Literature DB >> 29665257

Scaling Effect on Silicon Nitride Memristor with Highly Doped Si Substrate.

Sungjun Kim1, Sunghun Jung2, Min-Hwi Kim2, Ying-Chen Chen3, Yao-Feng Chang3, Kyung-Chang Ryoo2, Seongjae Cho4, Jong-Ho Lee2, Byung-Gook Park2.   

Abstract

A feasible approach is reported to reduce the switching current and increase the nonlinearity in a complementary metal-oxide-semiconductor (CMOS)-compatible Ti/SiNx /p+ -Si memristor by simply reducing the cell size down to sub-100 nm. Even though the switching voltages gradually increase with decreasing device size, the reset current is reduced because of the reduced current overshoot effect. The scaled devices (sub-100 nm) exhibit gradual reset switching driven by the electric field, whereas that of the large devices (≥1 µm) is driven by Joule heating. For the scaled cell (60 nm), the current levels are tunable by adjusting the reset stop voltage for multilevel cells. It is revealed that the nonlinearity in the low-resistance state is attributed to Fowler-Nordheim tunneling dominating in the high-voltage regime (≥1 V) for the scaled cells. The experimental findings demonstrate that the scaled metal-nitride-silicon memristor device paves the way to realize CMOS-compatible high-density crosspoint array applications.
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  low-power; memristors; nonlinearity; scaling; silicon nitride

Year:  2018        PMID: 29665257     DOI: 10.1002/smll.201704062

Source DB:  PubMed          Journal:  Small        ISSN: 1613-6810            Impact factor:   13.281


  3 in total

1.  All-Printed Flexible Memristor with Metal-Non-Metal-Doped TiO2 Nanoparticle Thin Films.

Authors:  Maryam Khan; Hafiz Mohammad Mutee Ur Rehman; Rida Tehreem; Muhammad Saqib; Muhammad Muqeet Rehman; Woo-Young Kim
Journal:  Nanomaterials (Basel)       Date:  2022-07-03       Impact factor: 5.719

2.  Donor-acceptor-type poly[chalcogenoviologen-alt-triphenylamine] for synaptic biomimicking and neuromorphic computing.

Authors:  Zhizheng Zhao; Qiang Che; Kexin Wang; Mohamed E El-Khouly; Jiaxuan Liu; Yubin Fu; Bin Zhang; Yu Chen
Journal:  iScience       Date:  2021-12-16

3.  Artificial Neurons and Synapses Based on Al/a-SiNxOy:H/P+-Si Device with Tunable Resistive Switching from Threshold to Memory.

Authors:  Kangmin Leng; Xu Zhu; Zhongyuan Ma; Xinyue Yu; Jun Xu; Ling Xu; Wei Li; Kunji Chen
Journal:  Nanomaterials (Basel)       Date:  2022-01-18       Impact factor: 5.076

  3 in total

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