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Record W4396732292 · doi:10.1016/j.molliq.2024.124969

Surface tension of aqueous solutions of large organic salts: Tetrabutylammonium acetate solutions

2024· article· en· W4396732292 on OpenAlexaff
Taiki Yamashita, Sota Shigehara, Saman Alavi, Ryo Ohmura

Bibliographic record

VenueJournal of Molecular Liquids · 2024
Typearticle
Languageen
FieldChemical Engineering
TopicThermodynamic properties of mixtures
Canadian institutionsUniversity of Ottawa
FundersJKA Foundation
KeywordsAqueous solutionSurface tensionChemistryInorganic chemistryButyl acetateOrganic chemistryThermodynamicsSolvent

Abstract

fetched live from OpenAlex

Aqueous solutions of simple ionic salts such as NaCl and NaBr have higher surface tensions compared to that of pure water and the surface tension of the solution increases with the increasing concentration of the salt. In contrast, the aqueous solutions of the ion sodium acetate (NaAc), which has an anion with both hydrophilic and hydrophobic parts, have a surface tension less than that of pure water, with the surface tension decreasing with salt concentration. The presence of large cations in the salt may change these trends. In this work, the interfacial tension of aqueous solutions of the organic ionic salt tetrabutylammonium acetate (TBAAc) is measured and compared with that of tetrabutylammonium bromide (TBAB). The surface tension of TBAAc aqueous solutions with mole fractions ranging from 0.00417 to 0.04191 were measured for temperatures ranging from 288.2 to 308.2 K and compared with the surface tension of TBAB solutions at similar concentrations. The experimental results showed that the interfacial tensions of TBAAc and TBAB aqueous solutions decreased with increasing concentration, leveling at around 0.04 mol fraction. At each concentration, the interfacial tensions of the TBAAc solutions were larger than those of the TBAB solutions. For the TBAAc and TBAB solutions, the surface excess concentrations of the salts in the solutions are calculated. The impact of these results structures and properties of these solutions are discussed.

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 score0.131
Threshold uncertainty score0.656

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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