Trace Metals in Groundwater & Vadose Zone Calcite: In Situ Containment & Stabilization of 90Strontium & Other Divalent Metals & Radionuclides at Arid West DOE Sites
Bibliographic record
Abstract
Radionuclide and metal contaminants such as 90Sr are present beneath U.S. Department of Energy (DOE) lands in both the groundwater (e.g., 100-N area at Hanford, WA) and vadose zone (e.g., Idaho Nuclear Technology and Engineering Center (INTEC) at the Idaho National Engineering and Environmental Laboratory). In situ containment and stabilization of these contaminants is a cost-effective treatment strategy. However, implementing in situ containment and stabilization approaches requires definition of the mechanisms that control contaminant sequestration. We are investigating the in situ immobilization of radionuclides or contaminant metals (e.g., 90Sr) by their facilitated co-precipitation with calcium carbonate in groundwater and vadose zone systems. Our facilitated approach, shown schematically in Figure 1, relies upon the hydrolysis of introduced urea to cause the acceleration of calcium carbonate precipitation (and trace metal co-precipitation) by increasing pH and alkalinity. Subsurface urea hydrolysis is catalyzed by the urease enzyme, which may be either introduced with the urea or produced in situ by ubiquitous subsurface urea hydrolyzing microorganisms. Because the precipitation process tends to be irreversible and many western aquifers are saturated with respect to calcite, the co-precipitated metals and radionuclides will be effectively removed from the aqueous phase over the long-term. Another advantage of the ureolysis approach is that the ammonium ions produced by the reaction can exchange with radionuclides sorbed to subsurface minerals, thereby enhancing the availability of the radionuclides for re-capture in a more stable solid phase (co-precipitation rather than adsorption).
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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) | 0.001 | 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".