Electrochemical regeneration of granular activated carbons loaded with phenol and natural organic matter
Bibliographic record
Abstract
The main objective of this study was to assess the performance of electrochemical regeneration of granular activated carbon via a set of bench-scale experiments using different operating conditions in the regeneration of several different activated carbons loaded with phenol or natural organic matter. The regeneration efficiency can be increased by increasing the charge applied, whether this was achieved by an increase in current or regeneration time. The degree of phenol-adsorption saturation did not significantly affect the regeneration efficiencies. The regeneration efficiencies of the various types of phenol-loaded activated carbon were quite similar despite the differences in their conductivity. The activated carbon exhibiting fully reversible adsorption of phenol had slightly higher regeneration efficiencies than those involving partially irreversible adsorption. Electrochemical regeneration of activated carbon is feasible at a laboratory scale as regeneration efficiencies up to 80% were achieved during electrochemical regeneration of phenol-loaded or natural organic matter-loaded activated carbons.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".