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Record W2077015111 · doi:10.1021/ma100212h

High-Performance Polythiophene Thin-Film Transistors Processed with Environmentally Benign Solvent

2010· article· en· W2077015111 on OpenAlexaff
Ping Liu, Yiliang Wu, Hualong Pan, Beng S. Ong, Shiping Zhu

Bibliographic record

VenueMacromolecules · 2010
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsMcMaster UniversityXerox (Canada)
Fundersnot available
KeywordsPolythiopheneThin-film transistorMaterials scienceSolventEnvironmentally friendlyOrganic semiconductorElectron mobilitySolubilityTransistorSemiconductorPolymerThin filmNanotechnologyChemical engineeringOptoelectronicsOrganic chemistryConductive polymerChemistryComposite materialElectrical engineering

Abstract

fetched live from OpenAlex

Solution processable organic thin-film transistors (OTFTs) have attracted great attention recently due to their high potentials to dramatically reduce the manufacturing cost for large-area and flexible electronic devices. However, most high performance polymeric semiconductors require chlorinated solvents for their device fabrications, which is not an environmentally friendly manufacturing process. In this article, we describe a facile approach to tuning the solubility characteristics of a high mobility polythiophene system by strategic structure modification and demonstrate significantly improved solution properties in environmentally benign solvents with high field-effect mobility up to 0.18 cm 2 V −1 s −1 . To our best knowledge, this is one of the highest mobility values reported so far for solution-processed OTFTs fabricated from polymeric semiconductors in nonchlorinated solvents. Furthermore, the molecular orientations and structural properties of newly developed polythiophenes were evaluated by both single crystal data of their building blocks and X-ray diffraction (XRD) of their thin films.

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 score0.002
Threshold uncertainty score0.840

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 head0.002
GPT teacher head0.155
Teacher spread0.153 · 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

Citations31
Published2010
Admission routes1
Has abstractyes

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