Powerful Concentration of Rhodium in Plating Wastewater Using Homogeneous Liquid–Liquid Extraction (HoLLE) and Study for Scale-up
Bibliographic record
Abstract
A powerful technique for the concentration of rhodium (Rh) in plating wastewater was developed. The technique entails complexing Rh with 1-(2-pyridylazo)-2-naphthol (PAN) followed by homogeneous liquid–liquid extraction (HoLLE) with Zonyl FSA. The optimum HoLLE conditions were determined as follows: [ethanol]T = 30.0 vol.%, pH = 4.00, and Rh:PAN = 1:5. Under these optimum conditions, 88.1% of Rh was extracted into the sedimented liquid phase. After phase separation, the volume ratio [aqueous phase (Va) /sedimented liquid phase (Vs)] of Va and Vs was 1000 (50 mL → 0.050 mL). We then applied the new method to wastewater generated by the plating industry. The phase separation was satisfactorily achieved when the volume was scaled up to 1000 mL of the actual wastewater; 84.7% of Rh was extracted into the sedimented liquid phase. After phase separation, Va/Vs was 588 (1000 mL - 1.70 mL).
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".