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Record W2318083523 · doi:10.1021/nn301827e

Noncovalent Bicomponent Self-Assemblies on a Silicon Surface

2012· article· en· W2318083523 on OpenAlex
Bulent Baris, Judicaël Jeannoutot, Vincent Luzet, Frank Palmino, Alain Rochefort, Frédéric Chérioux

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

VenueACS Nano · 2012
Typearticle
Languageen
FieldEngineering
TopicSurface Chemistry and Catalysis
Canadian institutionsPolytechnique MontréalRegroupement Québécois sur les Matériaux de Pointe
FundersAgence Nationale de la Recherche
KeywordsSupramolecular chemistryMaterials scienceSiliconNanoelectronicsNanotechnologySubstrate (aquarium)Covalent bondMoleculeSelf-assemblyNon-covalent interactionsNanometreChemical physicsOptoelectronicsChemistry

Abstract

fetched live from OpenAlex

Two-dimensional supramolecular multicomponent networks on surfaces are of major interest for the building of highly ordered functional materials with nanometer-sized features especially designed for applications in nanoelectronics, energy storage, sensors, etc. If such molecular edifices have been previously built on noble metals or HOPG surfaces, we have successfully realized a 2D open supramolecular framework on a silicon adatom-based surface under ultrahigh vacuum with thermal stability up to 400 K by combining molecule-molecule and molecule-silicon substrate interactions. One of these robust open networks was further used to control both the growth and the periodicity of the first bicomponent arrays without forming any covalent bond with a silicon surface. Our strategy allows the formation of a well-controlled long-range periodic array of single fullerenes by site-specificity inclusion into a bicomponent supramolecular network.

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 score0.016
Threshold uncertainty score0.675

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)0.0000.001

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 head0.212
Teacher spread0.202 · 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