Extraction of Zinc and Chromium(III) and Its Application to Treatment of Alloy Electroplating Wastewater
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Bibliographic record
Abstract
Abstract Extraction of Zn and Cr(III) with solvents containing (1) DEHPA, di-2-ethylhexyl phosphoric acid, (2) PC-88A, 2-ethylhexylphosphonic acid mono-2-ethylhexyl ester, (3) Cyanex 272, bis(2,4,4-trimethylpentyl)phosphinic acid, and (4) Cyanex 302, bis(2,4,4-trimethylpentyl)thiophosphinic acid, was studied with a view to separately recovering the two metals from alloy electroplating wastewater. All solvents extracted Zn well. Extraction of Cr(III) required a higher pH and Cr(III) hydroxide precipitation placed an upper limit on the pH that could be used, which in turn limited the extraction percentage. Among the four extractants, DEHPA performed the best, achieving close to 100% extraction at 0.1 M. The extracted Cr(III) could not be completely stripped (back-extracted). By using ammoniated DEHPA, both the precipitation and incomplete stripping problems were averted. The different performances of the DEHPA and ammoniated DEHPA solvents were explained in terms of the different extracted Cr(III) species and the slow kinetics of reactions involving ligand displacement of the Cr(III) species. This explanation was supported by stoichiometric and UV–visible spectral data. A flow sheet based on Zn extraction with DEHPA and Cr(III) extraction with ammoniated DEHPA was developed for treatment of Zn–Cr(III) alloy electroplating wastewater. The flow sheet was tested in an automated mixer–settler solvent extraction system. The treated wastewater contained <0.1 mg l−1 Zn and <1 mg l−1 Cr(III), and the recovered metals were in good purity. Keywords: ZincChromium(III)ExtractionRecoveryElectroplating wastewaterWaste treatment Acknowledgments This work was supported by a grant from the Research Grants Council of Hong Kong (Project No. 9040539), which is appreciated. Thanks are due to Cytec Canada Inc. for supplies of Cyanex 272 and Cyanex 302.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 it