纳米片
材料科学
记忆电阻器
纳米技术
计算机科学
机器人
功率(物理)
人工神经网络
电压
人工智能
电气工程
电子工程
工程类
物理
量子力学
作者
Yilong Wang,Jie Su,Guoyao Ouyang,Sunyingyue Geng,Mengchen Ren,Weiliang Pan,Jing Bian,Minghui Cao
标识
DOI:10.1002/adfm.202316397
摘要
Abstract The flexible biomimetic sensory system inspired by biology exhibits learning, memory, and cognitive behavior toward external stimuli, providing a promising direction for the future development of the artificial intelligence industry. In this work, a Zn‐TCPP (TCPP: tetrakis (4‐carboxyphenyl) porphyrin) based flexible memristor with ultra‐low both operating voltage (≈80 mV) and power consumption (0.39 nW) that simulates typical synaptic plasticities, under continuously adjustable ultra‐low voltage pulses (50 mV). The synaptic properties are well maintained even when bending 1000 times at a radius of 5 mm. Furthermore, the flexible bionic sensing system integrated with Zn‐TCPP based memristor and cotton fibre piezoresistive sensor can remember pressure and deformation current, thus simulate the learning‐forgetting‐relearning characteristics under mechanical stimuli (power supply = 100 mV). Especially, the system achieves a high recognition rate of 97% for gestures through self‐built datasets and neural network calculations and remains at a high level under the influence of 10% Gaussian noise (80%) and 5 mm bending state (91%). Consequently, the ultralow‐power flexible biomimetic sensing system shows great potential in the field of integrated artificial intelligence with multiple modules, paving the way for the development of low‐power biomimetic robots in the future.
科研通智能强力驱动
Strongly Powered by AbleSci AI