A multimode‐fused sensory memory system based on a robust self‐assembly nanoscaffolded BaTiO3:Eu2O3 memristor
Xiaobing Yan,
Yinxing Zhang,
Ziliang Fang,
Yong Sun,
Pan Liu,
Jiameng Sun,
Xiaotong Jia,
Shiqing Sun,
Zhenqiang Guo,
Zhen Zhao
Affiliations
Xiaobing Yan
School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering Hebei University Baoding the People's Republic of China
Yinxing Zhang
School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering Hebei University Baoding the People's Republic of China
Ziliang Fang
School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering Hebei University Baoding the People's Republic of China
Yong Sun
School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering Hebei University Baoding the People's Republic of China
Pan Liu
School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering Hebei University Baoding the People's Republic of China
Jiameng Sun
School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering Hebei University Baoding the People's Republic of China
Xiaotong Jia
School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering Hebei University Baoding the People's Republic of China
Shiqing Sun
School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering Hebei University Baoding the People's Republic of China
Zhenqiang Guo
School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering Hebei University Baoding the People's Republic of China
Zhen Zhao
School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain‐Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering Hebei University Baoding the People's Republic of China
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/BaTiO3:Eu2O3/La0.67Sr0.33MnO3 grown on Silicon structure with SrTiO3 as buffer layer is presented. The device possesses low coercive field voltage (−1.3–2.1 V) and robust endurance characteristic (~1010 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.