Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,942

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Pseudocapacitance: From Fundamental Understanding to High Power Energy Storage Materials

Open access
Fleischmann, Simon, Mitchell, James B., Wang, Ruocun, Zhan, Cheng, Jiang, De-en, Presser, Volker, Augustyn, Veronica·2020·Chemical Reviews

Abstract

There is an urgent global need for electrochemical energy storage that includes materials that can provide simultaneous high power and high energy density. One strategy to achieve this goal is with pseudocapacitive materials that take advantage of reversible surface or near-surface Faradaic reactions to store charge. This allows them to surpass the capacity limitations of electrical double-layer capacitors and the mass transfer limitations of batteries. The past decade has seen tremendous growth in the understanding of pseudocapacitance as well as materials that exhibit this phenomenon. The purpose of this Review is to examine the fundamental development of the concept of pseudocapacitance and how it came to prominence in electrochemical energy storage as well as to describe new classes of materials whose electrochemical energy storage behavior can be described as pseudocapacitive.

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/acs.chemrev.0c00170

Cites

4 of 4 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 4 references

Cited by

See all 1,942

Metadata

Authors
Fleischmann, S., Mitchell, J. B., Wang, R., Zhan, C., Jiang, D.-E., Presser, V., & Augustyn, V.
Venue
Chemical Reviews
Published
2020-06-28
Volume
120
Issue
14
Pages
6738-6782
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W3037830571
Cited by
1,942
References
4
FWCI
9.32
Type
journal article
Language
en
Open access
green

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: Pseudocapacitance: From Fundamental Understanding to High Power Energy Storage Materials. https://app.cochat.ai/papers/10.1021/acs.chemrev.0c00170
The paper
Fleischmann, S., Mitchell, J. B., Wang, R., Zhan, C., Jiang, D.-E., Presser, V., & Augustyn, V. (2020). Pseudocapacitance: From Fundamental Understanding to High Power Energy Storage Materials. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.0c00170

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.