Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 233

The DOI matches its Crossref record.

Ultrafine Nickel‐Nanoparticle‐Enabled SiO2 Hierarchical Hollow Spheres for High‐Performance Lithium Storage

Tang, Chunjuan, Liu, Yuning, Xu, Chang, Zhu, Jiexin, Wei, Xiujuan, Zhou, Liang, He, Liang, Yang, Wei, Mai, Liqiang·2018·Advanced Functional Materials

Abstract

The high theoretical capacity and natural abundance of SiO 2 make it a promising high‐capacity anode material for lithium‐ion batteries. However, its widespread application is significantly hampered by the intrinsic poor electronic conductivity and drastic volume variation. Herein, a unique hollow structured Ni/SiO 2 nanocomposite constructed by ultrafine Ni nanoparticle (≈3 nm) functionalized SiO 2 nanosheets is designed. The Ni nanoparticles boost not only the electronic conductivity but also the electrochemical activity of SiO 2 effectively. Meanwhile, the hollow cavity provides sufficient free space to accommodate the volume change of SiO 2 during repeated lithiation/delithiation; the nanosheet building blocks reduce the diffusion lengths of lithium ions. Due to the synergistic effect between Ni and SiO 2, the Ni/SiO 2 composite delivers a high reversible capacity of 676 mA h g−1 at 0.1 A g−1. At a high current density of 10 A g−1, a capacity of 337 mA h g−1 can be retained after 1000 cycles.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/adfm.201704561

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 233

Metadata

Authors
Tang, C., Liu, Y., Xu, C., Zhu, J., Wei, X., Zhou, L., He, L., Yang, W., & Mai, L.
Venue
Advanced Functional Materials
Publisher
Wiley
Published
2017-11-23
Volume
28
Issue
3
ISSN
  • 1616-301X (ISSN-L)
  • 1616-3028
OpenAlex
W2770980777
Cited by
233
References
0
FWCI
11.86
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Ultrafine Nickel‐Nanoparticle‐Enabled SiO2 Hierarchical Hollow Spheres for High‐Performance Lithium Storage. https://app.cochat.ai/papers/10.1002/adfm.201704561
The paper
Tang, C., Liu, Y., Xu, C., Zhu, J., Wei, X., Zhou, L., He, L., Yang, W., & Mai, L. (2018). Ultrafine Nickel‐Nanoparticle‐Enabled SiO2 Hierarchical Hollow Spheres for High‐Performance Lithium Storage. Advanced Functional Materials. https://doi.org/10.1002/adfm.201704561

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.