The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Nanostructured Electrodes for High‐Performance Pseudocapacitors
Abstract
The depletion of traditional energy resources as well as the desire to reduce high CO 2 emissions associated with energy production means that energy storage is now becoming more important than ever. New functional electrode materials are urgently needed for next‐generation energy storage systems, such as supercapacitors or batteries, to meet the ever increasing demand for higher energy and power densities. Advances in nanotechnology are essential to meet those future challenges. It is critical to develop ways of synthesizing new nanomaterials with enhanced properties or combinations of properties to meet future challenges. In this Minireview we discuss several important recent studies in developing nanostructured pseudocapacitor electrodes, and summarize three major parameters that are the most important in determining the performance of electrode materials. A technique to optimize these parameters simultaneously and to achieve both high energy and power densities is also introduced.
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
Ni(OH) 2 Nanoplates Grown on Graphene as Advanced Electrochemical Pseudocapacitor Materials
Wang, H., Casalongue, H. S., Liang, Y., & Dai, H. (2010) · Journal of the American Chemical Society · doi:10.1021/ja102267j · Cited by 2,042
Cited by
Metal oxide-based supercapacitors: progress and prospectives
An, C., Zhang, Y., Guo, H., & Wang, Y. (2019) · Nanoscale Advances · doi:10.1039/c9na00543a · Cited by 789
Metadata
- Authors
- Lu, Q., Chen, J. G., & Xiao, J. Q.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2013-01-10
- Volume
- 52
- Issue
- 7
- Pages
- 1882-1889
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W1977761514
- Cited by
- 579
- References
- 1
- FWCI
- 22.49
- 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: Nanostructured Electrodes for High‐Performance Pseudocapacitors. https://app.cochat.ai/papers/10.1002/anie.201203201
- The paper
- Lu, Q., Chen, J. G., & Xiao, J. Q. (2013). Nanostructured Electrodes for High‐Performance Pseudocapacitors. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201203201
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.