Advances in Metal-Organic Frameworks for High-Performance Direct Air Capture of CO

Weifeng Chen, Dandan Han, Kaihui Jiang, Xuan Tian, Zhenhua Xie, Yizhu Lei

Abstract readReview

In one paragraph

Review in ACS omega, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Weifeng ChenGuizhou Provincial Key Laboratory of Green Catalysis and Materials for Resource Conversion, Department of Chemistry, School of Chemistry and Materials Engineering, Liupanshui Normal University, Liupanshui City 553004, Guizhou Province, People's Republic of China.ORCID https://orcid.org/0000-0003-3655-3590

Dandan HanCollege of Environmental and Chemical Engineering, Dalian University, Dalian City 116622, Liaoning Province, People's Republic of China.

Kaihui JiangGuizhou Provincial Key Laboratory of Green Catalysis and Materials for Resource Conversion, Department of Chemistry, School of Chemistry and Materials Engineering, Liupanshui Normal University, Liupanshui City 553004, Guizhou Province, People's Republic of China.

Xuan TianGuizhou Provincial Key Laboratory of Green Catalysis and Materials for Resource Conversion, Department of Chemistry, School of Chemistry and Materials Engineering, Liupanshui Normal University, Liupanshui City 553004, Guizhou Province, People's Republic of China.

Zhenhua XieState Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei City 230026, Anhui Province, People's Republic of China.

Yizhu LeiGuizhou Provincial Key Laboratory of Green Catalysis and Materials for Resource Conversion, Department of Chemistry, School of Chemistry and Materials Engineering, Liupanshui Normal University, Liupanshui City 553004, Guizhou Province, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The escalating climate crisis demands gigaton-scale carbon dioxide removal, positioning Direct Air Capture (DAC) as a critical technological frontier. However, its widespread deployment is constrained by a fundamental trilemma involving cost, energy consumption, and sorbent longevity. Overcoming this challenge necessitates transformative material innovation. This review comprehensively examines recent breakthroughs in the molecular engineering of metal-organic frameworks (MOFs), emphasizing their application for the precise recognition of CO

Identifiers

PMID42495362

DOI10.1021/acsomega.6c03606

PMCPMC13393027

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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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.