Frothers and gas dispersion: A review of the structure-property-function relationship
Bibliographic record
Abstract
Over the past 20 years quantitative measures of frother functions have been developed to try to replace such qualitative descriptors as "weak" and "strong".One of these metrics is the critical coalescence concentration (CCC) that quantifies a frother's ability to reduce bubble size; another is the concentration at minimum velocity (CMV) that quantifies a frother's ability to reduce bubble rise velocity.The experimental procedure for the two measures is briefly outlined and the measures are shown to be related.Using CMV, based on more than 50 surfactants from the two main frother families, alcohols and polyglycols, the frother structure-property-function link is investigated.The structure variables were: in alcohols, alkyl chain length, and position of the methyl branch and hydroxyl group(s); and in polyglycols, alkyl chain length, and number of propylene oxide (PO) or ethylene oxide (EO) groups.On the argument that low CMV represents the desired outcome, the main findings are: the dominant effect of alkyl chain length in both alcohols and polyglycols; that for alcohols branched-chain isomers are superior to straight chain, with the best combination being OH at the terminus and the methyl branch as far away as possible; and for polyglycols, PO-based are superior to EO-based.Interpretation of these observations included the effect of structure on the following properties: surface activity, mass transfer rate, H-bonding, and molecule packing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".