Phu-Quan Pham1,2, Ngoc-Lam Le Pham3,4, Thuy-Anh Tran1,2, Van-Son Dang4, Quang Nguyen2,5, Ngoc Kim Pham1,2, Thuat Tran Nguyen3,4
On-Pinched Hysteresis in CrOx/TiOy-based Memristive Devices: Modeling and Analysis
Appl. Phys. Lett. 128, 153502 (2026)
DOI: 10.1063/5.0332014
1 Faculty of Materials Science and Technology, University of Science, Vietnam National University – Ho Chi Minh City, Ho Chi Minh City, 72754, Vietnam
2 Vietnam National University – Ho Chi Minh City, Ho Chi Minh City, 71309, Vietnam
3 Semiconductor and Advanced Materials Institute, Technology and Innovation Park, Vietnam National University – Hanoi, Hoa Lac, Hanoi, 13151, Vietnam.
4 Faculty of Physics, University of Science, Vietnam National University – Hanoi, 334 Nguyen Trai, Thanh Xuan, Hanoi, 11406, Vietnam
5 Department of Physics, International University, Vietnam National University – Ho Chi Minh City, Ho Chi Minh City, 71309, Vietnam
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.