The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
CO2 and CH4 Separation by Adsorption Using Cu-BTC Metal−Organic Framework
Abstract
Molecular simulations have shown that the metal−organic framework Cu-BTC (Cu 3 (BTC) 2 ) is an interesting candidate for the separation of CO 2 by adsorption. In this work, the first experimental binary and ternary adsorption data of CO 2, CH 4, and CO on the Cu-BTC are reported. These data are analyzed and compared with coadsorption models that are built from pure component isotherm data. Cu-BTC has a CO 2 /CH 4 selectivity of ∼8 and a high delta loading (=difference between adsorption capacity under conditions of adsorption and desorption) and therefore appears to be a good compromise between zeolites, with high selectivity for CO 2, but low delta loadings, and activated carbons, with high delta loadings, but low selectivity, for pressure swing adsorption applications.
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
Sing, K. S. W. (1985) · Pure and Applied Chemistry · doi:10.1351/pac198557040603 · Cited by 24,485
Span, R., & Wagner, W. (1996) · Journal of Physical and Chemical Reference Data · doi:10.1063/1.555991 · Cited by 5,049
Millward, A. R., & Yaghi, O. M. (2005) · Journal of the American Chemical Society · doi:10.1021/ja0570032 · Cited by 2,876
Cited by
Metal–Organic Frameworks for Separations
Li, J.-R., Sculley, J., & Zhou, H.-C. (2012) · Chemical Reviews · doi:10.1021/cr200190s · Cited by 6,323
García, E. J., Pérez-Pellitero, J., Pirngruber, G. D., Jallut, C., Palomino, M., Rey, F., & Valencia, S. (2014) · Industrial & Engineering Chemistry Research · doi:10.1021/ie500207s · Cited by 63
Self-citation
Metadata
- Authors
- Hamon, L., Jolimaître, E., & Pirngruber, G. D.
- Venue
- Industrial & Engineering Chemistry Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-07-20
- Volume
- 49
- Issue
- 16
- Pages
- 7497-7503
- ISSN
- 0888-5885 (ISSN-L)
- 1520-5045
- OpenAlex
- W1967538420
- Cited by
- 252
- References
- 3
- FWCI
- 13.59
- 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: CO2 and CH4 Separation by Adsorption Using Cu-BTC Metal−Organic Framework. https://app.cochat.ai/papers/10.1021/ie902008g
- The paper
- Hamon, L., Jolimaître, E., & Pirngruber, G. D. (2010). CO2 and CH4 Separation by Adsorption Using Cu-BTC Metal−Organic Framework. Industrial & Engineering Chemistry Research. https://doi.org/10.1021/ie902008g
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.
