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Record W2280978085

Sequestration of arsenic and molybdenum during the neutralization of uranium mill wastes: Key Lake mill, Saskatchewan, Canada

2015· article· en· W2280978085 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2015
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsnot available
Fundersnot available
KeywordsMillUraniumEnvironmental scienceMolybdenumUranium mineWaste managementMining engineeringGeologyMetallurgyArchaeologyGeographyEngineeringMaterials science
DOInot available

Abstract

fetched live from OpenAlex

The As- and Mo- bearing secondary mineral phases formed during the neutralization of uranium mill wastes were studied for a variety of ore blends including current and future ore sources at the Key Lake milling operation, northern Saskatchewan, Canada. A lab-scale plant model was employed to characterize secondary precipitates obtained during the mill waste neutralization process. Three scenarios of ore blends were processed through the lab-scale plant to produce mill waste solutions for neutralization before combination into final tailings. Slurry samples (n = 12) were collected from the secondary precipitates formed during the neutralization of mill wastes (raffinate) by precipitation with Ca(OH)2 (slaked lime) from pH 1.5 to 10.5. Synchrotron based X-ray absorption spectroscopy of mill and lab-scale plant precipitates showed arsenate adsorbed to ferrihydrite was the dominant As mineral phase regardless of pH or sample blend (53-77%), with fractional contributions from ferric arsenates, and adsorption to aluminum phases (AlOHSO4, As(OH)3 and hydrotalcite). Molybdate adsorbed to ferrihydrite was the dominant Mo mineral phase, regardless of pH or sample blend, with fractional contribution decreasing with increasing pH, and minor contributions from calcium molybdate, ferric molybdate and nickel molybdate. These results were used in geochemical modelling to predict the source terms for these mineral phases in tailings facilities. Sequestration of As and Mo in the model showed solubility was controlled by adsorption to both Fe and Al oxide surfaces as well as by direct precipitation with other dissolved constituents (Ni, Ca and SO4).The models developed pH profiles of mineral phase precipitation to explain the solubility of As, Mo, Fe, Al, Mg and Ni during sequestration from pH 1.5 to 10.5 that were consistent regardless of ore blend used in simulations. Since adsorption of anions to the surface of ferrihydrite has been shown to slow conversion to crystalline forms of Fe oxides (goethite and hematite) and sequestration of arsenate effectively controls As solubility at high pH (pH >10), As-bearing mineral phases are expected to be stable for thousands of years. With adsorption as well as direct precipitation considered, Mo phases though effectively sequestering below pH 8, became unstable and released Mo back into the tailings porewater (pH >10), as predicted by the thermodynamic model. Historical data obtained from as-discharged tailings as well as previously published U mill tailings studies agree with these findings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.143
Teacher spread0.136 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it