Evidence map›Paper›PMID 37565191›Full record

ReviewNational science review2023

Cavity-controlled methanol conversion over zeolite catalysts.

Wenna Zhang, Shanfan Lin, Yingxu Wei, Peng Tian, Mao Ye, Zhongmin Liu

Open access · goldAbstract readReview
In one paragraph

Review in National science review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
5.7field-weighted citation impact, top 3% 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

4 citing papers in PubMed, 57 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Green carbon science for carbon neutrality.National science review · 2023
    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

6 authors at 3 institutions in 1 country.

Wenna ZhangNational Engineering Research Center of Lower-Carbon Catalysis Technology, Dalian National Laboratory for Clean Energy, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
Shanfan LinNational Engineering Research Center of Lower-Carbon Catalysis Technology, Dalian National Laboratory for Clean Energy, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
Yingxu WeiNational Engineering Research Center of Lower-Carbon Catalysis Technology, Dalian National Laboratory for Clean Energy, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
Peng TianNational Engineering Research Center of Lower-Carbon Catalysis Technology, Dalian National Laboratory for Clean Energy, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
Mao YeNational Engineering Research Center of Lower-Carbon Catalysis Technology, Dalian National Laboratory for Clean Energy, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
Zhongmin LiuNational Engineering Research Center of Lower-Carbon Catalysis Technology, Dalian National Laboratory for Clean Energy, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
Collaborative Innovation Center of Chemistry for Energy Materials · CNDalian Institute of Chemical Physics · CNDalian National Laboratory for Clean Energy · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The successful development and application in industry of methanol-to-olefins (MTO) process brought about an innovative and efficient route for olefin production via non-petrochemical resources and also attracted attention of C1 chemistry and zeolite catalysis. Molecular sieve catalysts with diversified microenvironments embedding unique channel/cavity structure and acid properties, exhibit demonstrable features and advantages in the shape-selective catalysis of MTO. Especially, shape-selective catalysis over 8-MR and cavity-type zeolites with acidic supercage environment and narrow pore opening manifested special host-guest interaction between the zeolite catalyst and guest reactants, intermediates and products. This caused great differences in product distribution, catalyst deactivation and molecular diffusion, revealing the cavity-controlled methanol conversion over 8-MR and cavity-type zeolite catalyst. Furthermore, the dynamic and complicated cross-talk behaviors of catalyst material (coke)-reaction-diffusion over these types of zeolites determines the catalytic performance of the methanol conversion. In this review, we shed light on the cavity-controlled principle in the MTO reaction including cavity-controlled active intermediates formation, cavity-controlled reaction routes with the involvement of these intermediates in the complex reaction network, cavity-controlled catalyst deactivation and cavity-controlled diffusion. All these were exhibited by the MTO reaction performances and product selectivity over 8-MR and cavity-type zeolite catalysts. Advanced strategies inspired by the cavity-controlled principle were developed, providing great promise for the optimization and precise control of MTO process.

Indexed as

cavity-controlled principledeactivation and diffusionmethanol-to-olefinsreaction intermediates and routesshape-selective catalysis

Identifiers

PMID37565191
PMCPMC10411685
OpenAlexW4372202716

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.