailed analysis of the atomistic mechanisms governing the co-formation of Ta-cation and oxygen-deficient filaments. We show how varying the initial oxygen vacancy concentrations and spatial configurations within the HfO 2 matrix influences the final morphology and dimensions of the conductive filament. The switching is governed by field-driven formation and rupture of a hybrid Ta-cation-rich, oxygen-deficient filament in HfO 2 . The state variable that links the simulated structures to the electrical response is measured directly from the filament geometry, namely the tunneling gap between the filament tip and the bottom electrode together with the narrowest constriction along the filament, and each device configuration is sampled over five independent trajectories. The simulated switching behavior reproduces the qualitative features reported experimentally for this stack, including the switching polarity, the hysteresis shape, the set/reset ordering, and the appearance of intermediate resistance states, and the framework provides a route to relate atomistic filament geometry to device-level electrical response and to the origins of device-to-device variability.