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Record W4377819783 · doi:10.1002/anie.202304964

Sterically‐Hindered Molecular p‐Dopants Promote Integer Charge Transfer in Organic Semiconductors

2023· article· en· W4377819783 on OpenAlexafffund
Somaiyeh Charoughchi, Jiang Tian Liu, Melissa Berteau‐Rainville, Hannes Hase, Mohammad S. Askari, Shubham Bhagat, Pat Forgione, Ingo Salzmann

Bibliographic record

VenueAngewandte Chemie International Edition · 2023
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsInstitut National de la Recherche ScientifiqueConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversity of TorontoGovernment of CanadaConcordia UniversityFonds de recherche du Québec – Nature et technologiesCanadian Light Source
KeywordsDopantSteric effectsMaterials scienceOrganic semiconductorDopingElectron transferSemiconductorComputational chemistryMoleculeChemical physicsChemistryPhotochemistryOrganic chemistryOptoelectronics

Abstract

fetched live from OpenAlex

Molecular p-dopants designed to undergo electron transfer with organic semiconductors are typically planar molecules with high electron affinity. However, their planarity can promote the formation of ground-state charge transfer complexes with the semiconductor host and results in fractional instead of integer charge transfer, which is highly detrimental to doping efficiency. Here, we show this process can be readily overcome by targeted dopant design exploiting steric hindrance. To this end, we synthesize and characterize the remarkably stable p-dopant 2,2',2''-(cyclopropane-1,2,3-triylidene)tris(2-(perfluorophenyl)acetonitrile) comprising pendant functional groups that sterically shield its central core while retaining high electron affinity. Finally, we demonstrate it outperforms a planar dopant of identical electron affinity and increases the thin film conductivity by up to an order of magnitude. We believe exploiting steric hindrance represents a promising design strategy towards molecular dopants of enhanced doping efficiency.

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 score0.002

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)0.0010.000

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 head0.011
GPT teacher head0.223
Teacher spread0.212 · 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

Citations13
Published2023
Admission routes2
Has abstractyes

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