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Record W2604268998 · doi:10.18311/jsst/2016/14746

Interaction of a Cationic Surfactant with an Oppositely Charged Polymer

2017· article· en· W2604268998 on OpenAlexaff
Soumen Ghosh, Arpan Mal, Tanushree Chakraborty, Gobinda Chandra De, D. Gerrard Marangoni

Bibliographic record

VenueJournal of Surface Science and Technology · 2017
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsPulmonary surfactantChemistryCarboxymethyl celluloseCationic polymerizationConductometryPolymerTurbidimetryAqueous solutionMonomerCritical micelle concentrationMicelleAdsorptionPolymer chemistryInorganic chemistryChemical engineeringSodiumChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

The interactions between the cationic surfactant Dodecyltrimethylammonium Bromide (DTAB) and anionic polymer sodium carboxymethyl cellulose (Na-CMC) in aqueous medium were studied at 300K over different concentrations of Na-CMC by tensiometry, conductometry, viscometry, turbidimetry and fluorimetry. Aggregation of surfactant was attained in two steps, the first being the monomeric adsorption of surfactants on anionic sites of the polymer saturating at lower concentrations of surfactant and the second one being the formation of micelles by surfactants at higher concentrations. Mainly, two types of interactions prevailed throughout namely, electrostatic and hydrophobic interactions. Due to the variation of the interactions depending on the concentrations of polymer, there has been considerable differences in the behavioural pattern of the profiles for the lower concentrations of polymer compared to that of the upper ones.

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)0.001
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 score0.051
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.017
GPT teacher head0.274
Teacher spread0.257 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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