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Record W1975258585 · doi:10.1021/cm900265q

Novel High-Performance Liquid-Crystalline Organic Semiconductors for Thin-Film Transistors

2009· article· en· W1975258585 on OpenAlexaff
Ping Liu, Yiliang Wu, Hualong Pan, Yuning Li, Sandra Gardner, Beng S. Ong, Shiping Zhu

Bibliographic record

VenueChemistry of Materials · 2009
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsMcMaster UniversityXerox (Canada)
Fundersnot available
KeywordsMaterials scienceThiopheneThin filmLiquid crystalOrganic semiconductorSemiconductorBand gapAbsorption spectroscopyDiffractionTexture (cosmology)CrystallographyOptoelectronicsAnalytical Chemistry (journal)Organic chemistryNanotechnologyOpticsChemistry

Abstract

fetched live from OpenAlex

A novel class of liquid-crystalline organic semiconductors based on 2,5′-bis-[2-(4-pentylphenyl)vinyl]-thieno(3,2- b )thiophene and 2,5′-bis-[2-(4-pentylphenyl)vinyl]-(2,2′)bithiophene were synthesized through proper structural design. The materials exhibited high field-effect mobilities up to 0.15 cm 2 V −1 s −1 and current on/off ratio of 1 × 10 6 . The high performance is attributed to their abilities to form highly ordered structures through molecular packing, which is revealed by single-crystal and thin film X-ray diffraction (XRD). The structures were analyzed by polarized optical microscope and showed obvious changes in texture corresponding to the phase changes in DSC diagrams, indicating their abilities to form liquid-crystalline structures. High environmental stabilities have been demonstrated with these new compounds, which is consistent with their low HOMO levels and large band gaps. In addition, UV−vis spectra of the thin films formed from these compounds have showed that their absorption peaks mainly appear in the range of ultraviolet spectrum region, indicating they could be used for the application of those circuits requiring transparency such as 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 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 score0.001
Threshold uncertainty score0.826

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 head0.007
GPT teacher head0.190
Teacher spread0.182 · 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

Citations48
Published2009
Admission routes1
Has abstractyes

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