Characterization of natural organic matter in Wyoming-type bentonites irradiated at varied moisture levels
Bibliographic record
Abstract
Wyoming-type bentonite clay (MX-80; Wyoming, USA) will be used a deep geological repository (DGR) for the long-term storage of used nuclear fuel in Canada. The natural organic matter (NOM) found in bentonite may serve as a microbial nutrient source and potentially compromise the performance of the used fuel containers. Previous investigations indicate MX-80 NOM is present in low concentrations and has undergone extensive diagenetic alteration, though limited knowledge is available regarding NOM chemistry under simulated DGR conditions. Of particular concern is the possibility for gamma-radiation to alter NOM dissolution and reactivity due to the presence of reactive species generated by water radiolysis in Wyoming-type bentonites. In this study, NOM chemistry was investigated using complementary molecular-level techniques following exposure to a total gamma-radiation dose of 100 kGy (1.08 kGy/h for 93 hours) at varied moisture levels (20%, 40%, 60% and 80%) and room temperature. Treated samples exhibited relatively low total organic carbon concentrations (0.074-0.232%), with no evidence of any major changes in total, organic, and inorganic carbon concentrations. Solid-state 13C NMR spectroscopy detected no changes in solid-phase NOM chemistry after irradiation. Solubilization of NOM increased significantly with radiation exposure at 80% moisture, suggesting higher levels of water saturation may enhance dissolved organic matter (DOM) production. Solution-state 1H nuclear magnetic resonance (NMR), and UV-Vis analyses did not identify any significant differences in DOM composition. More sensitive, targeted compound analysis revealed significant decreases in total n-alkanol concentration at lower moisture content levels (20% and 40%). Several individual compound concentrations also differed significantly at the nanogram-level, including n-octacosanol and several n-alkanoic acids at elevated moisture levels (60% and 80%). These findings suggest the majority of NOM in MX-80 remains chemically stable under the anticipated initial conditions of the proposed DGR.
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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 | 0.000 |
| 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 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".