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Record W2779476017 · doi:10.3390/ma11010008

Organic Thin Film Transistors Incorporating Solution Processable Thieno[3,2-b]thiophene Thienoacenes

2017· article· en· W2779476017 on OpenAlexaff
Nicole A. Rice, François Magnan, Owen A. Melville, Jaclyn L. Brusso, Benoît H. Lessard

Bibliographic record

VenueMaterials · 2017
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsThiopheneMaterials scienceConjugated systemMoietyThin-film transistorMoleculeOrganic semiconductorPolymerTransistorElectron mobilityOrganic electronicsSmall moleculeField-effect transistorThin filmNanotechnologyOptoelectronicsChemical engineeringOrganic chemistryChemistryComposite materialElectrical engineering

Abstract

fetched live from OpenAlex

Bottom-gate bottom-contact organic thin film transistors (OTFTs) were prepared with four novel star-shaped conjugated molecules containing a fused thieno[3,2-b]thiophene moiety incorporated either in the core and/or at the periphery of the molecular framework. The molecules were soluble in CS2, allowing for solution-processing techniques to be employed. OTFTs with different channel geometries were characterized in both air and vacuum in order to compare environmental effects on performance. Blending the small molecules with poly(styrene), an insulating polymer, facilitated the formation of an even semiconducting film, resulting in an order of magnitude increase in device mobility. The highest field-effect mobilities were in air and on the order of 10−3 cm2/Vs for three of the four molecules, with a maximum mobility of 9.2 × 10−3 cm2/Vs achieved for the most conjugated small molecule. This study explores the relationship between processing conditions and OTFT devices performance for four different molecules within this new family of materials, resulting in a deeper insight into their potential as solution-processable semiconductors.

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 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 score0.856

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 studies0.0010.000
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 head0.010
GPT teacher head0.204
Teacher spread0.193 · 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

Citations17
Published2017
Admission routes1
Has abstractyes

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