IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i8p2117-d163675.html
   My bibliography  Save this article

Synthesis of the ZnO@ZnS Nanorod for Lithium-Ion Batteries

Author

Listed:
  • Haipeng Li

    (School of Materials Science and Engineering, Hebei University of Technology, Tianjin 300130, China)

  • Jiayi Wang

    (School of Materials Science and Engineering, Hebei University of Technology, Tianjin 300130, China)

  • Yan Zhao

    (School of Materials Science and Engineering, Hebei University of Technology, Tianjin 300130, China)

  • Taizhe Tan

    (Synergy Innovation Institute of Guangdong University of Technology, Heyuan 517000, China)

Abstract

The ZnO@ZnS nanorod is synthesized by solvothermal method as an anode material for lithium ion batteries. ZnS is deposited on ZnO and assembles in nanorod geometry successfully. The nanosized rod structure supports ion diffusion by substantially reducing the ion channel. The close-linking of ZnS and ZnO improves the synergetic effect. ZnS is in the middle of the ZnO core and the external environment, which would greatly relieve the volume change of the ZnO core during the Li + intercalation/de-intercalation processes; therefore, the ZnO@ZnS nanorod is helpful in maintaining excellent cycle stability. The ZnO@ZnS nanorod shows a high discharge capacity of 513.4 mAh g −1 at a current density of 200 mA g −1 after 100 cycles, while a reversible capacity of 385.6 mAh g −1 is achieved at 1000 mA g −1 .

Suggested Citation

  • Haipeng Li & Jiayi Wang & Yan Zhao & Taizhe Tan, 2018. "Synthesis of the ZnO@ZnS Nanorod for Lithium-Ion Batteries," Energies, MDPI, vol. 11(8), pages 1-8, August.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2117-:d:163675
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/8/2117/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/11/8/2117/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhongyue Zou & Jun Xu & Chris Mi & Binggang Cao & Zheng Chen, 2014. "Evaluation of Model Based State of Charge Estimation Methods for Lithium-Ion Batteries," Energies, MDPI, vol. 7(8), pages 1-18, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cornelius Satria Yudha & Soraya Ulfa Muzayanha & Hendri Widiyandari & Ferry Iskandar & Wahyudi Sutopo & Agus Purwanto, 2019. "Synthesis of LiNi 0.85 Co 0.14 Al 0.01 O 2 Cathode Material and its Performance in an NCA/Graphite Full-Battery," Energies, MDPI, vol. 12(10), pages 1-14, May.
    2. Cornelius Satria Yudha & Anjas Prasetya Hutama & Mintarsih Rahmawati & Hendri Widiyandari & Hartoto Nursukatmo & Hanida Nilasary & Haryo Satriya Oktaviano & Agus Purwanto, 2021. "Synthesis and Characterization of ZnO from Thermal Decomposition of Precipitated Zinc Oxalate Dihydrate as an Anode Material of Li-Ion Batteries," Energies, MDPI, vol. 14(18), pages 1-13, September.

    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. Qiao Zhu & Neng Xiong & Ming-Liang Yang & Rui-Sen Huang & Guang-Di Hu, 2017. "State of Charge Estimation for Lithium-Ion Battery Based on Nonlinear Observer: An H ∞ Method," Energies, MDPI, vol. 10(5), pages 1-19, May.
    2. Muhammad Umair Ali & Amad Zafar & Sarvar Hussain Nengroo & Sadam Hussain & Muhammad Junaid Alvi & Hee-Je Kim, 2019. "Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation," Energies, MDPI, vol. 12(3), pages 1-33, January.
    3. Woo-Yong Kim & Pyeong-Yeon Lee & Jonghoon Kim & Kyung-Soo Kim, 2019. "A Nonlinear-Model-Based Observer for a State-of-Charge Estimation of a Lithium-Ion Battery in Electric Vehicles," Energies, MDPI, vol. 12(17), pages 1-20, September.
    4. Bizhong Xia & Guanghao Chen & Jie Zhou & Yadi Yang & Rui Huang & Wei Wang & Yongzhi Lai & Mingwang Wang & Huawen Wang, 2019. "Online Parameter Identification and Joint Estimation of the State of Charge and the State of Health of Lithium-Ion Batteries Considering the Degree of Polarization," Energies, MDPI, vol. 12(15), pages 1-20, July.
    5. Xiong, Rui & Yu, Quanqing & Wang, Le Yi & Lin, Cheng, 2017. "A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter," Applied Energy, Elsevier, vol. 207(C), pages 346-353.
    6. Xiao Wang & Jun Xu & Yunfei Zhao, 2018. "Wavelet Based Denoising for the Estimation of the State of Charge for Lithium-Ion Batteries," Energies, MDPI, vol. 11(5), pages 1-13, May.
    7. Jun Xu & Binggang Cao & Junping Wang, 2016. "A Novel Method to Balance and Reconfigure Series-Connected Battery Strings," Energies, MDPI, vol. 9(10), pages 1-13, September.
    8. Bizhong Xia & Zheng Zhang & Zizhou Lao & Wei Wang & Wei Sun & Yongzhi Lai & Mingwang Wang, 2018. "Strong Tracking of a H-Infinity Filter in Lithium-Ion Battery State of Charge Estimation," Energies, MDPI, vol. 11(6), pages 1-20, June.
    9. Yin Hua & Min Xu & Mian Li & Chengbin Ma & Chen Zhao, 2015. "Estimation of State of Charge for Two Types of Lithium-Ion Batteries by Nonlinear Predictive Filter for Electric Vehicles," Energies, MDPI, vol. 8(5), pages 1-22, April.
    10. Saeed Mian Qaisar, 2020. "Event-Driven Coulomb Counting for Effective Online Approximation of Li-Ion Battery State of Charge," Energies, MDPI, vol. 13(21), pages 1-20, October.
    11. Xu, Jun & Wang, Haitao & Shi, Hu & Mei, Xuesong, 2020. "Multi-scale short circuit resistance estimation method for series connected battery strings," Energy, Elsevier, vol. 202(C).
    12. Yunfeng Jiang & Xin Zhao & Amir Valibeygi & Raymond A. De Callafon, 2016. "Dynamic Prediction of Power Storage and Delivery by Data-Based Fractional Differential Models of a Lithium Iron Phosphate Battery," Energies, MDPI, vol. 9(8), pages 1-17, July.
    13. Qingxia Yang & Jun Xu & Binggang Cao & Xiuqing Li, 2017. "A simplified fractional order impedance model and parameter identification method for lithium-ion batteries," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-13, February.
    14. Ines Baccouche & Sabeur Jemmali & Bilal Manai & Noshin Omar & Najoua Essoukri Ben Amara, 2017. "Improved OCV Model of a Li-Ion NMC Battery for Online SOC Estimation Using the Extended Kalman Filter," Energies, MDPI, vol. 10(6), pages 1-22, May.
    15. Saeed Sepasi & Leon R. Roose & Marc M. Matsuura, 2015. "Extended Kalman Filter with a Fuzzy Method for Accurate Battery Pack State of Charge Estimation," Energies, MDPI, vol. 8(6), pages 1-17, June.
    16. Turksoy, Arzu & Teke, Ahmet & Alkaya, Alkan, 2020. "A comprehensive overview of the dc-dc converter-based battery charge balancing methods in electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    17. Renxin Xiao & Jiangwei Shen & Xiaoyu Li & Wensheng Yan & Erdong Pan & Zheng Chen, 2016. "Comparisons of Modeling and State of Charge Estimation for Lithium-Ion Battery Based on Fractional Order and Integral Order Methods," Energies, MDPI, vol. 9(3), pages 1-15, March.
    18. Angela Amato & Matteo Bilardo & Enrico Fabrizio & Valentina Serra & Filippo Spertino, 2021. "Energy Evaluation of a PV-Based Test Facility for Assessing Future Self-Sufficient Buildings," Energies, MDPI, vol. 14(2), pages 1-23, January.
    19. Teng Liu & Yuan Zou & Dexing Liu & Fengchun Sun, 2015. "Reinforcement Learning–Based Energy Management Strategy for a Hybrid Electric Tracked Vehicle," Energies, MDPI, vol. 8(7), pages 1-18, July.
    20. Jufeng Yang & Bing Xia & Yunlong Shang & Wenxin Huang & Chris Mi, 2016. "Improved Battery Parameter Estimation Method Considering Operating Scenarios for HEV/EV Applications," Energies, MDPI, vol. 10(1), pages 1-20, December.

    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:gam:jeners:v:11:y:2018:i:8:p:2117-:d:163675. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.