Home /Research /A multimode‐fused sensory memory system based on a robust self‐assembly nanoscaffolded <scp>BaTiO<sub>3</sub></scp>:<scp>Eu<sub>2</sub>O<sub>3</sub></scp> memristor
PERCEPTION

A multimode‐fused sensory memory system based on a robust self‐assembly nanoscaffolded <scp>BaTiO<sub>3</sub></scp>:<scp>Eu<sub>2</sub>O<sub>3</sub></scp> memristor

Xiaobing Yan, Yinxing Zhang, Ziliang Fang, Yong Sun, Pan Liu, Jiameng Sun, Xiaotong Jia, Shiqing Sun, Zhenqiang Guo, Zhen Zhao

Year
2023
Citations
43
Access
Open access

Abstract

Abstract Biologically inspired neuromorphic sensory memory systems based on memristor have received a lot of attention in the booming artificial intelligence industry due to significant potential to effectively process multi‐sensory signals from complex external environments. However, many memristors have significant switching parameters disperse, which is a great challenge for using memristors in bionic neuromorphic sensory memory systems. Herein, a stable ferroelectric memristor based on the Pd/BaTiO 3 :Eu 2 O 3 /La 0.67 Sr 0.33 MnO 3 grown on Silicon structure with SrTiO 3 as buffer layer is presented. The device possesses low coercive field voltage (−1.3–2.1 V) and robust endurance characteristic (~10 10 cycles) through optimizing the growth temperature. More importantly, an ultra‐stable artificial multimodal sensory memory system with visual and tactile functions was reported for the first time by combining a pressure sensor, a photosensitive sensor, and a robotic arm. Utilizing the above system, the sensitivity value of the system is expressed by the conductance of the memristor to realize the gradual change of external stimulus, and multi signals inputs at the same time to this system have faithfully achieved sensory adaptation to multimodal sensors. This work paves the way for future development of memristor‐based perception systems in efficient multisensory neural robots. image

Keywords

MemristorNeuromorphic engineeringSensory systemComputer scienceMaterials scienceArtificial intelligenceArtificial neural networkEngineeringElectronic engineeringNeuroscience

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