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Record W3017650629 · doi:10.3390/ma13081961

Developing and Comparing 2,6-Anthracene Derivatives: Optical, Electrochemical, Thermal, and Their Use in Organic Thin Film Transistors

2020· article· en· W3017650629 on OpenAlexafffund
Mikhail Y. Vorona, Nathan J. Yutronkie, Owen A. Melville, Andrew J. Daszczynski, Jeffrey S. Ovens, Jaclyn L. Brusso, Benoît H. Lessard

Bibliographic record

VenueMaterials · 2020
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnthraceneMaterials scienceThermal stabilityMoietyOrganic semiconductorMelting pointThin-film transistorIntermolecular forceOrganic electronicsElectrochemistryTransistorOptoelectronicsPhotochemistryOrganic chemistryNanotechnologyLayer (electronics)ChemistryPhysical chemistryMoleculeElectrodeComposite material

Abstract

fetched live from OpenAlex

Anthracene-based semiconductors have attracted great interest due to their molecular planarity, ambient and thermal stability, tunable frontier molecular orbitals and strong intermolecular interactions that can lead to good device field-effect transistor performance. In this study, we report the synthesis of six anthracene derivatives which were di-substituted at the 2,6-positions, their optical, electrochemical and thermal properties, and their single crystal structures. It was found that 2,6-functionalization with various fluorinated phenyl derivatives led to negligible changes in the optical behaviour while influencing the electrochemical properties. Furthermore, the choice of fluorinated phenyl moiety had noticeable effects on melting point and thermal stability (ΔTm < 55 °C and ΔTd < 65 °C). Bottom-gate top-contact (BGTC) organic thin transistors (OTFTs) were fabricated and characterized using the 2,6-anthracene derivatives as the semiconducting layer. The addition of fluorine groups on the phenyl groups led to a transition from p-type behaviour to n-type behaviour in BGBC OTFTs.

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 score0.003
Threshold uncertainty score0.704

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 integrity0.0000.000
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 head0.022
GPT teacher head0.206
Teacher spread0.185 · 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
Published2020
Admission routes2
Has abstractyes

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