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Novel MnOx@Carbon hybrid nanowires with core/shell architecture as highly reversible anode materials for lithium ion batteries

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  • Pang, Haidong
  • Yang, Zunxian
  • Lv, Jun
  • Yan, Wenhuan
  • Guo, Tailiang

Abstract

Novel MnOx@Carbon hybrid nanowires were successfully synthesized by the combination of a hydrothermal process and a simple PVP (polyvinylpyrrolidone) – solution-soaking method followed by a subsequent carbonization treatment. The nanostructures exhibit the unique feature of having nanocrystalline manganese oxide particle encapsulated inside and an amorphous carbon layer coating the outside. The unique porous characteristics with many meso/micro-pores, and further the highly conductive carbon matrix would lead to the excellent electrochemical performance of the MnOx@Carbon nanowire electrode. The MnOx@Carbon hybrid nanowires exhibit a high initial reversible capacity of 824.4 mAhg−1, a reversible capacity of approximately 541 mAhg−1 after 54 cycles, and excellent cycling stability and rate capability with specific capacity of 298.24 mAhg−1 when cycled at the current density of 1000 mAg−1, which indicates that the composite is a promising anode candidate for Li-ion batteries.

Suggested Citation

  • Pang, Haidong & Yang, Zunxian & Lv, Jun & Yan, Wenhuan & Guo, Tailiang, 2014. "Novel MnOx@Carbon hybrid nanowires with core/shell architecture as highly reversible anode materials for lithium ion batteries," Energy, Elsevier, vol. 69(C), pages 392-398.
  • Handle: RePEc:eee:energy:v:69:y:2014:i:c:p:392-398
    DOI: 10.1016/j.energy.2014.03.029
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    1. Miranda, Á.G. & Chen, T.S. & Hong, C.W., 2013. "Feasibility study of a green energy powered thermoelectric chip based air conditioner for electric vehicles," Energy, Elsevier, vol. 59(C), pages 633-641.
    2. Xiong, Rui & Sun, Fengchun & He, Hongwen & Nguyen, Trong Duy, 2013. "A data-driven adaptive state of charge and power capability joint estimator of lithium-ion polymer battery used in electric vehicles," Energy, Elsevier, vol. 63(C), pages 295-308.
    3. Yang, Zunxian & Meng, Qing & Guo, Zaiping & Yu, Xuebin & Guo, Tailiang & Zeng, Rong, 2013. "Highly reversible lithium storage in uniform Li4Ti5O12/carbon hybrid nanowebs as anode material for lithium-ion batteries," Energy, Elsevier, vol. 55(C), pages 925-932.
    4. Zhang, Xiongwen & Kong, Xin & Li, Guojun & Li, Jun, 2014. "Thermodynamic assessment of active cooling/heating methods for lithium-ion batteries of electric vehicles in extreme conditions," Energy, Elsevier, vol. 64(C), pages 1092-1101.
    5. Sun, Fengchun & Hu, Xiaosong & Zou, Yuan & Li, Siguang, 2011. "Adaptive unscented Kalman filtering for state of charge estimation of a lithium-ion battery for electric vehicles," Energy, Elsevier, vol. 36(5), pages 3531-3540.
    6. He, Hongwen & Zhang, Xiaowei & Xiong, Rui & Xu, Yongli & Guo, Hongqiang, 2012. "Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles," Energy, Elsevier, vol. 39(1), pages 310-318.
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