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Record W2889196602 · doi:10.1002/app.46757

Functionalization of multiwalled carbon nanotubes by amidation and Michael addition reactions and the effect of the functional chains on the properties of waterborne polyurethane composites

2018· article· en· W2889196602 on OpenAlexaff
Shasha Li, Caiying Hou, Guozhang Ma, Hezhi Wang, Jianbin Wu, Xiaogang Hao, Hui Zhang

Bibliographic record

VenueJournal of Applied Polymer Science · 2018
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials sciencePolyurethaneComposite materialAcrylateCarbon nanotubeUltimate tensile strengthSurface modificationComposite numberPolymerChemical engineeringCopolymer

Abstract

fetched live from OpenAlex

ABSTRACT A new class of hydrophilic multiwalled carbon nanotubes (MWCNTs) was prepared by amidation of carboxylated MWCNTs and then undergoing the Michael addition reactions with hydroxyethyl acrylate (HEA), acryloyl morpholine (ACMO), and acrylamide (AM), respectively. The functionalized MWCNTs were dispersible well in water showing zeta potential value of higher than −33.8 mV. After used as reinforcing filler to fabricate the waterborne polyurethane (WPU) composites, the functionalized MWCNTs showed more homogenous dispersion and stronger interfacial adhesion in/with WPU matrix in comparison with pristine MWCNTs, leading to an effective improvement in the mechanical properties, hydrophilicity and electrical conductivity of the MWCNTs/WPU composites. As fabrication of 1.5 wt % MWCNTs composite, the tensile stress was greatly enhanced by about 20.3, 22.5, and 30.1% from 13.3 MPa of the pristine MWCNTs composites to 16.0, 16.3, and 17.3 MPa for the MWCNTs‐HEA, ‐ACMO, and ‐AM composites, respectively. Varying hydrophilic moieties offered different mechanical properties and electrical conductivities to the MWCNTs/WPU composites, which is suggested to be caused by the improved compatibility and hydrogen bonds between the functionalized MWCNTs and WPU macromolecules. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135 , 46757.

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 score0.741

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 studies0.0000.002
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 head0.008
GPT teacher head0.194
Teacher spread0.186 · 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

Citations12
Published2018
Admission routes1
Has abstractyes

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