Threshold Dynamics of Silver Filament Formation and Rupture in Ag/SiO ₂ /Au Memristors

Memristive devices with tunable volatility represent a promising platform for neuromorphic computing and adaptive electronics, enabling temporal information processing and gradual memory consolidation. Understanding the threshold dynamics governing conductive filament formation and rupture is critical for precise control of resistive switching behavior. Here, we systematically investigate Ag/SiO2/Au memristor devices to elucidate the physics of silver filament evolution, revealing the asymmetric interplay between drift-dominated formation and diffusion-dominated rupture processes. Quantitative analysis of filament formation dynamics yields an activation energy of 0.77 ± 0.12 eV for ion migration with field enhancement factor β = 0.21, demonstrating field-assisted thermally activated silver filament formation. Our experiments confirm that formation and rupture share a similar intrinsic energy landscape but operate under different driving forces: field-accelerated drift versus thermally-driven diffusion. Interestingly, detailed filament dynamics analysis reveals the existence of a critical metastable regime during both formation and rupture processes, where drift and diffusion forces balance, and conduction occurs via trap-assisted tunneling through nanoscale silver clusters. This metastable state exists at specific voltages where drift and diffusion forces achieve dynamic equilibrium, leading to intermediate conductance states between the stable low and high resistance states. Beyond this regime, the system exhibits deterministic behavior: at higher voltages, filament growth proceeds through sequential conduction regimes where Joule heating drives morphological changes in silver nanoclusters that concentrate the electric field and accelerate complete filament formation. At lower voltages, diffusion dominates and drives complete rupture of filaments back to nanoclusters. This enables voltage-tunable operation from stochastic to deterministic modes. Combined with quantitative activation energies and the drift-diffusion framework, our work provides fundamental insight into threshold switching physics and establishes design principles for engineering devices with controlled probabilistic or deterministic behavior for neuromorphic and stochastic computing applications.