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Record W2386902208 · doi:10.1021/acs.langmuir.6b01104

Morphology and Composition of Structured, Phase-Separated Behenic Acid–Perfluorotetradecanoic Acid Monolayer Films

2016· article· en· W2386902208 on OpenAlexafffund
Jeveria Rehman, Hessamaddin Younesi Araghi, Anqiang He, Matthew F. Paige

Bibliographic record

VenueLangmuir · 2016
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsUniversity of AlbertaUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationUniversity of Saskatchewan
KeywordsMiscibilityBehenic acidMonolayerChemical engineeringMorphology (biology)Pulmonary surfactantMaterials sciencePhase (matter)AdsorptionContext (archaeology)Microscale chemistrySpinodal decompositionChemistryOrganic chemistryNanotechnologyPolymer

Abstract

fetched live from OpenAlex

The phase separation of immiscible surfactants in mixed monolayer films provides an approach to physically manipulate important properties of thin films, including surface morphology, microscale composition, and mechanical properties. In this work, we predict, based upon existing miscibility studies and their thermodynamic underpinnings described in the literature, the miscibility and film morphology of mixed monolayers comprised of behenic acid (C21H43COOH) and perfluorotetradecanoic acid (C13F27COOH) in various molar ratios. Predictions are tested using a combination of experimental surface characterization methods for probing miscibility and film morphology at the solid/air and air/water interfaces. Film components were immiscible and phase-separated into chemically well-defined domains under a variety of experimental conditions, with monolayer morphology consistent with initial predictions. The extensibility of these basic predictions to other systems is discussed in the context of using these works for different perfluorinated surfactant molecules.

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 categoriesInsufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score0.999

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)0.0020.000

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 head0.013
GPT teacher head0.250
Teacher spread0.236 · 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

Citations16
Published2016
Admission routes2
Has abstractyes

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