Oh Seyong, Cho Jeong-Ick, Lee Byeong Hyeon, Seo Seunghwan, Lee Ju-Hee, Choo Hyongsuk, Heo Keun, Lee Sang Yeol, Park Jin-Hong
Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea.
Department of Microdevice Engineering, Korea University, Seoul 02841, Korea.
Sci Adv. 2021 Oct 29;7(44):eabg9450. doi: 10.1126/sciadv.abg9450.
We propose a flexible artificial synapse based on a silicon-indium-zinc-oxide (SIZO)/ion gel hybrid structure directly fabricated on a polyimide substrate, where the channel conductance is effectively modulated via ion movement in the ion gel. This synaptic operation is possible because of the low-temperature deposition process of the SIZO layer (<150°C) and the surface roughness improvement of the poly(4-vinylphenol) buffer layer (12.29→1.81 nm). The flexible synaptic device exhibits extremely stable synaptic performance under high mechanical (bending 1500 times with a radius of 5 mm) and electrical stress (application of voltage pulses 10 times) without any degradation. Last, a sensory-neuromorphic system for sign language translation, which consists of stretchable resistive sensors and flexible artificial synapses, is designed and successfully evaluated via training and recognition simulation using hand sign patterns obtained by stretchable sensors (maximum recognition rate, 99.4%).
我们提出了一种基于硅铟锌氧化物(SIZO)/离子凝胶混合结构的柔性人工突触,该结构直接制备在聚酰亚胺衬底上,其中沟道电导通过离子凝胶中的离子移动得到有效调制。由于SIZO层的低温沉积工艺(<150°C)以及聚(4-乙烯基苯酚)缓冲层表面粗糙度的改善(从12.29纳米降至1.81纳米),这种突触操作得以实现。该柔性突触器件在高机械应力(以5毫米半径弯曲1500次)和电应力(施加电压脉冲10次)下表现出极其稳定的突触性能,且无任何退化。最后,设计了一种用于手语翻译的传感神经形态系统,该系统由可拉伸电阻式传感器和柔性人工突触组成,并通过使用可拉伸传感器获取的手语模式进行训练和识别模拟,成功地进行了评估(最大识别率为99.4%)。