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Record W3215467629 · doi:10.3390/polym13234156

A Simple Approach to Control the Physical and Chemical Features of Custom-Synthesized N-Doped Carbon Nanotubes and the Extent of Their Network Formation in Polymers: The Importance of Catalyst to Substrate Ratio

2021· article· en· W3215467629 on OpenAlexaff
Elnaz Erfanian, Milad Kamkar, Shital Patangrao Pawar, Yalda Zamani Keteklahijani, Mohammad Arjmand, Uttandaraman Sundararaj

Bibliographic record

VenuePolymers · 2021
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsCarbon nanotubeMaterials scienceRaman spectroscopyCatalysisX-ray photoelectron spectroscopyNanocompositeChemical vapor depositionChemical engineeringSubstrate (aquarium)NanotubeNanotechnologyComposite materialOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

This study intends to reveal the significance of the catalyst to substrate ratio (C/S) on the structural and electrical features of the carbon nanotubes and their polymeric nanocomposites. Here, nitrogen-doped carbon nanotube (N-MWNT) was synthesized via a chemical vapor deposition (CVD) method using three ratios (by weight) of iron (Fe) catalyst to aluminum oxide (Al2O3) substrate, i.e.,1/9, 1/4, and 2/3, by changing the Fe concentration, i.e., 10, 20, and 40 wt.% Fe. Therefore, the synthesized N-MWNT are labelled as (N-MWNTs)10, (N-MWNTs)20, and (N-MWNTs)40. TEM, XPS, Raman spectroscopy, and TGA characterizations revealed that C/S ratio has a significant impact on the physical and chemical properties of the nanotubes. For instance, by increasing the Fe catalyst from 10 to 40 wt.%, carbon purity increased from 60 to 90 wt.% and the length of the nanotubes increased from 1.2 to 2.6 µm. Interestingly, regarding nanotube morphology, at the highest C/S ratio, the N-MWNTs displayed an open-channel structure, while at the lowest catalyst concentration the nanotubes featured a bamboo-like structure. Afterwards, the network characteristics of the N-MWNTs in a polyvinylidene fluoride (PVDF) matrix were studied using imaging techniques, AC electrical conductivity, and linear and nonlinear rheological measurements. The nanocomposites were prepared via a melt-mixing method at various loadings of the synthesized N-MWNTs. The rheological results confirmed that (N-MWNTs)10, at 0.5–2.0 wt.%, did not form any substantial network through the PVDF matrix, thereby exhibiting an electrically insulative behavior, even at a higher concentration of 3.0 wt.%. Although the optical microscopy, TEM, and rheological results confirmed that both (N-MWNTs)20 and (N-MWNTs)40 established a continuous 3D network within the PVDF matrix, (N-MWNTs)40/PVDF nanocomposites exhibited approximately one order of magnitude higher electrical conductivity. The higher electrical conductivity of (N-MWNTs)40/PVDF nanocomposites is attributed to the intrinsic chemical features of (N-MWNTs)40, such as nitrogen content and nitrogen bonding types.

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.

How this classification was reachedexpand

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)0.001
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 score0.004
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2021
Admission routes1
Has abstractyes

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