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Record W3084195394 · doi:10.3762/bjnano.11.120

Impact of fluorination on interface energetics and growth of pentacene on Ag(111)

2020· article· en· W3084195394 on OpenAlex
Qi Wang, Antoni Franco-Cañellas, Bin Shen, Thomas Geiger, Holger F. Bettinger, Frank Schreiber, Ingo Salzmann, Alexander Gerlach, Steffen Duhm

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBeilstein Journal of Nanotechnology · 2020
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsConcordia University
FundersHigher Education Discipline Innovation ProjectCollaborative Innovation Center of Suzhou Nano Science and TechnologyState Administration of Foreign Experts AffairsDiamond Light Source
KeywordsMonolayerX-ray photoelectron spectroscopyPentaceneUltraviolet photoelectron spectroscopyMaterials scienceStackingCrystallographyContext (archaeology)AdsorptionLow-energy electron diffractionElectron diffractionDiffractionChemistryNanotechnologyPhysical chemistryLayer (electronics)Nuclear magnetic resonanceOrganic chemistryOpticsPhysics

Abstract

fetched live from OpenAlex

We studied the structural and electronic properties of 2,3,9,10-tetrafluoropentacene (F4PEN) on Ag(111) via X-ray standing waves (XSW), low-energy electron diffraction (LEED) as well as ultraviolet and X-ray photoelectron spectroscopy (UPS and XPS). XSW revealed that the adsorption distances of F4PEN in (sub)monolayers on Ag(111) were 3.00 Å for carbon atoms and 3.05 Å for fluorine atoms. The F4PEN monolayer was essentially lying on Ag(111), and multilayers adopted π-stacking. Our study shed light not only on the F4PEN-Ag(111) interface but also on the fundamental adsorption behavior of fluorinated pentacene derivatives on metals in the context of interface energetics and growth mode.

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.

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 score0.005
Threshold uncertainty score0.279

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 head0.022
GPT teacher head0.306
Teacher spread0.284 · 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