Membrane Scaling in Electrodialysis Fed with High-Strength Wastewater
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Membrane scaling problems can limit broad applications of electrodialysis (ED) for nutrients recovery from wastewater. In this study, we investigated the calcium- and magnesium-scale precipitation on ion-exchange membranes (IEMs) using a laboratory-scale ED reactor. Two high-strength wastewater streams, including municipal waste (MW) liquid digestate and food waste (FW) liquid digestate, were fed into the ED reactor. For the operation with MW liquid digestate, the cumulative Ca2+ loss increased with the increasing electric current, while the electric current conditions did not affect the cumulative Mg2+ loss. After 8-h operation, 60.1% of Ca2+ and 39.0% of Mg2+ in the MW liquid digestate were lost in the form of precipitates. Observed scalants on cation-exchange membranes were vaterite, amorphous calcium carbonate (ACC), and struvite, while ACC was not found on anion-exchange membranes. Observed scalants of calcium carbonate with MW liquid digestate (vaterite and ACC) were different from scalants (calcite) found with synthetic solutions. Among these scalants, struvite was formed as sharp (needle-shaped) crystals that can potentially damage the IEM. The gradual loss of Mg2+ was observed with FW liquid digestate because of high PO43− concentration, indicating the formation of struvite. The membrane with high selectivity for divalent ions resulted in the rapid decrease in electric current, implying serious membrane scaling on IEMs. These findings demonstrated that the membrane scaling problems by calcium and magnesium precipitation are ubiquitous in ED for nutrients recovery from wastewater.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it