Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 538

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Rice husks as a sustainable source of nanostructured silicon for high performance Li-ion battery anodes

Open access
Liu, Nian, Huo, Kaifu, McDowell, Matthew T., Zhao, Jie, Cui, Yi·2013·Scientific Reports

Abstract

The recovery of useful materials from earth-abundant substances is of strategic importance for industrial processes. Despite the fact that Si is the second most abundant element in the Earth's crust, processes to form Si nanomaterials is usually complex, costly and energy-intensive. Here we show that pure Si nanoparticles (SiNPs) can be derived directly from rice husks (RHs), an abundant agricultural byproduct produced at a rate of 1.2 × 10(8) tons/year, with a conversion yield as high as 5% by mass. And owing to their small size (10-40 nm) and porous nature, these recovered SiNPs exhibits high performance as Li-ion battery anodes, with high reversible capacity (2,790 mA h g(-1), seven times greater than graphite anodes) and long cycle life (86% capacity retention over 300 cycles). Using RHs as the raw material source, overall energy-efficient, green, and large scale synthesis of low-cost and functional Si nanomaterials is possible.

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 · 10.1038/srep01919

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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

Cites

Show all 1 references

Cited by

See all 538

Metadata

Authors
Liu, N., Huo, K., McDowell, M. T., Zhao, J., & Cui, Y.
Venue
Scientific Reports
Published
2013-05-29
Volume
3
Issue
1
Pages
1919-1919
ISSN
2045-2322 (ISSN-L)
OpenAlex
W2135410019
Cited by
538
References
1
FWCI
28.76
Type
journal article
Language
en
Open access
gold

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: Rice husks as a sustainable source of nanostructured silicon for high performance Li-ion battery anodes. https://app.cochat.ai/papers/10.1038/srep01919
The paper
Liu, N., Huo, K., McDowell, M. T., Zhao, J., & Cui, Y. (2013). Rice husks as a sustainable source of nanostructured silicon for high performance Li-ion battery anodes. Scientific Reports. https://doi.org/10.1038/srep01919

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.