Evidence map›Paper›PMID 35424941›Full record

ReviewRSC advances2022

Strategies for the application of metal-organic frameworks in catalytic reactions.

Fei Gao, Runhan Yan, Yao Shu, Qingbin Cao, Li Zhang

Open access · goldAbstract readReview
In one paragraph

Review in RSC advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 47 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Solid-stateMagnetic resonance (Gottingen, Germany) · 2024
    Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 1 country.

Fei GaoSchool of Physics and Materials, Nanchang University Nanchang 330031 China gaofei@ncu.edu.cn gaofeiring@163.com.ORCID https://orcid.org/0000-0003-1474-9592
Runhan YanSchool of Physics and Materials, Nanchang University Nanchang 330031 China gaofei@ncu.edu.cn gaofeiring@163.com.
Yao ShuInstitute of New Materials, Guangdong Academy of Science Guangzhou 510651 China.
Qingbin CaoThe State Key Laboratory of Chemical Engineering, Tsinghua University Beijing 100084 China.
Li ZhangInstitute of Applied Chemistry, Jiangxi Academy of Science Nanchang 330096 China.
Nanchang University · CNInstitute of New Materials · CNJiangxi Academy of Sciences · CNState Key Laboratory of Chemical Engineering · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efficient catalysts play crucial roles in various organic reactions and polymerization. Metal-organic frameworks (MOFs) have the merits of ultrahigh porosity, large surface area, dispersed polymetallic sites and modifiable linkers, which make them promising candidates for catalyzation. This review primarily summarizes the recent research progress on diverse strategies for tailoring MOFs that are endowed with excellent catalytic behavior. These strategies include utilizing MOFs as nanosized reaction channels, metal nodes decorated as catalytic active sites and the modification of ligands or linkers. All these make them highly attractive to various applications, especially in catalyzing organic reactions or polymerizations and they have proven to be effective catalysts for a wide variety of reactions. MOFs are still an evolving field with tremendous prospects; therefore, through the research and development of more modification and regulation strategies, MOFs will realize their wider practical application in the future.

Identifiers

PMID35424941
PMCPMC8968187
OpenAlexW4223909726

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.