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Record W2603197872 · doi:10.1021/acs.jpcc.7b00391

Influence of Halogen Bonds on the Compactness of Supramolecular Assemblies on Si(111)-B

2017· article· en· W2603197872 on OpenAlexafffund
Gaolei Zhan, Marc‐André Dubois, Younes Makoudi, Simon Lamare, Judicaël Jeannoutot, Xavier Bouju, Alain Rochefort, Frank Palmino, Frédéric Chérioux

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2017
Typearticle
Languageen
FieldEngineering
TopicSurface Chemistry and Catalysis
Canadian institutionsPolytechnique MontréalRegroupement Québécois sur les Matériaux de Pointe
FundersNatural Sciences and Engineering Research Council of CanadaAgence Nationale de la Recherche
KeywordsSupramolecular chemistryScanning tunneling microscopevan der Waals forceHalogenHalogen bondMoleculeCrystallographyChemistryChemical physicsMaterials scienceHydrogen bondNanotechnologyAlkylOrganic chemistry

Abstract

fetched live from OpenAlex

The role of halogen bonds on the molecular structure of large assemblies on a weakly reactive surface has been investigated. Our scanning tunneling microscopy (STM) experiments reveal a large variation of compactness of assemblies along the amount of halogen bonds within the building unit. In brief, we observe an increasing compactness of the supramolecular structures for zero, one, and two halogen atoms per molecule. Our experimental results are supported by molecular and STM calculations where the presence of van der Waals interactions was also considered. We found that molecular units adopt a structural arrangement that maximizes highly selective nitrogen-surface bonding and favor lateral interactions where the molecules are driven by halogen bonds. This study suggests that the presence of halogen bonds can be an efficient tool to control the molecular arrangement within two-dimension or one-dimension supramolecular networks on a silicon surface.

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 score0.127
Threshold uncertainty score0.321

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 science0.0010.000
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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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

Citations7
Published2017
Admission routes2
Has abstractyes

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