Advanced treatment of biologically pretreated coal chemical industry wastewater using the catalytic ozonation process combined with a gas-liquid-solid internal circulating fluidized bed reactor
Bibliographic record
Abstract
Abstract This paper investigated the performance of the combined system of catalytic ozonation and the gas-liquid-solid internal circulating fluidized bed reactor for the advanced treatment of biologically pretreated coal chemical industry wastewater (CCIW). The results indicated that with ozonation alone for 60min, the removal efficiency of chemical oxygen demand (COD) could reach 34%. The introduction of activated carbon, pumice, γ-Al2O3 carriers improved the removal performance of COD, and the removal efficiency was increased by 8.6%, 4.2%, 2%, respectively. Supported with Mn, the catalytic performance of activated carbon and γ-Al2O3 were improved significantly with COD removal efficiencies of 46.5% and 41.3%, respectively; however, the promotion effect of pumice supported with Mn was insignificant. Activated carbon supported with Mn had the best catalytic performance. The catalytic ozonation combined system of MnOX/activated carbon could keep ozone concentration at a lower level in the liquid phase, and promote the transfer of ozone from the gas phase to the liquid phase to improve ozonation efficiency.
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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) | 0.001 | 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".