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Record W1914015691 · doi:10.1002/ppap.201500040

Nanofluids Containing MWCNTs Coated with Nitrogen-Rich Plasma Polymer Films for CO<sub>2</sub>Absorption in Aqueous Medium

2015· article· en· W1914015691 on OpenAlex

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

VenuePlasma Processes and Polymers · 2015
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceChemical engineeringAqueous solutionPolymerCarbon nanotubeAbsorption (acoustics)NitrogenLayer (electronics)NanofluidNanotechnologyOrganic chemistryChemistryComposite materialNanoparticle

Abstract

fetched live from OpenAlex

Amine-functionalized multi-walled carbon nanotubes (MWCNTs) dispersed in water are investigated as CO2 absorbents. MWCNTs grown by chemical vapor deposition on stainless steel meshes form open forests that can be coated via a RF capacitively coupled glow discharge. When treating the MWCNTs in an atmosphere containing either pure ammonia or mixtures of ammonia and ethylene for 5 min, grafting of nitrogen functional groups or deposition of a nitrogen-rich plasma polymer layer occurs. In particular, for a 1:1 mixture, a 10 nm thick plasma polymer layer coats the MWCNTs. This layer contains about 19 N at%, and 12% of these nitrogen atoms are nucleophilic sites (such as amines) that may react with CO2. These functional groups not only enhance the absorption of CO2, but also increase the hydrophilic character of the MWCNTs, allowing them to stay suspended in water for at least three months at room temperature. The CO2 absorption capacity of this nanofluid is 36% higher than that of water, with a MWCNT concentration of about 40 mg L−1.

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 categoriesMeta-epidemiology (narrow)
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 score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.214
Teacher spread0.200 · 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