Novel Two-Terminal Synapse/Neuron Based on an Antiferroelectric Hafnium Zirconium Oxide Device for Neuromorphic Computing
Functionally diverse devices with artificial neuron and synapse properties are critical for neuromorphic systems. We present a two-terminal artificial leaky-integrate-fire (LIF) neuron based on 6 nm Hf<sub>0.1</sub>Zr<sub>0.9</sub>O<sub>2</sub> (HZO) antiferroelectric (AFE) thin films and develop a synaptic device through work function (WF) engineering. LIF neuron characteristics, including integration, firing, and leakage, are achieved in W/HZO/W devices due to the accumulated polarization and spontaneous depolarization of AFE HZO films. By engineering the top electrode with asymmetric WFs, we found that Au/Ti/HZO/W devices exhibit synaptic weight plasticity, such as paired-pulse facilitation and long-term potentiation/depression, achieving >90% accuracy in digit recognition within constructed artificial neural network systems. These findings suggest that AFE HZO capacitor-based neurons and WF-engineered artificial synapses hold promise for constructing efficient spiking neuron networks and artificial neural networks, thereby advancing neuromorphic computing applications based on emerging AFE HZO devices.
Authors
- Jiajie Yu
- Yinchi Liu (ORCID: https://orcid.org/0009-0007-8361-2879)
- Hao Zhu (ORCID: https://orcid.org/0000-0003-3890-6871)
- Zhenhai Li (ORCID: https://orcid.org/0000-0001-9878-3274)
- Yongkai Liu (ORCID: https://orcid.org/0009-0009-2875-1096)
- Lu Chen (ORCID: https://orcid.org/0009-0008-1201-676X)
- David Wei Zhang
- Tianyu Wang (ORCID: https://orcid.org/0000-0001-8114-3481)
- Qingqing Sun (ORCID: https://orcid.org/0000-0002-6533-1834)
- Lin Chen (ORCID: https://orcid.org/0000-0002-7145-7564)
- Jialin Meng (ORCID: https://orcid.org/0000-0002-2166-3220)
- Kangli Xu (ORCID: https://orcid.org/0000-0002-8077-3593)
- Yifan Song (ORCID: https://orcid.org/0009-0001-8646-3916)
Institutions
- Shandong University (CN)
- Chinese Academy of Sciences (CN)
- Fudan University (CN)
- Shanghai Innovative Research Center of Traditional Chinese Medicine (CN)
- Jiaxing University (CN)
- Suzhou Research Institute (CN)
- Shanghai Fudan Microelectronics (China) (CN)
- Shanghai Institute of Microsystem and Information Technology (CN)
Publication Details
- Journal
- Nano Letters
- Published
- 2024-08-15
- DOI
- https://doi.org/10.1021/acs.nanolett.4c02142
- Citations
- 18
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 3.76
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Science and Technology Commission of Shanghai Municipality
- Natural Science Foundation of Jiangsu Province
- National Key Research and Development Program of China