Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 496

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Porous carbon-based materials for hydrogen storage: advancement and challenges

Xia, Yongde, Yang, Zhuxian, Zhu, Yanqiu·2013·Journal of Materials Chemistry A

Abstract

The development of highly efficient hydrogen storage materials is one of the main challenges that must be tackled in a widely expected hydrogen economy. Physisorption in porous materials with high surface areas and chemisorption in hydrides are the two main options for solid state hydrogen storage, and both options possess their inherent advantages and drawbacks. In this work, recent progress towards porous carbon-based materials for hydrogen storage is analyzed and reviewed. The hydrogen storage performance of plain porous carbons, metal-supported porous carbons and porous carbons confined hydrides is summarized. Some strategies for effectively controlling the hydrogen storage capacity and tuning the hydrogen adsorption enthalpy for porous carbon materials via appropriate manipulation of surface area, pore volume and pore size are discussed in detail. The new development of porous carbon-based materials for hydrogen storage is particularly emphasized.

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 · 10.1039/c3ta10583k

Cites

5 of 5 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 5 references

Cited by

See all 496

Metadata

Authors
Xia, Y., Yang, Z., & Zhu, Y.
Venue
Journal of Materials Chemistry A
Published
2013
Volume
1
Issue
33
Pages
9365
ISSN
  • 2050-7488 (ISSN-L)
  • 2050-7496
OpenAlex
W2049648774
Cited by
496
References
5
FWCI
11.54
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: Porous carbon-based materials for hydrogen storage: advancement and challenges. https://app.cochat.ai/papers/10.1039/c3ta10583k
The paper
Xia, Y., Yang, Z., & Zhu, Y. (2013). Porous carbon-based materials for hydrogen storage: advancement and challenges. Journal of Materials Chemistry A. https://doi.org/10.1039/c3ta10583k

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.