Counter-current acid leaching process for copper azole treated wood waste
Bibliographic record
Abstract
This study explores the performance of a counter-current leaching process (CCLP) for copper extraction from copper azole treated wood waste for recycling of wood and copper. The leaching process uses three acid leaching steps with 0.1 M H2SO4 at 75degrees C and 15% slurry density followed by three rinses with water. Copper is recovered from the leachate using electrodeposition at 5 amperes (A) for 75 min. Ten counter-current remediation cycles were completed achieving > or = 94% copper extraction from the wood during the 10 cycles; 80-90% of the copper was recovered from the extract solution by electrodeposition. The counter-current leaching process reduced acid consumption by 86% and effluent discharge volume was 12 times lower compared with the same process without use of counter-current leaching. However, the reuse of leachates from one leaching step to another released dissolved organic carbon and caused its build-up in the early cycles.
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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 | 0.001 |
| 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".