Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 598

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

Highly porous and stable metal–organic frameworks for uranium extraction

Carboni, Michaël, Abney, Carter W., Liu, Shubin, Lin, Wenbin·2013·Chemical Science

Abstract

Three metal–organic frameworks (MOFs) of the UiO-68 network topology were prepared using the amino-TPDC or TPDC bridging ligands containing orthogonal phosphorylurea groups (TPDC is p,p′-terphenyldicarboxylic acid), and investigated for sorption of uranium from water and artificial seawater. The stable and porous phosphorylurea-derived MOFs were shown to be highly efficient in sorbing uranyl ions, with saturation sorption capacities as high as 217 mg U g−1 which is equivalent to binding one uranyl ion for every two sorbent groups. Coordination modes between uranyl groups and simplified phosphorylurea motifs were investigated by DFT calculations, revealing a thermodynamically favorable monodentate binding of two phosphorylurea ligands to one uranyl ion. Convergent orientation of phosphorylurea groups at appropriate distances inside the MOF cavities is believed to facilitate their cooperative binding with uranyl ions. This work represents the first application of MOFs as novel sorbents to extract actinide elements from aqueous media.

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/c3sc50230a

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 598

Metadata

Authors
Carboni, M., Abney, C. W., Liu, S., & Lin, W.
Venue
Chemical Science
Published
2013
Volume
4
Issue
6
Pages
2396
ISSN
  • 2041-6520 (ISSN-L)
  • 2041-6539
OpenAlex
W2125623338
Cited by
598
References
5
FWCI
18.07
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: Highly porous and stable metal–organic frameworks for uranium extraction. https://app.cochat.ai/papers/10.1039/c3sc50230a
The paper
Carboni, M., Abney, C. W., Liu, S., & Lin, W. (2013). Highly porous and stable metal–organic frameworks for uranium extraction. Chemical Science. https://doi.org/10.1039/c3sc50230a

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.