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Record W2143925214 · doi:10.1039/c2cp41407d

Self-assembly of a catechol-based macrocycle at the liquid–solid interface: experiments and molecular dynamics simulations

2012· article· en· W2143925214 on OpenAlexaff
Javier Saiz‐Poseu, Alberto Martínez‐Otero, Thomas J. Roussel, Joseph K.‐H. Hui, Mavis L. Montero, Roberto Urcuyo, Mark J. MacLachlan, Jordi Faraudo, Daniel Ruiz‐Molina

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2012
Typearticle
Languageen
FieldEngineering
TopicSurface Chemistry and Catalysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDesorptionCatecholMolecular dynamicsSolventMoleculeSelf-assemblyChemistryX-ray photoelectron spectroscopyAdsorptionChemical physicsCrystallographyScanning tunneling microscopeMaterials sciencePhysical chemistryChemical engineeringComputational chemistryNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

This combined experimental (STM, XPS) and molecular dynamics simulation study highlights the complex and subtle interplay of solvent effects and surface interactions on the 2-D self-assembly pattern of a Schiff-base macrocycle containing catechol moieties at the liquid-solid interface. STM imaging reveals a hexagonal ordering of the macrocycles at the n-tetradecane/Au(111) interface, compatible with a desorption of the lateral chains of the macrocycle. Interestingly, all the triangular-shaped macrocycles are oriented in the same direction, avoiding a close-packed structure. XPS experiments indicate the presence of a strong macrocycle-surface interaction. Also, MD simulations reveal substantial solvent effects. In particular, we find that co-adsorption of solvent molecules with the macrocycles induces desorption of lateral chains, and the solvent molecules act as spacers stabilizing the open self-assembly pattern.

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 categoriesMeta-epidemiology (narrow)
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 score0.082
Threshold uncertainty score1.000

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 head0.006
GPT teacher head0.249
Teacher spread0.243 · 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.

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

Citations14
Published2012
Admission routes1
Has abstractyes

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