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Record W1479884101 · doi:10.1039/c2cp40937b

Poly(2,5-bis(2-octyldodecyl)-3,6-di(furan-2-yl)-2,5-dihydro-pyrrolo[3,4-c]pyrrole-1,4-dione-co-thieno[3,2-b]thiophene): a high performance polymer semiconductor for both organic thin film transistors and organic photovoltaics

2012· article· en· W1479884101 on OpenAlexaff
Y. Li, Prashant Sonar, Samarendra P. Singh, Zi‐En Ooi, Erica S. H. Lek

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2012
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsThiopheneOrganic solar cellMaterials sciencePyrroleAcceptorFuranOrganic semiconductorEnergy conversion efficiencyPolymer solar cellElectron mobilitySide chainSemiconductorBand gapPolymerPhotochemistryPolymer chemistryChemistryOrganic chemistryOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

A new diketopyrrolopyrrole (DPP)-containing donor-acceptor polymer, poly(2,5-bis(2-octyldodecyl)-3,6-di(furan-2-yl)-2,5-dihydro-pyrrolo[3,4-c]pyrrole-1,4-dione-co-thieno[3,2-b]thiophene) (PDBF-co-TT), is synthesized and studied as a semiconductor in organic thin film transistors (OTFTs) and organic photovoltaics (OPVs). High hole mobility of up to 0.53 cm(2) V(-1) s(-1) in bottom-gate, top-contact OTFT devices is achieved owing to the ordered polymer chain packing and favoured chain orientation, strong intermolecular interactions, as well as uniform film morphology of PDBF-co-TT. The optimum band gap of 1.39 eV and high hole mobility make this polymer a promising donor semiconductor for the solar cell application. When paired with a fullerene acceptor, PC71BM, the resulting OPV devices show a high power conversion efficiency of up to 4.38% under simulated standard AM1.5 solar illumination.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.200
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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes1
Has abstractyes

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