Dynamic Control of Synaptic Plasticity by Competing Ferroelectric and Trap-Assisted Switching in IGZO Transistors with Al2O3/HfO2 Dielectricsopen access
- Authors
- Kwon, Ojun; Lee, Dong Ho; Oh, Seyoung; Yoon, Jongwon; Kim, Hyo-Bae; Ahn, Ji-Hoon; Park, Woojin; Kim, Han Seul; Cho, Byungjin
- Issue Date
- Sep-2025
- Publisher
- John Wiley and Sons Inc
- Keywords
- Al2O3/HfO2 high-k dielectrics; charge trapping; ferroelectric polarization; tunable synaptic dynamics
- Citation
- Advanced Functional Materials
- Indexed
- SCIE
SCOPUS
- Journal Title
- Advanced Functional Materials
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/126599
- DOI
- 10.1002/adfm.202513449
- ISSN
- 1616-301X
1616-3028
- Abstract
- Ferroelectric synaptic transistors have gained significant attention for neuromorphic applications owing to their low power consumption and high-speed modulation. However, charge trapping in ferroelectric films introduces nonlinearity, instability, and poor reproducibility during synaptic weight updates. A buried gate-structured InGaZnO synaptic transistor with an Al2O3/HfO2 dielectric stack is demonstrated in this study to achieve unprecedented conductance modulation by leveraging the frequency-dependent coupling between ferroelectric polarization and charge trapping. The versatile conductance-tuning capability of double switching modes enables even single-polarity voltage-driven potentiation and depression while simultaneously achieving highly linear conductance modulation. The diffusion of Al atoms into the HfO2 layer promotes additional oxygen vacancies, which contribute to the emergence of deep-level trap states. These defects also facilitate noncentrosymmetric crystal-phase stabilization through spontaneous symmetry breaking, thereby inducing ferroelectricity, which is corroborated by density-functional-theory simulations and piezoelectric-force-microscopy measurements. By fully utilizing dual-mode operation, the device achieves highly linear conductance updates with a minimum nonlinearity of 0.47 and enables potentiation and depression under a pulse-train configuration with a single voltage polarity. The system attains a high pattern-recognition accuracy of 97.03% for handwritten digit classification. This dual-mode operation strategy provides a compelling pathway for simplifying the architecture of integrated neuromorphic circuits and enhancing their computational efficiency.
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