Liquid-liquid dispersion under pulsed electric fields in a horizontal cell
Bibliographic record
Abstract
Liquid-liquid reactors require good agitation and large interfacial area, as does liquid-liquid extraction equipment. Conventionally, droplet dispersion is obtained by mechanical agitation, for example, in stirred tanks. An alternative approach involving much less energy consumption is to promote droplet dispersion and motion by applying an electric field. The formation and initial motion of drops provide the focus for this study. The apparatus used was a nearly horizontal rectangular cell (38*10*10 cm) equipped with parallel electrode plates along the two sides of the cell as well as a stainless steel nozzle (0.71 mm diameter) connected to a high-voltage pulsed electric power supply. The experiments were carried out in this liquid-liquid contactor by generating a series of single droplets of distilled water from the grounded nozzle and observing their subsequent motion in the viscous continuous phase under the influence of the pulsed electric field. As the applied voltage was increased, the formed droplets were reduced in size and showed repulsion and some upwards scattering: the droplet velocity near the nozzle was greatly increased by the field, with the droplets decelerating as they moved away from the nozzle.>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".