Construction of polar topological nanodevices for neuromorphic computing

The research field of polar topological domains has witnessed rapid expansion in recent years, inspired by the vast application potentials for future topological electronic devices. Nonetheless, such topological devices remain elusive. In this study, we implemented the polar topological domain structures as neuromorphic computing elements, and present 12-state non-volatile ferroelectric topological nanodevices that demonstrate exceptional neuromorphic computing capabilities through the controlled formation and erasure of walls. These nanodevices exhibit near-linear long-term potentiation and long-term depression characteristics under repetitive voltage pulses, achieving a remarkable dynamic range. Simulations using a convolutional neural network model with these devices attain 95% recognition accuracy on the Modified National Institute of Standards and Technology handwritten digits dataset within 100 epochs. These results expand the functional scope of polar topological electronic devices to future neuromorphic computing systems.

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Publication Details

Journal
Applied Physics Reviews
Published
2025-12-01
DOI
https://doi.org/10.1063/5.0294235
Primary Topic
Ferroelectric and Negative Capacitance Devices
Type
article
Field-Weighted Citation Impact
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article

Construction of polar topological nanodevices for neuromorphic computing

Yihang Guo, Zhen Hong Fan, Shuoshuo Ma, Jun‐Ming Liu et al.
Applied Physics Reviews
Ferroelectric and Negative Capacitance Devices
article

Construction of polar topological nanodevices for neuromorphic computing

Yihang Guo, Zhen Hong Fan, Shuoshuo Ma, Jun‐Ming Liu, Houlin Zhou, Songhua Cai, Zhiqing Song, Minghui Qin, Xingsen Gao, Jiyan Dai, Wentao Shuai, Guo Tian, Jiaqi Zhang, Wenjie Li, Jianbiao Xian
article en

Abstract

The research field of polar topological domains has witnessed rapid expansion in recent years, inspired by the vast application potentials for future topological electronic devices. Nonetheless, such topological devices remain elusive. In this study, we implemented the polar topological domain structures as neuromorphic computing elements, and present 12-state non-volatile ferroelectric topological nanodevices that demonstrate exceptional neuromorphic computing capabilities through the controlled formation and erasure of walls. These nanodevices exhibit near-linear long-term potentiation and long-term depression characteristics under repetitive voltage pulses, achieving a remarkable dynamic range. Simulations using a convolutional neural network model with these devices attain 95% recognition accuracy on the Modified National Institute of Standards and Technology handwritten digits dataset within 100 epochs. These results expand the functional scope of polar topological electronic devices to future neuromorphic computing systems.

Applied Physics ReviewsVol. 12(4)
Hong Kong Polytechnic University (HK), South China Normal University (CN), Collaborative Innovation Center of Advanced Microstructures (CN), Nanjing University (CN)
Openalex Percentile: Top 60%
Ferroelectric and Negative Capacitance Devices
DOISourceOpenAlex
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