材料科学
电介质
晶体管
光电子学
突触重量
驻极体
梯度下降
纳米技术
弯曲半径
高-κ电介质
电压
计算机科学
人工神经网络
复合材料
电气工程
弯曲
人工智能
工程类
作者
Yushan Li,Wei Cai,R. Tao,Wentao Shuai,Jingjing Rao,Cheng Chang,Xubing Lu,Honglong Ning
标识
DOI:10.1021/acsami.4c02880
摘要
Inkjet printing artificial synapse is cost-effective but challenging in emulating synaptic dynamics with a sufficient number of effective weight states under ultralow voltage spiking operation. A synaptic transistor gated by inkjet-printed composite dielectric of polar-electret polyvinylpyrrolidone (PVP) and high-k zirconia oxide (ZrOx) is proposed and thus synthesized to solve this issue. Quasi-linear weight update with a large variation margin is obtained through the coupling effect and the facilitation of dipole orientation, which can be attributed to the orderly arranged molecule chains induced by the carefully designed microfluidic flows. Crucial features of biological synapses including long-term plasticity, spike-timing-dependence-plasticity (STDP), "Learning-Experience" behavior, and ultralow energy consumption (<10 fJ/pulse) are successfully implemented on the device. Simulation results exhibit an excellent image recognition accuracy (97.1%) after 15 training epochs, which is the highest for printed synaptic transistors. Moreover, the device sustained excellent endurance against bending tests with radius down to 8 mm. This work presents a very viable solution for constructing the futuristic flexible and low-cost neural systems.
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