Inhomogeneity-facilitated application of ferroelectric barium titanate thin films in artificial neuromorphic system

The growing interest in ferroelectric materials has witnessed the thriving prospect of bio-inspired artificial neuromorphic system, where multi-level polarization states play a crucial role. In this work, with typical BaTiO3 ferroelectric thin film as the model system, we explore the physical effect...

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Bibliographic Details
Published in:Applied physics letters 2024-11, Vol.125 (19)
Main Authors: Wang, Chenxi, Guo, Lin, Hu, Junjie, Li, Titao, Zhuo, Fangping, Wu, Hong-Hui, Lu, Xiaoqiang, Zhu, Minmin
Format: Article
Language:English
Subjects:
Barium titanates
Domain walls
Electric fields
Energy consumption
Ferroelectric materials
Ferroelectricity
Hysteresis loops
Inhomogeneity
Performance enhancement
Polarization
Thin films
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Summary:The growing interest in ferroelectric materials has witnessed the thriving prospect of bio-inspired artificial neuromorphic system, where multi-level polarization states play a crucial role. In this work, with typical BaTiO3 ferroelectric thin film as the model system, we explore the physical effects of inhomogeneity on polarization switching dynamics and neuromorphic performance. Inhomogeneous films exhibited pinched polarization–electric field hysteresis loops, leading to a high recognition accuracy of 96.03% for hand-written digits, compared to about 10.31% for homogeneous films. The inhomogeneity in switching dynamics was analyzed by inhomogeneous field mechanism. Diffusive distributions of switching time and local electric fields were observed, aligning with experimental results and the expected inhomogeneity. The prolonged domain wall depinning time and lowered energy consumption suggest the potential for multi-level polarization states, a possibility further confirmed by phase-field simulations that demonstrated their presence during long-term potentiation/depression. Our work highlights the positive influence of inhomogeneity in enhancing the performance of ferroelectric-based neuromorphic systems.
ISSN:0003-6951
1077-3118
DOI:10.1063/5.0238783