神经形态工程学
材料科学
可扩展性
人工神经网络
突触重量
晶体管
计算机科学
制作
灵活性(工程)
柔性电子器件
电子工程
实现(概率)
电介质
逻辑门
纳米技术
可穿戴技术
光电子学
反向传播
电子皮肤
人工智能
点间距
作者
Dongfang Shen,Yumeng Zhou,R K Li,Shengkai Xia,Lingshuo Meng,Liang Zhang,Mingjia Zhang
出处
期刊:ACS Nano
[American Chemical Society]
日期:2026-04-23
卷期号:20 (17): 13105-13115
被引量:1
标识
DOI:10.1021/acsnano.6c00995
摘要
The memtransistor constructed using the emerging two-dimensional tellurene material has demonstrated significant potential for application in artificial synaptic devices and image recognition. However, conventional device fabrication processes, such as dry transfer, restrict tellurene's further application in flexibility and wearable electronics. Here, a fully printed, flexible tellurene field-effect transistor (FET) is demonstrated, consisting of a channel, gate dielectric layer, and contact electrodes, all of which are prepared using functional inks that include tellurene, h-BN, and graphene, respectively. Such a device integrates scalable ink formulations and neuromorphic functionality for advanced electronics, exhibiting relatively stable electrical performance even after 10,000 bending cycles at a curvature radius of 11.05 mm. Applying electric stimulation to the h-BN layer enables the realization of a bioinspired memtransistor, achieving paired-pulse facilitation, reconfigurable short-term plasticity to long-term plasticity transitions, and synaptic weight updates. Moreover, image recognition simulation using an artificial neural network achieves 93.91% accuracy on the Modified National Institute of Standards and Technology database, which can maintain 78.33% accuracy after introducing σ = 0.7 Gaussian noise. These results position printed tellurene FETs as promising, noise-resilient building blocks for scalable, flexible neuromorphic systems.
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