Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 439

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Mixed Metal–Organic Framework with Multiple Binding Sites for Efficient C2H2/CO2Separation

Open access
Gao, Junkuo, Qian, Xuefeng, Lin, Rui‐Biao, Krishna, Rajamani, Wu, Hui, Zhou, Wei, Chen, Banglin·2020·Angewandte Chemie International Edition

Abstract

The separation of C 2 H 2/CO 2 is particularly challenging owing to their similarities in physical properties and molecular sizes. Reported here is a mixed metal–organic framework (M′MOF), [Fe(pyz)Ni(CN)4] (FeNi‐M′MOF, pyz=pyrazine), with multiple functional sites and compact one‐dimensional channels of about 4.0 Å for C 2 H 2/CO 2 separation. This MOF shows not only a remarkable volumetric C 2 H 2 uptake of 133 cm 3 cm−3, but also an excellent C 2 H 2/CO 2 selectivity of 24 under ambient conditions, resulting in the second highest C 2 H 2‐capture amount of 4.54 mol L−1, thus outperforming most previous benchmark materials. The separation performance of this material is driven by π–π stacking and multiple intermolecular interactions between C 2 H 2 molecules and the binding sites of FeNi‐M′MOF. This material can be facilely synthesized at room temperature and is water stable, highlighting FeNi‐M′MOF as a promising material for C 2 H 2/CO 2 separation.

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 · 10.1002/anie.202000323

Cites

2 of 2 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 2 references

Cited by

See all 439

Metadata

Authors
Gao, J., Qian, X., Lin, R., Krishna, R., Wu, H., Zhou, W., & Chen, B.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2020-01-30
Volume
59
Issue
11
Pages
4396-4400
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2998819515
Cited by
439
References
2
FWCI
44.92
Type
journal article
Language
en
Open access
green

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: Mixed Metal–Organic Framework with Multiple Binding Sites for Efficient C2H2/CO2Separation. https://app.cochat.ai/papers/10.1002/anie.202000323
The paper
Gao, J., Qian, X., Lin, R., Krishna, R., Wu, H., Zhou, W., & Chen, B. (2020). Mixed Metal–Organic Framework with Multiple Binding Sites for Efficient C2H2/CO2Separation. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.202000323

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.