The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Graphene–Nanotube–Iron Hierarchical Nanostructure as Lithium Ion Battery Anode
Abstract
In this study, we report a novel route via microwave irradiation to synthesize a bio-inspired hierarchical graphene--nanotube--iron three-dimensional nanostructure as an anode material in lithium-ion batteries. The nanostructure comprises vertically aligned carbon nanotubes grown directly on graphene sheets along with shorter branches of carbon nanotubes stemming out from both the graphene sheets and the vertically aligned carbon nanotubes. This bio-inspired hierarchical structure provides a three-dimensional conductive network for efficient charge-transfer and prevents the agglomeration and restacking of the graphene sheets enabling Li-ions to have greater access to the electrode material. In addition, functional iron-oxide nanoparticles decorated within the three-dimensional hierarchical structure provides outstanding lithium storage characteristics, resulting in very high specific capacities. The anode material delivers a reversible capacity of ~1024 mA · h · g(-1) even after prolonged cycling along with a Coulombic efficiency in excess of 99%, which reflects the ability of the hierarchical network to prevent agglomeration of the iron-oxide nanoparticles.
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.
Integrity signals
Registry
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.
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
Thermal properties of graphene and nanostructured carbon materials
Balandin, A. A. (2011) · Nature Materials · doi:10.1038/nmat3064 · Cited by 6,244
Cited by
Synthesis and Modification of Carbon Nanomaterials utilizing Microwave Heating
Schwenke, A. M., Hoeppener, S., & Schubert, U. S. (2015) · Advanced Materials · doi:10.1002/adma.201500472 · Cited by 366
Li3V2(PO4)3 cathode materials for lithium-ion batteries: A review
Rui, X., Yan, Q., Skyllas-Kazacos, M., & Lim, T. M. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2014.01.126 · Cited by 342
Flexible electromagnetic wave absorbing composite based on 3D rGO-CNT-Fe3O4 ternary films
Li, J., Xie, Y., Lu, W., & Chou, T.-W. (2018) · Carbon · doi:10.1016/j.carbon.2017.11.094 · Cited by 267
Metadata
- Authors
- Lee, S.-H., Sridhar, V., Jung, J.-H., Karthikeyan, K., Lee, Y.-S., Mukherjee, R., Koratkar, N., & Oh, I.-K.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-04-08
- Volume
- 7
- Issue
- 5
- Pages
- 4242-4251
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2026366935
- Cited by
- 196
- References
- 1
- FWCI
- 16.58
- 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.