Uranium, Cesium, and Mercury Leaching and Recovery from Cemented Radioactive Wastes in Sulfuric Acid and Iodide Media
Bibliographic record
Abstract
The Canadian Nuclear Laboratories (CNL) is developing a long-term management strategy for its existing inventory of solid radioactive cemented wastes, which contain uranium, mercury, fission products, and a number of minor elements. The composition of the cemented radioactive waste poses significant impediments to the extraction and recovery of uranium using conventional technology. The goal of this research was to develop an innovative method for uranium, mercury and cesium recovery from surrogate radioactive cemented waste (SRCW). Leaching using sulfuric acid and saline media significantly improves the solubilization of the key elements from the SRCW. Increasing the NaCl concentration from 0.5 to 4 M increases the mercury solubilization from 82% to 96%. The sodium chloride forms a soluble mercury complex when mercury is present as HgO or metallic mercury but not with HgS that is found in 60 °C cured SRCW. Several leaching experiments were done using a sulfuric acid solution with KI to leach SRCW cured at 60 °C and/or aged for 30 months. Solubilization yields are above 97% for Cs and 98% for U and Hg. Leaching using sulfuric acid and KI improves the solubilization of Hg by oxidation of Hg0, as well as HgS, and form a mercury tetraiodide complex. Hg and Cs were selectively removed from the leachate prior to uranium recovery. It was found that U recovery from sulfuric leachate in iodide media using the resin Lewatit TP260 is very efficient. Considering these results, a process including effluent recirculation was applied. Improvements of solubilization due to the recycling of chemical reagents were observed during effluent recirculation.
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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 | 0.001 |
| 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) | 0.001 | 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".