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; 48 of the 48 references it cites were found in a registry or an index.

A molecular sieve with ultrafast adsorption kinetics for propylene separation

Cui, Jiyu, Zhang, Zhaoqiang, Yang, Lifeng, Hu, Jianbo, Jin, Anye, Yang, Zhenglu, Zhao, Yue, Meng, Biao, Zhou, Yu, Wang, Jun, Su, Yun, Wang, Jun, Cui, Xili, Xing, Huabin·2024·Science

Abstract

The design of molecular sieves is vital for gas separation, but it suffers from a long-standing issue of slow adsorption kinetics due to the intrinsic contradiction between molecular sieving and diffusion within restricted nanopores. We report a molecular sieve ZU-609 with local sieving channels that feature molecular sieving gates and rapid diffusion channels. The precise cross-sectional cutoff of molecular sieving gates enables the exclusion of propane from propylene. The coexisting large channels constituted by sulfonic anions and helically arranged metal-organic architectures allow the fast adsorption kinetics of propylene, and the measured propylene diffusion coefficient in ZU-609 is one to two orders of magnitude higher than previous molecular sieves. Propylene with 99.9% purity is obtained through breakthrough experiments with a productivity of 32.2 L kg −1 .

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 · 10.1126/science.abn8418

Cites

48 of 48 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 48 references

Metadata

Authors
Cui, J., Zhang, Z., Yang, L., Hu, J., Jin, A., Yang, Z., Zhao, Y., Meng, B., Zhou, Y., Wang, J., Su, Y., Wang, J., Cui, X., & Xing, H.
Venue
Science
Published
2024-01-12
Volume
383
Issue
6679
Pages
179-183
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W4389767254
Cited by
308
References
48
FWCI
22.81
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: A molecular sieve with ultrafast adsorption kinetics for propylene separation. https://app.cochat.ai/papers/10.1126/science.abn8418
The paper
Cui, J., Zhang, Z., Yang, L., Hu, J., Jin, A., Yang, Z., Zhao, Y., Meng, B., Zhou, Y., Wang, J., Su, Y., Wang, J., Cui, X., & Xing, H. (2024). A molecular sieve with ultrafast adsorption kinetics for propylene separation. Science. https://doi.org/10.1126/science.abn8418

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.