Enhanced Biodegradation and Fate of Hexahydro-1,3,5-Trinitro-1,3,5-Triazine (RDX) and Octahydro-1,3,5,7-Tetranitro-1,3,5,7-Tetrazocine (HMX) in Anaerobic Soil Slurry Bioprocess
Bibliographic record
Abstract
Native soil microbial populations and unadapted municipal anaerobic sludges were compared for nitramine explosive degradation in microcosm assays under various conditions. Microbial populations from an explosive-contaminated soil were only able to mineralize 12% hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) (at a concentration of 800 mg/kg slurry) or 4% octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) (at a concentration of 267 mg/kg slurry). In contrast, municipal anaerobic sludges were able to mineralize them to carbon dioxide, with efficiencies of up to 65%. Reduction of RDX and HMX into their corresponding nitroso-derivatives was notably faster than their mineralization. The biodegradation of HMX was typically delayed by the presence of RDX in the microcosm, confirming RDX is used as an electron acceptor preferentially to HMX. The laboratory-scale bioslurry reactor reproduced the results of the microcosm assays, yet with much higher RDX and HMX degradation rates. A radiolabel-based mass balance in the soil slurry indicated that, besides a significant mineralization to carbon dioxide, 25% and 31% of RDX and HMX, respectively, appeared as acetonitrile-extractable metabolites, while the remaining part was incorporated into biomass and irreversibly bound to the soil matrix. About 10% of the HMX derivatives were estimated to be chemically bound to the soil matrix, while for RDX the estimation was nil.
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.
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".