Confirmation of the retention of 226Ra in U-mine tailings by barite
Bibliographic record
Abstract
• The McClean Lake plant's tailings are rich in 226 Ra. • The distribution of 226 Ra activity among the minerals was observed. • The experimental data are confirmed by thermodynamic modelling. • 226 Ra is mainly retained in barite as a solid solution. • This solid solution is an effective trap for the long-term. Uranium ore from the Athabasca basin in Saskatchewan Canada, particularly from the McClean Lake and Cigar Lake deposits, is extremely rich in uranium (U): 2 to 20–25 % U 3 O 8 . The ore is also rich in many elements considered to be Constituents of Potential Concern (COPC) for the environment, including arsenic (As), selenium (Se), nickel (Ni), molybdenum (Mo), lead (Pb), cobalt (Co) and radium-226 ( 226 Ra). Following uranium extraction, residual materials (tailings) containing these elements in partially immobilized forms are placed in the McClean Lake plant Tailings Management Facility (TMF). Uranium tailings are sulfate-rich low-level radioactive waste containing 226 Ra, with activities of up to 3000 Bq/g. Barium chloride (BaCl 2 ) is added to precipitate 226 Ra in barite as a solid-solution. Following this neutralisation treatment, 226 Ra in the tailings is generally considered as sequestered in barite and sorbed onto ferrihydrite. To assess the subsequent stability of 226 Ra in the tailings, an extensive study of its retention potential was performed. Characterisations incude assessment of tailings pore water and solids chemistry, tailings mineralogy, cation exchange capacity measurement, scanning electron microscopy and energy-dispersive x-ray spectroscopy (SEM/EDS), and alpha-autoradiography analyses supplemented with thermodynamic modelling. This work confirms that barite is the main 226 Ra binding-phase, in agreement with the 226 Ra concentration measured in the porewater (6 Bq/L) resulting from a coprecipitation reaction. A (Ba,Ra)SO 4 solid-solution regulates the average 226 Ra concentration now and over the long term, through a distribution coefficient which is subject to a gradual shift towards a recrystallisation equilibrium. Recrystallisation causes an increase in the long-term concentration of 226 Ra in the tailing water to 10 Bq/L. The work, conducted to assess the management strategy of the tailings, allowed us to ensure that the tailings have no significant effects on the downstream environment over the long term.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".