Determination of factors effecting the properties of water-air microdispersion
Bibliographic record
Abstract
The article presents the results of laboratory studies on the effect of the liquid-gas ratio and the foaming agent type on the average water-air micro dispersion size obtained from the foaming agent solution. The size of microbubbles significantly effects the efficiency of flotation and depends on the type and concentration of foaming agent used for their production. A generator was used to obtain water-air micro dispersion. The works were performed to work out the water-air micro dispersion parameters of at different liquid-gas ratio and different performance of the generator. The following foaming agents were used as objects of research: sodium butyl aero flot (BTF), flotanol C-7, butyl triethylenetetramine (B-TETA) at a concentration of 0.5 g/dm3. It has been established, that the optimal phase liquid-gas ratio was 1:1, the optimal capacity of the generator was 6-7.2 dm3/h with an average particle size of air-water micro dispersion- 33-41 mm for BTF solution, 103-107 mm for C-7 solution, 90-93 mm for B-TETA solution. The type of foaming agent used in flotation effects the size and stability of microbubbles. It is established that the flotation agents can be arranged in the following line with respect to their ability to create micro dispersion: IIBK→Senfroth 580→B-TETA→OPSB→Flotanol C-7→T-92→BTF. The best results are shown by BTF that creates micro dispersion of 43-58 μm (t 20-40 °С) and stability of 80 sec with concentration of 0.5 g/dm3.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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 teacher head, 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".