Understanding and mitigating performance decline in electrochemical deionization
Bibliographic record
Abstract
Capacitive deionization based on carbonaceous electrodes represents an energy-efficient technology suitable for low-salinity brackish water desalination where high recovery rates are critical to economic viability. Substituting insertion compounds for carbonaceous materials in electrochemical desalination electrodes enables higher ion adsorption capacities, excellent energy efficiency in higher salinity feedwaters, and selective removal of target ions. Despite the promise of electrochemical desalination processes, the durability of the electrode materials when treating complex waters is a documented issue that has not been systematically investigated. The present work reviews recent work on the impact of fouling on the performance of carbonaceous and insertion-based electrochemical desalination processes; discusses key factors controlling the corrosion/degradation of carbonaceous and insertion-based electrodes used in electrochemical desalination; and identifies potential strategies for improving the fouling tolerance and minimizing the corrosion or degradation of carbonaceous and insertion based electrodes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".