Yang Ruqi, Yin Lei, Lu Jianguo, Lu Bojing, Pi Xiaodong, Li Siqin, Zhuge Fei, Lu Yangdan, Shao Wenyi, Ye Zhizhen
State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China.
Wenzhou Key Laboratory of Novel Optoelectronic and Nano Materials, Institute of Wenzhoum, Zhejiang University, Wenzhou325006, China.
ACS Appl Mater Interfaces. 2022 Oct 19;14(41):46866-46875. doi: 10.1021/acsami.2c14029. Epub 2022 Oct 4.
Neuromorphic computing, which mimics brain function, can address the shortcomings of the "von Neumann" system and is one of the critical components of next-generation computing. The use of light to stimulate artificial synapses has the advantages of low power consumption, low latency, and high stability. We demonstrate amorphous InAlZnO-based light-stimulated artificial synaptic devices with a thin-film transistor structure. The devices exhibit fundamental synaptic properties, including excitatory postsynaptic current, paired-pulse facilitation (PPF), and short-term plasticity to long-term plasticity conversion under light stimulation. The PPF index stimulated by 375 nm light is 155.9% when the time interval is 0.1 s. The energy consumption of each synaptic event is 2.3 pJ, much lower than that of ordinary MOS devices and other optical-controlled synaptic devices. The relaxation time constant reaches 277 s after only 10 light spikes, which shows the great synaptic plasticity of the device. In addition, we simulated the learning-forgetting-relearning-forgetting behavior and learning efficiency of human beings under different moods by changing the gate voltage. This work is expected to promote the development of high-performance optoelectronic synaptic devices for neuromorphic computing.
模仿大脑功能的神经形态计算能够解决“冯·诺依曼”系统的缺点,是下一代计算的关键组成部分之一。利用光来刺激人工突触具有低功耗、低延迟和高稳定性的优点。我们展示了具有薄膜晶体管结构的基于非晶铟铝锌氧化物的光刺激人工突触器件。这些器件展现出基本的突触特性,包括兴奋性突触后电流、双脉冲易化(PPF)以及在光刺激下从短期可塑性到长期可塑性的转变。当时间间隔为0.1秒时,由375纳米光刺激的PPF指数为155.9%。每个突触事件的能量消耗为2.3皮焦,远低于普通MOS器件和其他光控突触器件。仅经过10次光脉冲后,弛豫时间常数就达到277秒,这表明该器件具有很强的突触可塑性。此外,我们通过改变栅极电压模拟了人类在不同情绪下的学习 - 遗忘 - 再学习 - 遗忘行为和学习效率。这项工作有望推动用于神经形态计算的高性能光电突触器件的发展。