Forming-free flexible memristor with multilevel storage for neuromorphic computing by full PVD technique

Flexible resistive random access memory (RRAM) has shown great potential in wearable electronics. With tunable multilevel resistance states, flexible memristors could be used to mimic the bio-synapses for constructing high-efficient wearable neuromorphic computing system. However, the flexible subst...

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Bibliographic Details
Published inJournal of materials science & technology Vol. 60; pp. 21 - 26
Main Authors Wang, Tian-Yu, Meng, Jia-Lin, Li, Qing-Xuan, Chen, Lin, Zhu, Hao, Sun, Qing-Qing, Ding, Shi-Jin, Zhang, David Wei
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 10.01.2021
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Summary:Flexible resistive random access memory (RRAM) has shown great potential in wearable electronics. With tunable multilevel resistance states, flexible memristors could be used to mimic the bio-synapses for constructing high-efficient wearable neuromorphic computing system. However, the flexible substrate has intrinsic disadvantages including low-temperature tolerance and poor complementary metal-oxide-semiconductor (CMOS) compatibility, which limit the development of flexible electronics. The physical vapor deposition (PVD) fabrication process could prepare RRAM without requirement of further treatment, which greatly simplified preparation steps and reduced the production costs. On the other hand, forming process, as a common pre-programing operation in RRAM, increases the energy consumption and limits the application scenarios of RRAM. Here, a NiO-based forming-free RRAM with low set voltage was fabricated via full PVD technique. The flexible device exhibited reliable resistive switching characteristics under flat state even compressive and tensile states (R = 10 mm). The tunable multilevel resistance states (5 levels) could be obtained by controlling the compliance current. Besides, synaptic plasticities also were verified in this device. The flexible NiO-based RRAM shows great potential in wearable forming-free multibit memory and neuromorphic computing electronics.
ISSN:1005-0302
1941-1162
DOI:10.1016/j.jmst.2020.04.059