Simultaneous consolidation and remediation of copper-contaminated sediments with vacuum electro-osmosis
Bibliographic record
Abstract
Contaminated sediment treatment typically requires both dehydration and decontamination, which are normally investigated separately. By integrating vacuum electro-osmosis with electrokinetic remediation technologies, this study demonstrates the potential for simultaneous consolidation and remediation. A novel experiment system for vacuum electro-osmosis was developed to treat sediments with varying initial copper concentrations. The electrical characteristics indicated that both vacuum pressure and copper ions significantly affected the maintenance of electrical conductivity. Vacuum membrane compression increased effective potential by 5–6 V, and there was a clear positive correlation between initial currents and initial concentration of contaminants. The consolidation properties revealed that as contaminants and moisture were removed, the pores between soil particles increased, causing sudden subsidence in the middle area. Higher initial concentration contributed to higher ultimate drainage volumes, peaking at 1950.25 mL, and more evenly distributed settlement. Copper content measurements suggested that excessively low or high initial concentrations of copper diminished remediation effectiveness, with the highest anodic decontamination efficiency at 60%, albeit at the detriment of the cathode region. Copper fractions analysis revealed that weak acid-extractable and water-soluble fractions accounted for over 85% of total copper, predominantly influencing consolidation and remediation.
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.
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 | 0.001 |
| 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 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".