Evidence map›Paper›PMID 40873943›Full record

ArticleACS applied engineering materials2025

Mixed Matrix Membranes Composed of Graphene-Based Derivatives as Additives in PVAm for CO

James Baker, Cristina Perinu, Maria Psarrou, Sigmund Mordal Lucasen, Victor Kusuma, Patrick F Muldoon, Akrivi Asimakopoulou, David Hopkinson, Solon P Economopoulos

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ACS applied engineering materials, 2025. 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

9 authors.

James BakerU.S. Department of Energy, National Energy Technology Laboratory, 626 Cochrans Mill Rd, Pittsburgh, Pennsylvania 15236, United States.
Cristina PerinuDepartment of Chemistry, Norwegian University of Science and Technology, 7491 Trondheim, Norway.
Maria PsarrouDepartment of Chemistry, Norwegian University of Science and Technology, 7491 Trondheim, Norway.
Sigmund Mordal LucasenDepartment of Chemistry, Norwegian University of Science and Technology, 7491 Trondheim, Norway.
Victor KusumaU.S. Department of Energy, National Energy Technology Laboratory, 626 Cochrans Mill Rd, Pittsburgh, Pennsylvania 15236, United States.ORCID https://orcid.org/0000-0002-7881-4536
Patrick F MuldoonU.S. Department of Energy, National Energy Technology Laboratory, 626 Cochrans Mill Rd, Pittsburgh, Pennsylvania 15236, United States.ORCID https://orcid.org/0000-0001-5241-1694
Akrivi AsimakopoulouAdvanced Renewable Technologies & Environmental Materials in Integrated Systems, ARTEMIS, Chemical Process and Energy Resources Institute CPERI, Centre for Research and Technology Hellas CERTH, Thermi, 57001 Thessaloniki, Greece.
David HopkinsonU.S. Department of Energy, National Energy Technology Laboratory, 626 Cochrans Mill Rd, Pittsburgh, Pennsylvania 15236, United States.
Solon P EconomopoulosDepartment of Chemistry, Norwegian University of Science and Technology, 7491 Trondheim, Norway.ORCID https://orcid.org/0000-0002-2609-4602

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Graphene oxide (GO) mixed matrix membranes (MMMs) that employ facilitated transport of carbon dioxide were prepared and tested for use in postcombustion carbon capture. Two graphene hybrids were synthesized using exfoliated graphene (G) and GO as a basis and were then appended with triethylene glycol (TEG) and

Indexed as

carbon capturegraphenegraphene functionalizationgraphene oxidemixed matrix membranes

Identifiers

PMID40873943
PMCPMC12379166

What OpenQuestion holds

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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.