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Record W3048264043 · doi:10.1002/smll.202002393

Oxygen‐Induced 1D to 2D Transformation of On‐Surface Organometallic Structures

2020· article· en· W3048264043 on OpenAlexaff
Penghui Ji, Gianluca Galeotti, F. De Marchi, Daling Cui, Kewei Sun, Haiming Zhang, G. Contini, Maryam Ebrahimi, Oliver MacLean, Federico Rosei, Lifeng Chi

Bibliographic record

VenueSmall · 2020
Typearticle
Languageen
FieldEngineering
TopicSurface Chemistry and Catalysis
Canadian institutionsLakehead UniversityInstitut National de la Recherche Scientifique
FundersNational Natural Science Foundation of ChinaMinistry of Science and Technology
KeywordsScanning tunneling microscopeX-ray photoelectron spectroscopyAdsorptionOxygenPolymerDensity functional theoryPolymerizationAnnealing (glass)Materials scienceChemical physicsChemical engineeringChemistryNanotechnologyPhotochemistryPhysical chemistryComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

While surface-confined Ullmann-type coupling has been widely investigated for its potential to produce π-conjugated polymers with unique properties, the pathway of this reaction in the presence of adsorbed oxygen has yet to be explored. Here, the effect of oxygen adsorption between different steps of the polymerization reaction is studied, revealing an unexpected transformation of the 1D organometallic (OM) chains to 2D OM networks by annealing, rather than the 1D polymer obtained on pristine surfaces. Characterization by scanning tunneling microscopy and X-ray photoelectron spectroscopy indicates that the networks consist of OM segments stabilized by chemisorbed oxygen at the vertices of the segments, as supported by density functional theory calculations. Hexagonal 2D OM networks with different sizes on Cu(111) can be created using precursors with different length, either 4,4″-dibromo-p-terphenyl or 1,4-dibromobenzene (dBB), and square networks are obtained from dBB on Cu(100). The control over size and symmetry illustrates a versatile surface patterning technique, with potential applications in confined reactions and host-guest chemistry.

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 score0.094
Threshold uncertainty score0.408

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 head0.024
GPT teacher head0.204
Teacher spread0.180 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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