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Record W4407636712 · doi:10.1038/s41699-025-00534-8

Recent advances in retention and permeation of CO2 gas using MXene based membranes

2025· article· en· W4407636712 on OpenAlex
Yasseen S. Ibrahim, Moustafa M. Zagho, Amr ElAlfy, Alamgir Karim, Ahmed A. Elzatahry

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenpj 2D Materials and Applications · 2025
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsUniversity of Waterloo
FundersUniversity of South AlabamaAmerican Chemical SocietyWelch Foundation
KeywordsPermeationMembraneChemical engineeringMaterials scienceChemistryEngineering

Abstract

fetched live from OpenAlex

Abstract Human-induced emissions demand effective CO 2 separation technologies. Energy-efficient membranes, like MXenes with 2D structures, enhance selective gas permeation. This review highlights advancements in improving CO 2 retention of MXene membranes, including self-standing, ion-intercalation, and modification techniques. It also examines MXenes in mixed matrix membranes to optimize CO 2 permeation. Strategies addressing the selectivity-permeability trade-off, humidified MXenes, and hybrid fillers are discussed, along with challenges and future directions in MXene-based CO 2 separation technologies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.259
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it