Xu Kangli, Wang Tianyu, Lu Chen, Song Yifan, Liu Yongkai, Yu Jiajie, Liu Yinchi, Li Zhenhai, Meng Jialin, Zhu Hao, Sun Qing-Qing, Zhang David Wei, Chen Lin
School of Microelectronics, State Key Laboratory of Integrated Chips and Systems, Fudan University, Shanghai 200433, P. R. China.
School of Integrated Circuits, Shandong University, Jinan 250100, China.
Nano Lett. 2024 Sep 11;24(36):11170-11178. doi: 10.1021/acs.nanolett.4c02142. Epub 2024 Aug 15.
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 HfZrO (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.
具有人工神经元和突触特性的功能多样的器件对于神经形态系统至关重要。我们展示了一种基于6纳米铪锆氧化物（HZO）反铁电（AFE）薄膜的两端人工漏电积分发放（LIF）神经元，并通过功函数（WF）工程开发了一种突触器件。由于AFE HZO薄膜的极化积累和自发去极化，在W/HZO/W器件中实现了LIF神经元特性，包括积分、发放和漏电。通过用不对称功函数设计顶部电极，我们发现Au/Ti/HZO/W器件表现出突触权重可塑性，如双脉冲易化和长时程增强/抑制，在构建的人工神经网络系统中数字识别准确率达到90%以上。这些发现表明，基于AFE HZO电容器的神经元和功函数工程化的人工突触有望构建高效的脉冲神经元网络和人工神经网络，从而推动基于新兴AFE HZO器件的神经形态计算应用。
