Multifunctional Polymer Memory via Bi‐Interfacial Topography for Pressure Perception Recognition. Issue 8 (25th February 2020)

• Record Type: Journal Article
• Authors: Wang, Xiangjing; Zhou, Zhe; Ban, Chaoyi; Zhang, Zepu; Ju, Shang; Huang, Xiao; Mao, Huiwu; Chang, Qing; Yin, Yuhang; Song, Mengya; Cheng, Shuai; Ding, Yamei; Liu, Zhengdong; Ju, Ruolin; Xie, Linghai; Miao, Feng; Liu, Juqing; Huang, Wei
• Is Part Of: Advanced science. Volume 7:Issue 8(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-02-25
• Subjects: memristors -- multimode -- nanoholes -- nanowrinkles -- recognition memory; Science -- Periodicals; 505
• DOI: 10.1002/advs.201902864
• Languages: English
• ISSNs: 2198-3844

Abstract

Abstract: Emerging memory devices, that can provide programmable information recording with tunable resistive switching under external stimuli, hold great potential for applications in data storage, logic circuits, and artificial synapses. Realization of multifunctional manipulation within individual memory devices is particularly important in the More‐than‐Moore era, yet remains a challenge. Here, both rewritable and nonerasable memory are demonstrated in a single stimuli‐responsive polymer diode, based on a nanohole‐nanowrinkle bi‐interfacial structure. Such synergic nanostructure is constructed from interfacing a nanowrinkled bottom graphene electrode and top polymer matrix with nanoholes; and it can be easily prepared by spin coating, which is a low‐cost and high‐yield production method. Furthermore, the resulting device, with ternary and low‐power operation under varied external stimuli, can enable both reversible and irreversible biomimetic pressure recognition memories using a device‐to‐system framework. This work offers both a general guideline to fabricate multifunctional memory devices via interfacial nanostructure engineering and a smart information storage basis for future artificial intelligence. Abstract : A general guideline for fabricating a multimode memristor based on spontaneously formed bi‐interfacial nanostructures is proposed to simulate the somatosensory recognition memory.