Sorption and Stability of the Polycyclic Nitramine Explosive CL‐20 in Soil
Bibliographic record
Abstract
The polycyclic nitramine CL-20 (2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane) is being considered for use as a munition, but its environmental fate and impact are unknown. The present study consisted of two main elements. First, sorption-desorption data were measured with soils and minerals to evaluate the respective contributions of organic matter and minerals to CL-20 immobilization. Second, since CL-20 hydrolyzes at a pH of >7, the effect of sorption on CL-20 degradation was examined in alkaline soils. Sorption-desorption isotherms measured using five slightly acidic soils (5.1 < pH < 6.9) containing various amounts of total organic carbon (TOC) revealed a nonlinear sorption that increased with TOC [K(d) (0.33% TOC) = 2.4 L kg(-1); K(d) (20% TOC) = 311 L kg(-1)]. Sorption to minerals (Fe(2)O(3), silica, kaolinite, montmorillonite, illite) was very low (0 < K(d) < 0.6 L kg(-1)), suggesting that mineral phases do not contribute significantly to CL-20 sorption. Degradation of CL-20 in sterile soils having different pH values increased as follows: sandy agricultural topsoil from Varennes, QC, Canada (VT) (pH = 5.6; K(d) = 15 L kg(-1); 8% loss) < clay soil from St. Sulpice, QC, Canada (CSS) (pH = 8.1; K(d) = 1 L kg(-1); 82% loss) < sandy soil provided by Agriculture Canada (SAC) (pH = 8.1, K(d) = approximately 0 L kg(-1); 100% loss). The faster degradation in SAC soil compared with CSS soil was attributed to the absence of sorption in the former. In summary, CL-20 is highly immobilized by soils rich in organic matter. Although sorption retards abiotic degradation, CL-20 still decomposes in soils where pH is >7.5, suggesting that it will not persist in even slightly alkaline soils.
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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 | 0.001 | 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".