IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-41868-5.html
   My bibliography  Save this article

CMOS backend-of-line compatible memory array and logic circuitries enabled by high performance atomic layer deposited ZnO thin-film transistor

Author

Listed:
  • Wenhui Wang

    (Southern University of Science and Technology)

  • Ke Li

    (Southern University of Science and Technology)

  • Jun Lan

    (Southern University of Science and Technology)

  • Mei Shen

    (Southern University of Science and Technology)

  • Zhongrui Wang

    (The University of Hong Kong)

  • Xuewei Feng

    (Shanghai Jiao Tong University)

  • Hongyu Yu

    (Southern University of Science and Technology)

  • Kai Chen

    (Southern University of Science and Technology)

  • Jiamin Li

    (Southern University of Science and Technology)

  • Feichi Zhou

    (Southern University of Science and Technology)

  • Longyang Lin

    (Southern University of Science and Technology)

  • Panpan Zhang

    (Beijing University of Posts and Telecommunications)

  • Yida Li

    (Southern University of Science and Technology)

Abstract

The development of high-performance oxide-based transistors is critical to enable very large-scale integration (VLSI) of monolithic 3-D integrated circuit (IC) in complementary metal oxide semiconductor (CMOS) backend-of-line (BEOL). Atomic layer deposition (ALD) deposited ZnO is an attractive candidate due to its excellent electrical properties, low processing temperature below copper interconnect thermal budget, and conformal sidewall deposition for novel 3D architecture. An optimized ALD deposited ZnO thin-film transistor achieving a record field-effect and intrinsic mobility (µFE /µo) of 85/140 cm2/V·s is presented here. The ZnO TFT was integrated with HfO2 RRAM in a 1 kbit (32 × 32) 1T1R array, demonstrating functionalities in RRAM switching. In order to co-design for future technology requiring high performance BEOL circuitries implementation, a spice-compatible model of the ZnO TFTs was developed. We then present designs of various ZnO TFT-based inverters, and 5-stage ring oscillators through simulations and experiments with working frequency exceeding 10’s of MHz.

Suggested Citation

  • Wenhui Wang & Ke Li & Jun Lan & Mei Shen & Zhongrui Wang & Xuewei Feng & Hongyu Yu & Kai Chen & Jiamin Li & Feichi Zhou & Longyang Lin & Panpan Zhang & Yida Li, 2023. "CMOS backend-of-line compatible memory array and logic circuitries enabled by high performance atomic layer deposited ZnO thin-film transistor," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41868-5
    DOI: 10.1038/s41467-023-41868-5
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-41868-5
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-41868-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Max M. Shulaker & Gage Hills & Rebecca S. Park & Roger T. Howe & Krishna Saraswat & H.-S. Philip Wong & Subhasish Mitra, 2017. "Three-dimensional integration of nanotechnologies for computing and data storage on a single chip," Nature, Nature, vol. 547(7661), pages 74-78, July.
    2. Maheswari Sivan & Yida Li & Hasita Veluri & Yunshan Zhao & Baoshan Tang & Xinghua Wang & Evgeny Zamburg & Jin Feng Leong & Jessie Xuhua Niu & Umesh Chand & Aaron Voon-Yew Thean, 2019. "All WSe2 1T1R resistive RAM cell for future monolithic 3D embedded memory integration," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    3. Baoshan Tang & Hasita Veluri & Yida Li & Zhi Gen Yu & Moaz Waqar & Jin Feng Leong & Maheswari Sivan & Evgeny Zamburg & Yong-Wei Zhang & John Wang & Aaron V-Y. Thean, 2022. "Wafer-scale solution-processed 2D material analog resistive memory array for memory-based computing," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    4. Yang Liu & Sheng Wang & Huaping Liu & Lian-Mao Peng, 2017. "Carbon nanotube-based three-dimensional monolithic optoelectronic integrated system," Nature Communications, Nature, vol. 8(1), pages 1-8, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maosong Xie & Yueyang Jia & Chen Nie & Zuheng Liu & Alvin Tang & Shiquan Fan & Xiaoyao Liang & Li Jiang & Zhezhi He & Rui Yang, 2023. "Monolithic 3D integration of 2D transistors and vertical RRAMs in 1T–4R structure for high-density memory," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Yuxuan Zhang & You Meng & Liqiang Wang & Changyong Lan & Quan Quan & Wei Wang & Zhengxun Lai & Weijun Wang & Yezhan Li & Di Yin & Dengji Li & Pengshan Xie & Dong Chen & Zhe Yang & SenPo Yip & Yang Lu , 2024. "Pulse irradiation synthesis of metal chalcogenides on flexible substrates for enhanced photothermoelectric performance," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    3. Wei Su & Xiao Li & Linhai Li & Dehua Yang & Futian Wang & Xiaojun Wei & Weiya Zhou & Hiromichi Kataura & Sishen Xie & Huaping Liu, 2023. "Chirality-dependent electrical transport properties of carbon nanotubes obtained by experimental measurement," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    4. Yijun Li & Jianshi Tang & Bin Gao & Jian Yao & Anjunyi Fan & Bonan Yan & Yuchao Yang & Yue Xi & Yuankun Li & Jiaming Li & Wen Sun & Yiwei Du & Zhengwu Liu & Qingtian Zhang & Song Qiu & Qingwen Li & He, 2023. "Monolithic three-dimensional integration of RRAM-based hybrid memory architecture for one-shot learning," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    5. Shengqi Wang & Wenjie Li & Junying Xue & Jifeng Ge & Jing He & Junyang Hou & Yu Xie & Yuan Li & Hao Zhang & Zdeněk Sofer & Zhaoyang Lin, 2024. "A library of 2D electronic material inks synthesized by liquid-metal-assisted intercalation of crystal powders," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    6. Fernando Aguirre & Abu Sebastian & Manuel Gallo & Wenhao Song & Tong Wang & J. Joshua Yang & Wei Lu & Meng-Fan Chang & Daniele Ielmini & Yuchao Yang & Adnan Mehonic & Anthony Kenyon & Marco A. Villena, 2024. "Hardware implementation of memristor-based artificial neural networks," Nature Communications, Nature, vol. 15(1), pages 1-40, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41868-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.