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Record W1979897656 · doi:10.1021/la062890n

Structural and Compositional Mapping of a Phase-Separated Langmuir−Blodgett Monolayer by Atomic Force Microscopy

2007· article· en· W1979897656 on OpenAlexafffund
Shatha E. Qaqish, Matthew F. Paige

Bibliographic record

VenueLangmuir · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMonolayerArachidic acidLangmuir–Blodgett filmChemistryHexadecaneSurface pressurePhase (matter)LangmuirSubstrate (aquarium)Surface forces apparatusAnalytical Chemistry (journal)CrystallographyAdhesionOrganic chemistryAqueous solution

Abstract

fetched live from OpenAlex

The structure and composition of a phase-separated arachidic acid (C19H39COOH) (AA) and perfluorotetradecanoic acid (C13F27COOH) (PA) Langmuir-Blodgett monolayer film was characterized by several different types of atomic force microscopic measurements. At the liquid-air interface, surface pressure-area isotherms show that mixtures of the two acids follow the additivity rule expected from ideal mixtures. Topographic images of the deposited monolayer indicate that the surfactants are oriented normal to the substrate surface, and that the acids undergo phase separation to form a series of discontinuous, hexagonal domains separated by a continuous domain. A combination of lateral force (friction) imaging and adhesion force measurements show that the discontinuous domains are enriched in AA, whereas the surrounding continuous domain is a mixture of both AA and PA. This was further verified by selective, in situ dissolution of AA by n-hexadecane, followed by high-resolution topographical imaging of the discontinuous domains.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.306
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2007
Admission routes2
Has abstractyes

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