Optimizing degradation conditions of treatment of TATB explosive wastewater by γ-Fe<sub>2</sub>O<sub>3</sub> nanoparticles and UV synergistic degradation
Bibliographic record
Abstract
In this work, the effect of superparamagnetic γ-Fe 2 O 3 nanoparticles and ultraviolet light (UV) synergistic degradation on the treatment of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) explosive wastewater was studied. γ-Fe 2 O 3 nanoparticles were prepared by hydrolysis method and the degradation performance of TATB explosive wastewater was systematically studied with UV light assisted. The results showed that γ-Fe 2 O 3 magnetic nanoparticles have a low size distribution that ranged from 5 to 10 nm and possesses superparamagnetic properties. The optimized degradation condition was investigated and best degradation performance was obtained with the optimized conditions: the initial of pH = 3, UV illumination intensity (5 w/cm 2 ), reaction temperature (25 °C), initial total organic carbon concentration (4.025 mg/L) as well as reaction time (60 min). This work can offer a new idea to degrade the explosive wastewater.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".