MétaCan
Menu
Back to cohort
Record W3022331029 · doi:10.1002/cplu.202000233

Anthracene−Pentacene Dyads: Synthesis and OFET Characterization

2020· article· en· W3022331029 on OpenAlexafffund
Miriam Hauschild, Lan Chen, Sebastian H. Etschel, Michael J. Ferguson, Frank Hampel, Marcus Halik, Rik R. Tykwinski

Bibliographic record

VenueChemPlusChem · 2020
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche ForschungsgemeinschaftUniversity of Alberta
KeywordsPentaceneAnthraceneMaterials scienceOrganic semiconductorAmbipolar diffusionPhotochemistryOrganic field-effect transistorChemistryThin-film transistorCrystallographyNanotechnologyOptoelectronicsElectronField-effect transistorTransistor

Abstract

fetched live from OpenAlex

Abstract The synthesis of a series of unsymmetrical derivatives of pentacene appended with functionalized anthracene moieties is reported. These anthracene−pentacene dyads have been characterized by UV‐vis spectroscopy and cyclic voltammetry to examine their electronic properties. X‐ray crystallographic analysis was used to examine the solid‐state features of anthracene−pentacene dyads 1 a – d with H−, F−, Cl−, and Br− substituents on the 9‐position of anthracene, and shows that the packing arrangement of anthracene−pentacene derivatives 1 b,d,e are remarkably similar irrespective of the presence of fluoride, bromide or methyl substituents. The pentacene−anthracene dyads have been incorporated into OTFTs to evaluate their semiconducting properties. The pentacene derivative 1 b shows ambipolar behavior using AlO x C 14 PA as the gate dielectric (electron and hole mobilities of 7.6 ⋅ 10 −3 and 1.6 ⋅ 10 −1 cm 2 V −1 s −1 ), while performance of all derivatives was poor using p‐doped Silicon as the substrate. These studies highlight the importance of thin‐film formation over molecular structure.

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 score0.028
Threshold uncertainty score0.552

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 head0.010
GPT teacher head0.184
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.

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

Citations3
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueChemPlusChemSame topicOrganic Electronics and PhotovoltaicsFrench-language works237,207