Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 308

The DOI matches its Crossref record.

Sorbent Cost and Performance in CO2 Capture Systems

Abanades, Juan C., Rubin, Edward S., Anthony, Edward J.·2004·Industrial & Engineering Chemistry Research

Abstract

Power plants are prime candidates to apply CO 2 capture for final storage as a mitigation option for climate change. Many CO 2 capture concepts make use of a sorption−desorption cycle to separate CO 2 from flue gas or O 2 from air. These include commercial absorption processes, as well as processes using new sorbent formulations, adsorption, and high-temperature chemical looping cycles for CO 2 and O 2 . All of these new processes must confront the large scale of carbon flows typical in a power plant. In this work, a common mass balance for all of these processes is used to define a parameter that highlights the minimum sorbent performance required to keep sorbent makeup costs at an acceptable level. A well-established reference system for which reliable commercial data exist (absorption with monoethanolamine, MEA) is used as a technoeconomic baseline to show that some of the sorbents being proposed in the open literature might need to be tested under laboratory conditions for tens of thousands of sorption−desorption cycles before they can be further considered as viable options for CO 2 capture from power plants.

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/ie049962v

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

See all 308

Metadata

Authors
Abanades, J. C., Rubin, E. S., & Anthony, E. J.
Venue
Industrial & Engineering Chemistry Research
Published
2004-05-26
Volume
43
Issue
13
Pages
3462-3466
ISSN
  • 0888-5885 (ISSN-L)
  • 1520-5045
OpenAlex
W2161133920
Cited by
308
References
0
FWCI
29.41
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: Sorbent Cost and Performance in CO2 Capture Systems. https://app.cochat.ai/papers/10.1021/ie049962v
The paper
Abanades, J. C., Rubin, E. S., & Anthony, E. J. (2004). Sorbent Cost and Performance in CO2 Capture Systems. Industrial & Engineering Chemistry Research. https://doi.org/10.1021/ie049962v

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.