Fully hafnium-based ferroelectric/antiferroelectric devices for hybrid SNN neuromorphic computing

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Abstract
Neuromorphic computing based on ferroelectric devices has shown great potential in artificial intelligence tasks. However, the challenge of heterogeneous integration between synaptic and neuronal devices has imposed additional limitations on hybrid neural network hardware. In this work, ferroelectric and antiferroelectric devices based on element doping engineering of HfZrOx films are employed to emulate synaptic and neuron functionality for hybrid spiking neural network (SNN) neuromorphic computing. By constructing a functional circuit based on an Hf0.5Zr0.5O2 ferroelectric device, neural characteristics were emulated for SNN computing. Furthermore, the integrate-and-fire dynamics is implemented based on spontaneous depolarization characteristic of a full hafnium-based hybrid ferroelectric neural network, greatly simplifying conventional neuron circuits. The novel neural network architecture achieves a classification accuracy of 92.8% on the Dynamic Vision Sensor dataset, establishing a crucial foundation for the development of high-efficiency neuromorphic computing systems. This work demonstrates considerable promise for realizing hybrid neuromorphic hardware using CMOS-compatible full hafnium-based ferroelectric devices.
Funding Information
  • National Natural Science Foundation of China (12474071)
  • Natural Science Foundation of Shandong Province (ZR2025ZD10)
  • Natural Science Foundation of Shandong Province (ZR2025QB50)
  • Natural Science Foundation of Shandong Province (ZR2024YQ051)
  • Basic and Applied Basic Research Foundation of Guangdong Province (2025A1515011191)
  • Shanghai Sailing Program (23YF1402200)
  • Shanghai Sailing Program (23YF1402400)
  • Basic Research Program of Jiangsu Province (BK20250420)
  • Basic Research Program of Jiangsu Province (BK20240424)
  • open resarch fund of state key laboratory of crystal materials (KF2406)
  • Taishan Scholar Foundation of Shandong Province (tsqn202507058)
  • Taishan Scholar Foundation of Shandong Province (tsqn202408006)
  • Young Talent of Lifting engineering for Science and Technology in Shandong (SDAST2024QTB002)
  • Qilu Young Scholar Program of Shandong University (none)

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