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Record W2797485401 · doi:10.1039/c8sc00758f

Origin of poor doping efficiency in solution processed organic semiconductors

2018· article· en· W2797485401 on OpenAlexaff
Ajay Jha, Hong-Guang Duan, Vandana Tiwari, Michael Thorwart, R. J. Dwayne Miller

Bibliographic record

VenueChemical Science · 2018
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Toronto
FundersMax-Planck-GesellschaftDeutsche ForschungsgemeinschaftTata Institute of Fundamental Research
KeywordsDopingOrganic semiconductorMaterials scienceIonSemiconductorCharge carrierChemical physicsPolymerCharge (physics)OptoelectronicsCoupling (piping)SpectroscopyAnalytical Chemistry (journal)ChemistryOrganic chemistryPhysicsMetallurgyComposite material

Abstract

fetched live from OpenAlex

with an intermolecular distance of ∼4.5 Å between ions in solution, which is approximately the expected distance in processed films. The fact that this relationship persists from solution to the processed film gives direct evidence that Coulomb interactions are retained from the precursor solution to the processed films. This memory effect renders the charge carriers equally bound also in the film and, hence, results in poor doping efficiencies. This new insight will help pave the way towards rational tailoring of the electronic interactions to improve doping efficiencies in processed organic semiconductor 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 score0.015
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.231
Teacher spread0.221 · 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

Citations29
Published2018
Admission routes1
Has abstractyes

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