Non-pinched hysteresis in CrO <i>x</i> /TiO <i>y</i> -based memristive devices: Modeling and analysis

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.

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Publication Details

Journal
Applied Physics Letters
Published
2026-04-13
DOI
https://doi.org/10.1063/5.0332014
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Non-pinched hysteresis in CrO x /TiO y -based memristive devices: Modeling and analysis

Ngoc Kim Pham, Phu‐Quan Pham, T. Ngoc Tran, Van-Son Dang et al.
Applied Physics Letters
Advanced Memory and Neural Computing
article

Non-pinched hysteresis in CrO x /TiO y -based memristive devices: Modeling and analysis

Ngoc Kim Pham, Phu‐Quan Pham, T. Ngoc Tran, Van-Son Dang, Quang Nguyen, Thuat Nguyen-Tran, Ngoc-Lam Pham Le
article en

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.

Applied Physics LettersVol. 128(15)
Vietnam National University Ho Chi Minh City (VN), National Economics University (VN), Vietnam National University, Hanoi (VN), Ho Chi Minh City International University (VN), VNU University of Science (VN)
Quỹ Đổi mới sáng tạo Vingroup
Reduced inequalities
Openalex Percentile: Top 23%
Advanced Memory and Neural Computing
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