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Electrical transport properties of single wall carbon nanotube/polyurethane composite based field effect transistors fabricated by UV-assisted direct-writing technology

2012· article· en· W1988107314 on OpenAlexaff
Brahim Aïssa, Daniel Therriault, Rouhollah D. Farahani, Louis Laberge Lebel, My Alı El Khakani

Bibliographic record

VenueNanotechnology · 2012
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsPolytechnique MontréalInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMicrofiberMaterials sciencePolyurethaneComposite numberNanocompositeCarbon nanotubeFabricationComposite materialField-effect transistorIonTransistorNanotechnologyOptoelectronicsVoltageOrganic chemistryElectrical engineering

Abstract

fetched live from OpenAlex

We report on the fabrication and transport properties of single-walled carbon nanotube (SWCNT)/polyurethane (PU) nanocomposite microfiber-based field effect transistors (FETs). UV-assisted direct-writing technology was used, and microfibers consisting of cylindrical micro-rods, having different diameters and various SWCNT loads, were fabricated directly onto SiO₂/Si substrates in a FET scheme. The room temperature dc electrical conductivities of these microfibers were shown to increase with respect to the SWCNT concentrations in the nanocomposite, and were about ten orders of magnitude higher than that of the pure polyurethane, when the SWCNT load ranged from 0.1 to 2.5 wt% only. Our results show that for SWCNT loads ≤ 1.5 wt%, all the microfibers behave as a FET with p-type transport. The resulting FET exhibited excellent performance, with an I(on)/I(off) ratio of 10⁵ and a maximum on-state current (I(on)) exceeding 70 µA. Correlations between the FET performance, SWCNTs concentration, and the microfiber diameters are also discussed.

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 categoriesMeta-epidemiology (narrow), Research integrity
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 score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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.

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

Citations19
Published2012
Admission routes1
Has abstractyes

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