Abstract
Transition-metal oxide memristors are promising for neuromorphic computing, yet most SPICE models overlook material-specific effects such as oxygen stoichiometry and non-pinched hysteresis. Here, we systematically study CrOx/TiOy memristors fabricated under controlled oxygen concentrations (10%–50%) and propose an improved SPICE-compatible model. The devices exhibit oxygen-dependent resistive switching, retention, and pulse-driven plasticity, with optimal performance at 40% oxygen. Our model explicitly reproduces the non-pinched hysteresis observed in I–V curves, consistent with behaviors such as ion immigration, charge trapping, and remnant polarization, and achieves close agreement with experiments across multiple stoichiometries. Validation includes endurance, retention, and synaptic functions such as long-term potentiation/depression and spike-number/amplitude-dependent plasticity. Finally, the model is extended from single devices to a 4 × 4 crossbar array, demonstrating its scalability for artificial neural network simulations. These results emphasize the critical role of oxygen stoichiometry in CrOx/TiOy memristors and introduce a modeling framework that bridges experimental device physics with circuit-level neuromorphic applications.
Pham, P.-Q., Le, N.-L.P., Tran, T.-A., Dang, V.-S., Nguyen, Q., Pham, N.K. and Nguyen-Tran, T. (2026) Applied Physics Letters, 128(15), p. 153502.