Electrochemical Mass Transfer Measurements with Glycerin Used To Reach High Schmidt Numbers
Bibliographic record
Abstract
The electrochemical technique with the ferri−ferrocyanide system has been used to study mass transfer at high Schmidt numbers in a straight pipe and a Y-bifurcation flow model, with the latter being relevant to arterial blood flow and atherosclerosis. Results at higher Sc values were wanted in order to match blood properties ( Sc ranging from 1.5 × 10 5 to 6 × 10 5 ). Glycerin was found to be the best viscosity modifier, although it posed some experimental problems; the presence of glycerin and sodium hydroxide results in the degradation of ferricyanide ions. The rate of degradation is directly proportional to the temperature and ferricyanide concentration. Thus, the experiments had to be performed rapidly after preparation of the solution. After optimization of the experimental conditions, a Schmidt number of about 50 000 was obtained, higher than those attained previously and likely the highest Schmidt number achieved experimentally in homogeneous solutions. Averaged mass transfer in both the pipe and the bifurcation showed the same trend as those obtained previously at lower Schmidt numbers. The dependence of the Sherwood number on Sc 1/3 holds well for laminar flow up to at least Sc = 50 000. The 1/3 exponent also holds in turbulent flow, measured up to a Reynolds number of 10 000.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".