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Record W3037726233 · doi:10.1002/cphc.202000359

Morphological and Interaction Characteristics of Surface‐Active Ionic Liquids and Palmitic Acid in Mixed Monolayers

2020· article· en· W3037726233 on OpenAlexaff
Ala’a F. Eftaiha, Abdussalam K. Qaroush, Ghada G. Kayed, Abdel Rahman K. Abdel Rahman, Khaleel I. Assaf, Matthew F. Paige

Bibliographic record

VenueChemPhysChem · 2020
Typearticle
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAlkylBrewster's angleMonolayerSurface pressureIonic liquidChemistryLangmuirChemical engineeringAnalytical Chemistry (journal)CrystallographyPhysical chemistryOrganic chemistryAqueous solutionOptics

Abstract

fetched live from OpenAlex

Abstract A series of water soluble, surface‐active ionic liquids (SAILs), namely, 1‐alkyl‐3‐methyl imidazolium chlorides ([C n ‐ mim ]Cl) and their mixtures with palmitic acid (PA) are investigated in Langmuir monolayers and Langmuir–Blodgett films. It is inferred from the surface pressure‐area isotherms that C 16 ‐ mim ‐IL mixes non‐ideally with PA and stabilizes the binary mixed films. In addition, the residence of mim ‐IL at the water surface is enhanced as a function of the increasing alkyl side chain length. Generally, the compressional moduli values decrease upon increasing the content of the mim ‐ILs over a wide range of compositions. Furthermore, film relaxation measurements indicate that the IL component is selectively excluded from the mixed films upon achieving a certain target pressure. Brewster angle microscope images demonstrate minimal changes on the PA domains in the presence of either C 4 ‐ and C 8 ‐ mim ‐ILs, whereas presence of the hexadecyl counterpart results in the formation of condensed sheets. Atomic force microscopy imaging of deposited films show the formation of propeller‐like aggregates when C 8 ‐ or C 16 ‐ mim ‐IL is present in the mixed films.

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 score0.029
Threshold uncertainty score0.437

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 head0.023
GPT teacher head0.232
Teacher spread0.210 · 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

Citations10
Published2020
Admission routes1
Has abstractyes

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