Leng Kangmin, Zhu Xu, Ma Zhongyuan, Yu Xinyue, Xu Jun, Xu Ling, Li Wei, Chen Kunji
The School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.
Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China.
Nanomaterials (Basel). 2022 Jan 18;12(3):311. doi: 10.3390/nano12030311.
As the building block of brain-inspired computing, resistive switching memory devices have recently attracted great interest due to their biological function to mimic synapses and neurons, which displays the memory switching or threshold switching characteristic. To make it possible for the Si-based artificial neurons and synapse to be integrated with the neuromorphic chip, the tunable threshold and memory switching characteristic is highly in demand for their perfect compatibility with the mature CMOS technology. We first report artificial neurons and synapses based on the Al/a-SiNO:H/P-Si device with the tunable switching from threshold to memory can be realized by controlling the compliance current. It is found that volatile TS from Al/a-SiNO:H/P-Si device under the lower compliance current is induced by the weak Si dangling bond conductive pathway, which originates from the broken Si-H bonds. While stable nonvolatile MS under the higher compliance current is attributed to the strong Si dangling bond conductive pathway, which is formed by the broken Si-H and Si-O bonds. Theoretical calculation reveals that the conduction mechanism of TS and MS agree with P-F model, space charge limited current model and Ohm's law, respectively. The tunable TS and MS characteristic of Al/a-SiNO:H/P-Si device can be successfully employed to mimic the biological behavior of neurons and synapse including the integrate-and-fire function, paired-pulse facilitation, long-term potentiation and long-term depression as well as spike-timing-dependent plasticity. Our discovery supplies an effective way to construct the neuromorphic devices for brain-inspired computing in the AI period.
作为受大脑启发的计算的基石，电阻开关记忆器件最近因其模仿突触和神经元的生物学功能而备受关注，该功能呈现出记忆开关或阈值开关特性。为了使基于硅的人工神经元和突触能够与神经形态芯片集成，可调阈值和记忆开关特性对于它们与成熟的互补金属氧化物半导体（CMOS）技术的完美兼容性至关重要。我们首次报道了基于Al/a-SiNO:H/P-Si器件的人工神经元和突触，通过控制顺从电流可以实现从阈值到记忆的可调开关。研究发现，在较低顺从电流下，Al/a-SiNO:H/P-Si器件的挥发性阈值开关（TS）是由弱硅悬键导电通路引起的，该通路源于Si-H键的断裂。而在较高顺从电流下稳定的非挥发性记忆开关（MS）则归因于强硅悬键导电通路，它是由Si-H键和Si-O键的断裂形成的。理论计算表明，TS和MS的传导机制分别与P-F模型、空间电荷限制电流模型和欧姆定律一致。Al/a-SiNO:H/P-Si器件的可调TS和MS特性可以成功地用于模仿神经元和突触的生物学行为，包括积分发放功能、双脉冲易化、长时程增强和长时程抑制以及尖峰时间依赖可塑性。我们的发现为人工智能时代构建受大脑启发的计算的神经形态器件提供了一种有效方法。
