Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 979

The DOI matches its Crossref record.

Carbon Nanosheet Frameworks Derived from Peat Moss as High Performance Sodium Ion Battery Anodes

Ding, Jia, Wang, Huanlei, Li, Zhi, Kohandehghan, Alireza, Cui, Kai, Xu, Zhanwei, Zahiri, Beniamin, Tan, Xuehai, Lotfabad, Elmira Memarzadeh, Olsen, Brian C., Mitlin, David·2013·ACS Nano

Abstract

We demonstrate that peat moss, a wild plant that covers 3% of the earth's surface, serves as an ideal precursor to create sodium ion battery (NIB) anodes with some of the most attractive electrochemical properties ever reported for carbonaceous materials. By inheriting the unique cellular structure of peat moss leaves, the resultant materials are composed of three-dimensional macroporous interconnected networks of carbon nanosheets (as thin as 60 nm). The peat moss tissue is highly cross-linked, being rich in lignin and hemicellulose, suppressing the nucleation of equilibrium graphite even at 1100 °C. Rather, the carbons form highly ordered pseudographitic arrays with substantially larger intergraphene spacing (0.388 nm) than graphite (c/2 = 0.3354 nm). XRD analysis demonstrates that this allows for significant Na intercalation to occur even below 0.2 V vs Na/Na(+). By also incorporating a mild (300 °C) air activation step, we introduce hierarchical micro- and mesoporosity that tremendously improves the high rate performance through facile electrolyte access and further reduced Na ion diffusion distances. The optimized structures (carbonization at 1100 °C + activation) result in a stable cycling capacity of 298 mAh g(-1) (after 10 cycles, 50 mA g(-1)), with ∼150 mAh g(-1) of charge accumulating between 0.1 and 0.001 V with negligible voltage hysteresis in that region, nearly 100% cycling Coulombic efficiency, and superb cycling retention and high rate capacity (255 mAh g(-1) at the 210th cycle, stable capacity of 203 mAh g(-1) at 500 mA g(-1)).

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 · 10.1021/nn404640c

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

Metadata

Authors
Ding, J., Wang, H., Li, Z., Kohandehghan, A., Cui, K., Xu, Z., Zahiri, B., Tan, X., Lotfabad, E. M., Olsen, B. C., & Mitlin, D.
Venue
ACS Nano
Published
2013-11-12
Volume
7
Issue
12
Pages
11004-11015
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2042940360
Cited by
979
References
0
FWCI
38.34
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

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.