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Record W2105375146 · doi:10.1002/aic.14851

Effect of ionic strength on bubble coalescence in inorganic salt and seawater solutions

2015· article· en· W2105375146 on OpenAlexafffund
Joshua Sovechles, Kristian E. Waters

Bibliographic record

VenueAIChE Journal · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMinerals Flotation and Separation Techniques
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCoalescence (physics)Ionic strengthSeawaterBubbleChemistryElectrolyteIonic bondingSalt (chemistry)Chemical engineeringSalt solutionInorganic chemistryIonAqueous solutionOrganic chemistryPhysical chemistryMechanicsGeologyPhysics

Abstract

fetched live from OpenAlex

Bubble size is of fundamental importance in the flotation process, as it provides the surface area for particle collection. Typically, weak surfactants (frothers) are added to process water to reduce bubble coalescence. Certain inorganic electrolytes, which occur naturally in some flotation process water, have been shown to mimic the role of frothers. The concentration at which bubble coalescence is inhibited, the critical coalescence concentration, was determined in a 5.5‐L mechanical flotation cell for a series of coalescence inhibiting inorganic salts. To mimic some industrial flotation process water, a synthetic sea salt solution was also tested. It was found that when the multicomponent sea salt solution was broken down into its constituent parts, the addition of the ionic strength of each ion correlated well with the overall ionic strength curve of all the salts tested. The critical coalescence ionic strength ranged from 0.22 to 0.35, with sea salt being 0.26. © 2015 American Institute of Chemical Engineers AIChE J , 61: 2489–2496, 2015

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.317

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 integrity0.0000.000
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 head0.273
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

Citations53
Published2015
Admission routes2
Has abstractyes

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