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Record W2982557666 · doi:10.1088/1361-6528/ab5274

Functionalized single-walled carbon-nanotube-blended P3HT-based high performance memory behavior thin-film transistor devices

2019· article· en· W2982557666 on OpenAlexafffund
Brahim Aïssa, Adnan Ali, Ali Bentouaf, Waqar Khan, Mohammad Istiaque Hossain, Jens Kroeger

Bibliographic record

VenueNanotechnology · 2019
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsRaymor (Canada)MPB Technologies & Communications (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceCarbon nanotubeOptoelectronicsTransistorFabricationThin-film transistorComposite numberNanotechnologyActive layerLayer (electronics)Composite materialElectrical engineering

Abstract

fetched live from OpenAlex

Abstract We report on the fabrication and transport properties of single-walled carbon nanotubes (SWCNT) blended with P3HT (poly 3-hexyl thiophene-2, 5-diyl). The composite is used as a hybrid organic active channel transistor. The performances of the fabricated devices were investigated as a function of the SWCNTs’ loads in the composite, and their response evaluated under white light illumination. Our results show that for SWCNT loads ≤1.5 wt%, all the devices behave as p-type transistors, exhibiting excellent performance, with an I on /I off ratio of 10 4 and a maximum on-state current ( I on ) exceeding 80 μ A. Moreover, compared with pristine transistors with a P3HT channel, the Hall mobility of these hybrid TFTs was found to increase by more than one order of magnitude, i.e. increasing from 0.062 to 1.54 cm 2 V −1 s −1 . Finally, under light illumination, the transfer characteristics (i.e. I DS as a function of V GS ) were found to systematically undergo a typical shift together with a fully-reversible memory behavior. A fundamental understanding of this work can assist in providing new routes for the development of reliable efficient hybrid organic-based optoelectronic devices.

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)0.000
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 score0.044
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.180
Teacher spread0.174 · 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

Citations12
Published2019
Admission routes2
Has abstractyes

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