Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 556

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Calculating Geometric Surface Areas as a Characterization Tool for Metal−Organic Frameworks

Düren, Tina, Millange, Franck, Férey, Gérard, Walton, Krista S., Snurr, Randall Q.·2007·The Journal of Physical Chemistry C

Abstract

Metal−organic frameworks (MOFs) synthesized in a building-block approach from organic linkers and metal corner units offer the opportunity to design materials with high surface areas for adsorption applications by assembling the appropriate building blocks. In this paper, we show that the surface area calculated in a geometric fashion from the crystal structure is a useful tool for characterizing MOFs. We argue that the accessible surface area rather than the widely used Connolly surface area is the appropriate surface area to characterize crystalline solids for adsorption applications. The accessible surface area calculated with a probe diameter corresponding to the adsorbate of interest provides a simple way to screen and compare adsorbents. We investigate the effects of the probe molecule diameter on the accessible surface area and discuss the implications for increasing the surface area of metal−organic frameworks by the use of catenated structures. We also demonstrate that the accessible surface area provides a useful tool for judging the quality of a synthesized sample. Experimental surface areas can be adversely affected by incomplete solvent removal during activation, crystal collapse, or interpenetration. The easily calculated accessible surface area provides a benchmark for the theoretical upper limit for a perfect crystal.

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/jp074723h

Cites

1 of 1 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

Cited by

See all 556

Metadata

Authors
Düren, T., Millange, F., Férey, G., Walton, K. S., & Snurr, R. Q.
Venue
The Journal of Physical Chemistry C
Published
2007-10-01
Volume
111
Issue
42
Pages
15350-15356
ISSN
  • 1932-7447 (ISSN-L)
  • 1932-7455
OpenAlex
W2002542825
Cited by
556
References
1
FWCI
17.11
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

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.