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Record W2912248478 · doi:10.1088/1361-648x/ab0171

Energy-level alignment at strongly coupled organic–metal interfaces

2019· article· en· W2912248478 on OpenAlexafffund
Meng-Ting Chen, Oliver T. Hofmann, Alexander Gerlach, Benjamin Bröker, Christoph Bürker, Jens Niederhausen, Takuya Hosokai, J. Zegenhagen, Antje Vollmer, Ralph Rieger, Kläus Müllen, Frank Schreiber, Ingo Salzmann, Norbert Koch, Egbert Zojer, Steffen Duhm

Bibliographic record

VenueJournal of Physics Condensed Matter · 2019
Typearticle
Languageen
FieldMaterials Science
TopicMachine Learning in Materials Science
Canadian institutionsConcordia University
FundersNational Key Research and Development Program of ChinaNatural Sciences and Engineering Research Council of CanadaCollaborative Innovation Center of Suzhou Nano Science and TechnologyHigher Education Discipline Innovation ProjectState Administration of Foreign Experts AffairsAustrian Science FundConcordia UniversitySoochow UniversityEuropean Synchrotron Radiation FacilityDeutsche Forschungsgemeinschaft
KeywordsX-ray photoelectron spectroscopyUltraviolet photoelectron spectroscopyWork functionWork (physics)Density functional theorySubstrate (aquarium)Materials scienceMetalChemical physicsFermi levelUltravioletSpectroscopyElectronic structureOptoelectronicsChemistryComputational chemistryPhysicsThermodynamicsNuclear magnetic resonanceMetallurgy

Abstract

fetched live from OpenAlex

Energy-level alignment at organic-metal interfaces plays a crucial role for the performance of organic electronic devices. However, reliable models to predict energetics at strongly coupled interfaces are still lacking. We elucidate contact formation of 1,2,5,6,9,10-coronenehexone (COHON) to the (1 1 1)-surfaces of coinage metals by means of ultraviolet photoelectron spectroscopy, x-ray photoelectron spectroscopy, the x-ray standing wave technique, and density functional theory calculations. While for low COHON thicknesses, the work-functions of the systems vary considerably, for thicker organic films Fermi-level pinning leads to identical work functions of 5.2 eV for all COHON-covered metals irrespective of the pristine substrate work function and the interfacial interaction strength.

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 score0.005

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 communication0.0010.001
Open science0.0010.001
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 head0.013
GPT teacher head0.236
Teacher spread0.224 · 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

Citations19
Published2019
Admission routes2
Has abstractyes

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