Demineralization of glucose solutions by electrodialysis: Influence of the ionic composition on the mass transfer and process performances
Bibliographic record
Abstract
Abstract The aim of the present work was to investigate the influence of the ionic composition on the demineralization of a saccharide solution containing glucose. Experiments were carried out in order to evaluate the influence of the ionic composition on the solvent and solutes fluxes (glucose and electrolytes) through the membrane under different conditions (ionic compositions: NaCl, Na2SO4 and CaCl2; with or without current). From diffusion experiments (without current), it was shown that the glucose diffusion flux decreases for increasing ion hydration. These results are in agreement with those obtained in a previous work showing that the transfer modification reflects changes in the membrane properties associated with the hydration of its counter‐ion which is likely linked to swelling mechanisms at a microscopic scale. From the experiments carried out in normal ED conditions (with current) an additional convective contribution was pointed out. This kind of result is rather scarce in the literature. The glucose flux was then the sum of two contributions: diffusion and convection, due to the electro‐osmotic flux which is proportional to the electrical current. The contribution of the glucose convection flux on the overall glucose transfer was ranged between 70 and 90 % according to the electrolyte nature (NaCl, Na2SO4 and CaCl2) and the electric current (150 or 300 A m−2). The variation of the convective flux has been further correlated to the hydration of the ions. Indeed increasing convection fluxes were obtained for decreasing anion (or cation) hydration. It was shown that the saccharide transfer increases in presence of salts and that this increase was correlated to the saccharide dehydration in presence of electrolyte. Finally, the solvent, ions and glucose fluxes were used to calculate the glucose loss factor versus the demineralization factor to evaluate the influence of the electrolyte nature on the demineralization process performances. It was observed that, for a fixed demineralization factor, the glucose loss factor (comprised between 4 and 5 % for a demineralization factor of 90 %) increased with the ion hydration due to the higher contribution of the glucose convection flux.
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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".