Stannous chloride—an effective reducing agent for the removal of selenium(IV) from acidic solution
Bibliographic record
Abstract
Abstract BACKGROUND: Selenium removal from aqueous solutions can be a significant industrial problem, particularly in the metallurgical industry. In order to evaluate new reducing agents for this application, the reduction of selenious acid (H 2 SeO 3 ) species with stannous ions (Sn 2+ ) from weakly acidic sulfate solutions containing 300 mg L −1 of selenium at 23 °C was studied. RESULTS: At initial pH values < 1.3 and molar ratio ≥ 2, less than 0.5 µg L −1 of selenium(IV) remained in solution after reduction. The reductive precipitation reaction started as soon as the stannous ions were added to the selenium‐bearing solution and was completed in less than 5 min. The reaction products, characterized using X‐ray diffraction, electron microscopy, particle and surface area measurements, X‐ray photoelectron spectroscopy and chemical analysis, were composed of approximately equal amounts of tin selenide and tin dioxide. In addition to tin selenide a minor amount of selenium(IV) was found to be removed via adsorption on the tin dioxide formed in situ . Tests with a complex industrial solution also resulted in full and stable selenium precipitation. CONCLUSION: Stannous ions were found to be very effective in removing selenious ions from synthetic and industrial solutions, producing very stable precipitates. Copyright © 2012 Society of Chemical Industry
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| 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 teacher head, 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".