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Record W4411614150 · doi:10.1039/d5cp01414j

Computational study of PEDOT derivatives: reducing air stability to satisfy the self-doping criteria of transparent conjugated polymers

2025· article· en· W4411614150 on OpenAlexafffund
Florian Regnier, Mario Leclerc, Jérôme Cornil

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2025
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaFonds De La Recherche Scientifique - FNRS
KeywordsConjugated systemPEDOT:PSSPolymerDopingTransparency (behavior)Materials scienceConductive polymerConductivityNanotechnologyChemical engineeringOptoelectronicsChemistryComputer sciencePhysical chemistryComposite material

Abstract

fetched live from OpenAlex

PEDOT has been one of the most extensively studied conjugated polymers due to its unique combination of good transparency and high electrical conductivity, making it a promising alternative to ITO electrodes. With the aim of designing more conducting and transparent chains, we provide here a state-of-the-art quantum-chemical (TD)-DFT analysis to investigate whether significant HOMO level destabilization and red-shifted optical absorption in the doped state can be achieved through simple derivatization schemes. We demonstrate that a copolymer featuring an alternation of an EDOT unit and a substituted thiophene ring can compete with PEDOT. Moreover, the calculations indicate that the exact layout of the substituents on the thiophene rings can tune the extent of delocalization of the charge carriers in the doped state, and by extension the charge transport properties.

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 score0.620

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 head0.033
GPT teacher head0.319
Teacher spread0.286 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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