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Porous Doped Silicon Nanowires for Lithium Ion Battery Anode with Long Cycle Life

Ge, Mingyuan, Rong, Jiepeng, Fang, Xin, Zhou, Chongwu·2012·Nano Letters

Abstract

Porous silicon nanowires have been well studied for various applications; however, there are only very limited reports on porous silicon nanowires used for energy storage. Here, we report both experimental and theoretical studies of porous doped silicon nanowires synthesized by direct etching of boron-doped silicon wafers. When using alginate as a binder, porous silicon nanowires exhibited superior electrochemical performance and long cycle life as anode material in a lithium ion battery. Even after 250 cycles, the capacity remains stable above 2000, 1600, and 1100 mAh/g at current rates of 2, 4, and 18 A/g, respectively, demonstrating high structure stability due to the high porosity and electron conductivity of the porous silicon nanowires. A mathematic model coupling the lithium ion diffusion and the strain induced by lithium intercalation was employed to study the effect of porosity and pore size on the structure stability. Simulation shows silicon with high porosity and large pore size help to stabilize the structure during charge/discharge cycles.

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Metadata

Authors
Ge, M., Rong, J., Fang, X., & Zhou, C.
Venue
Nano Letters
Published
2012-04-11
Volume
12
Issue
5
Pages
2318-2323
ISSN
  • 1530-6984 (ISSN-L)
  • 1530-6992
OpenAlex
W2142904252
Cited by
856
References
0
FWCI
57.58
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Porous Doped Silicon Nanowires for Lithium Ion Battery Anode with Long Cycle Life. https://app.cochat.ai/papers/10.1021/nl300206e
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Ge, M., Rong, J., Fang, X., & Zhou, C. (2012). Porous Doped Silicon Nanowires for Lithium Ion Battery Anode with Long Cycle Life. Nano Letters. https://doi.org/10.1021/nl300206e

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.