Positive Impact of Pulsed Electric Field on Lactic Acid Removal, Demineralization and Membrane Scaling during Acid Whey Electrodialysis
Bibliographic record
Abstract
The drying of acid whey is hindered by its high mineral and organic acid contents, and their removal is performed industrially through expensive and environmentally impacting serial processes. Previous works demonstrated the ability to remove these elements by electrodialysis alone but with a major concern-membrane scaling. In this study, two conditions of pulsed electric field (PEF) were tested and compared to conventional DC current condition to evaluate the potential of PEF to mitigate membrane scaling and to affect lactic acid and salt removals. The application of a PEF 25 s/25 s pulse/pause combination at an initial under-limiting current density allowed for decreasing the amount of scaling, the final system electrical resistance by 32%, and the relative energy consumption up to 33%. The use of pulsed current also enabled better lactic acid removal than the DC condition by 10% and 16% for PEF 50 s/10 s and 25 s/25 s, respectively. These results would be due to two mechanisms: (1) the mitigation of concentration polarization phenomenon and (2) the rinsing of the membranes during the pause periods. To the best of our knowledge, this was the first time that PEF current conditions were used on acid whey to both demineralize and deacidify it.
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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".