1. Organic ferroelectric transistors with composite dielectric for efficient neural computing.
- Author
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Li, Changqing, Tian, Fuguo, Luo, Zhongzhong, Luo, Haoyang, Yan, Jie, Xu, Xiangdong, Wan, Xiang, Zhu, Li, Tan, Chee Leong, Yu, Zhihao, Xu, Yong, and Sun, Huabin
- Subjects
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ORGANIC field-effect transistors , *ENERGY storage , *CONVOLUTIONAL neural networks , *INTERFACIAL roughness , *STRAY currents , *FERROELECTRIC polymers - Abstract
Organic ferroelectric field-effect transistors (Fe-OFETs) exhibit exceptional capabilities in mimicking biological neural systems and represent one of the primary options for flexible artificial synaptic devices. Ferroelectric polymers, such as poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)), given their strong ferroelectricity and facile solution processing, have emerged as the preferred choices for the ferroelectric dielectric layer of wearable devices. However, the solution processed P(VDF-TrFE) films can lead to high interface roughness, prone to cause excessive gate leakage. Meanwhile, the ferroelectric layer in neural computing and memory applications also faces a trade-off between storage time and energy for read/write operations. This study introduces a composite dielectric layer for Fe-OFETs, fabricated via a solution-based process. Different thicknesses of poly(N-vinylcarbazole) (PVK) are shown to significantly alter the ferroelectric hysteresis window and leakage current. The optimized devices exhibit synaptic plasticity with a transient current of 3.52 mA and a response time of approximately 50 ns. The Fe-OFETs with the composite dielectric were modeled and integrated into convolutional neural networks, achieving a 92.95% accuracy rate. This highlights the composite dielectric's advantage in neuromorphic computing. The introduction of PVK optimizes the interface and balances device performance of Fe-OFETs for neuromorphic computing. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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