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Record W4387715541 · doi:10.1039/d3cp03640e

Surface doping of rubrene single crystals by molecular electron donors and acceptors

2023· article· en· W4387715541 on OpenAlexaff
Christos Gatsios, Andreas Opitz, Dominique Lungwitz, Ahmed E. Mansour, Thorsten Schultz, Dongguen Shin, Sebastian Hammer, Jens Pflaum, Yadong Zhang, Stephen Barlow, Seth R. Marder, Norbert Koch

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2023
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsMcGill University
FundersH2020 Marie Skłodowska-Curie ActionsDivision of Materials ResearchHorizon 2020 Framework ProgrammeDeutsche ForschungsgemeinschaftEuropean CommissionBayerisches Staatsministerium für Wissenschaft, Forschung und KunstNational Natural Science Foundation of ChinaSolar Technologies go HybridNational Science Foundation
KeywordsRubreneDopingMaterials scienceOrganic semiconductorDopantElectron mobilityFermi levelBand gapOptoelectronicsSemiconductorCrystal (programming language)Molecular electronicsChemical physicsElectronNanotechnologyChemistryMoleculePhysicsComputer science

Abstract

fetched live from OpenAlex

The surface molecular doping of organic semiconductors can play an important role in the development of organic electronic or optoelectronic devices. Single-crystal rubrene remains a leading molecular candidate for applications in electronics due to its high hole mobility. In parallel, intensive research into the fabrication of flexible organic electronics requires the careful design of functional interfaces to enable optimal device characteristics. To this end, the present work seeks to understand the effect of surface molecular doping on the electronic band structure of rubrene single crystals. Our angle-resolved photoemission measurements reveal that the Fermi level moves in the band gap of rubrene depending on the direction of surface electron-transfer reactions with the molecular dopants, yet the valence band dispersion remains essentially unperturbed. This indicates that surface electron-transfer doping of a molecular single crystal can effectively modify the near-surface charge density, while retaining good charge-carrier mobility.

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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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