IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-45923-7.html
   My bibliography  Save this article

VO2 memristor-based frequency converter with in-situ synthesize and mix for wireless internet-of-things

Author

Listed:
  • Chang Liu

    (Peking University)

  • Pek Jun Tiw

    (Peking University)

  • Teng Zhang

    (Peking University)

  • Yanghao Wang

    (Peking University)

  • Lei Cai

    (Peking University)

  • Rui Yuan

    (Peking University)

  • Zelun Pan

    (Peking University)

  • Wenshuo Yue

    (Peking University)

  • Yaoyu Tao

    (Peking University
    Peking University)

  • Yuchao Yang

    (Peking University
    Peking University
    Peking University
    Chinese Institute for Brain Research (CIBR), Beijing)

Abstract

Wireless internet-of-things (WIoT) with data acquisition sensors are evolving rapidly and the demand for transmission efficiency is growing rapidly. Frequency converter that synthesizes signals at different frequencies and mixes them with sensor datastreams is a key component for efficient wireless transmission. However, existing frequency converters employ separate synthesize and mix circuits with complex digital and analog circuits using complementary metal-oxide semiconductor (CMOS) devices, naturally incurring excessive latency and energy consumption. Here we report a highly uniform and calibratable VO2 memristor oscillator, based on which we build memristor-based frequency converter using 8 $$\times$$ × 8 VO2 array that can realize in-situ frequency synthesize and mix with help of compact periphery circuits. We investigate the self-oscillation based on negative differential resistance of VO2 memristors and the programmability with different driving currents and calibration resistances, demonstrating capabilities of such frequency converter for in-situ frequency synthesize and mix for 2 ~ 8 channels with frequencies up to 48 kHz for low frequency transmission link. When transmitting classical sensor data (acoustic, vision and spatial) in an end-to-end WIoT experimental setup, our VO2-based memristive frequency converter presents up to 1.45× ~ 1.94× power enhancement with only 0.02 ~ 0.21 dB performance degradations compared with conventional CMOS-based frequency converter. This work highlights the potential in solving frequency converter’s speed and energy efficiency problems in WIoT using high crystalline quality epitaxially grown VO2 and calibratable VO2-based oscillator array, revealing a promising direction for next-generation WIoT system design.

Suggested Citation

  • Chang Liu & Pek Jun Tiw & Teng Zhang & Yanghao Wang & Lei Cai & Rui Yuan & Zelun Pan & Wenshuo Yue & Yaoyu Tao & Yuchao Yang, 2024. "VO2 memristor-based frequency converter with in-situ synthesize and mix for wireless internet-of-things," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-45923-7
    DOI: 10.1038/s41467-024-45923-7
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-45923-7
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-45923-7?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. Jeffrey M. Perkel, 2017. "The Internet of Things comes to the lab," Nature, Nature, vol. 542(7639), pages 125-126, February.
    2. Rui Yuan & Qingxi Duan & Pek Jun Tiw & Ge Li & Zhuojian Xiao & Zhaokun Jing & Ke Yang & Chang Liu & Chen Ge & Ru Huang & Yuchao Yang, 2022. "A calibratable sensory neuron based on epitaxial VO2 for spike-based neuromorphic multisensory system," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Sourav Dutta & Abhinav Parihar & Abhishek Khanna & Jorge Gomez & Wriddhi Chakraborty & Matthew Jerry & Benjamin Grisafe & Arijit Raychowdhury & Suman Datta, 2019. "Programmable coupled oscillators for synchronized locomotion," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    4. Rui Yuan & Pek Jun Tiw & Lei Cai & Zhiyu Yang & Chang Liu & Teng Zhang & Chen Ge & Ru Huang & Yuchao Yang, 2023. "A neuromorphic physiological signal processing system based on VO2 memristor for next-generation human-machine interface," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    5. Wei Yi & Kenneth K. Tsang & Stephen K. Lam & Xiwei Bai & Jack A. Crowell & Elias A. Flores, 2018. "Biological plausibility and stochasticity in scalable VO2 active memristor neurons," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    6. Qingxi Duan & Zhaokun Jing & Xiaolong Zou & Yanghao Wang & Ke Yang & Teng Zhang & Si Wu & Ru Huang & Yuchao Yang, 2020. "Spiking neurons with spatiotemporal dynamics and gain modulation for monolithically integrated memristive neural networks," Nature Communications, Nature, vol. 11(1), pages 1-13, December.
    7. Yuchao Yang & Peng Gao & Linze Li & Xiaoqing Pan & Stefan Tappertzhofen & ShinHyun Choi & Rainer Waser & Ilia Valov & Wei D. Lu, 2014. "Electrochemical dynamics of nanoscale metallic inclusions in dielectrics," Nature Communications, Nature, vol. 5(1), pages 1-9, September.
    8. Yuchao Yang & Xiaoxian Zhang & Liang Qin & Qibin Zeng & Xiaohui Qiu & Ru Huang, 2017. "Probing nanoscale oxygen ion motion in memristive systems," Nature Communications, Nature, vol. 8(1), pages 1-10, 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. Rui Yuan & Pek Jun Tiw & Lei Cai & Zhiyu Yang & Chang Liu & Teng Zhang & Chen Ge & Ru Huang & Yuchao Yang, 2023. "A neuromorphic physiological signal processing system based on VO2 memristor for next-generation human-machine interface," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Rui Yuan & Qingxi Duan & Pek Jun Tiw & Ge Li & Zhuojian Xiao & Zhaokun Jing & Ke Yang & Chang Liu & Chen Ge & Ru Huang & Yuchao Yang, 2022. "A calibratable sensory neuron based on epitaxial VO2 for spike-based neuromorphic multisensory system," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Zhiyuan Li & Zhongshao Li & Wei Tang & Jiaping Yao & Zhipeng Dou & Junjie Gong & Yongfei Li & Beining Zhang & Yunxiao Dong & Jian Xia & Lin Sun & Peng Jiang & Xun Cao & Rui Yang & Xiangshui Miao & Ron, 2024. "Crossmodal sensory neurons based on high-performance flexible memristors for human-machine in-sensor computing system," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    4. Ke Yang & Yanghao Wang & Pek Jun Tiw & Chaoming Wang & Xiaolong Zou & Rui Yuan & Chang Liu & Ge Li & Chen Ge & Si Wu & Teng Zhang & Ru Huang & Yuchao Yang, 2024. "High-order sensory processing nanocircuit based on coupled VO2 oscillators," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    5. Yuan-Hang Zhang & Chesson Sipling & Erbin Qiu & Ivan K. Schuller & Massimiliano Di Ventra, 2024. "Collective dynamics and long-range order in thermal neuristor networks," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    6. Ying Zhang & Ge-Qi Mao & Xiaolong Zhao & Yu Li & Meiyun Zhang & Zuheng Wu & Wei Wu & Huajun Sun & Yizhong Guo & Lihua Wang & Xumeng Zhang & Qi Liu & Hangbing Lv & Kan-Hao Xue & Guangwei Xu & Xiangshui, 2021. "Evolution of the conductive filament system in HfO2-based memristors observed by direct atomic-scale imaging," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    7. See-On Park & Hakcheon Jeong & Jongyong Park & Jongmin Bae & Shinhyun Choi, 2022. "Experimental demonstration of highly reliable dynamic memristor for artificial neuron and neuromorphic computing," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    8. Sang Hyun Sung & Tae Jin Kim & Hyera Shin & Tae Hong Im & Keon Jae Lee, 2022. "Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    9. Ui Yeon Won & Quoc An Vu & Sung Bum Park & Mi Hyang Park & Van Dam Do & Hyun Jun Park & Heejun Yang & Young Hee Lee & Woo Jong Yu, 2023. "Multi-neuron connection using multi-terminal floating–gate memristor for unsupervised learning," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    10. Dong, Yujiao & Yang, Shuting & Liang, Yan & Wang, Guangyi, 2022. "Neuromorphic dynamics near the edge of chaos in memristive neurons," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    11. Konlechner, Roland & Allagui, Anis & Antonov, Vladimir N. & Yudin, Dmitry, 2023. "A superstatistics approach to the modelling of memristor current–voltage responses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 614(C).
    12. Milad Shafiee & Guillaume Bellegarda & Auke Ijspeert, 2024. "Viability leads to the emergence of gait transitions in learning agile quadrupedal locomotion on challenging terrains," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    13. Teresa Riso & Carla Morrone, 2023. "To Align Technological Advancement and Ethical Conduct: An Analysis of the Relationship between Digital Technologies and Sustainable Decision-Making Processes," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    14. Kafraj, Mohadeseh Shafiei & Parastesh, Fatemeh & Jafari, Sajad, 2020. "Firing patterns of an improved Izhikevich neuron model under the effect of electromagnetic induction and noise," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    15. Jaehyun Kang & Taeyoon Kim & Suman Hu & Jaewook Kim & Joon Young Kwak & Jongkil Park & Jong Keuk Park & Inho Kim & Suyoun Lee & Sangbum Kim & YeonJoo Jeong, 2022. "Cluster-type analogue memristor by engineering redox dynamics for high-performance neuromorphic computing," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    16. Tianyu Wang & Jialin Meng & Xufeng Zhou & Yue Liu & Zhenyu He & Qi Han & Qingxuan Li & Jiajie Yu & Zhenhai Li & Yongkai Liu & Hao Zhu & Qingqing Sun & David Wei Zhang & Peining Chen & Huisheng Peng & , 2022. "Reconfigurable neuromorphic memristor network for ultralow-power smart textile electronics," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    17. Zachary Laswick & Xihu Wu & Abhijith Surendran & Zhongliang Zhou & Xudong Ji & Giovanni Maria Matrone & Wei Lin Leong & Jonathan Rivnay, 2024. "Tunable anti-ambipolar vertical bilayer organic electrochemical transistor enable neuromorphic retinal pathway," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    18. Shengbo Wang & Shuo Gao & Chenyu Tang & Edoardo Occhipinti & Cong Li & Shurui Wang & Jiaqi Wang & Hubin Zhao & Guohua Hu & Arokia Nathan & Ravinder Dahiya & Luigi Giuseppe Occhipinti, 2024. "Memristor-based adaptive neuromorphic perception in unstructured environments," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    19. Liying Xu & Jiadi Zhu & Bing Chen & Zhen Yang & Keqin Liu & Bingjie Dang & Teng Zhang & Yuchao Yang & Ru Huang, 2022. "A distributed nanocluster based multi-agent evolutionary network," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    20. Ushakov, Yury & Balanov, Alexander & Savel’ev, Sergey, 2021. "Role of noise in spiking dynamics of diffusive memristor driven by heating-cooling cycles," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).

    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:15:y:2024:i:1:d:10.1038_s41467-024-45923-7. 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.