Organic transformation and kinetics in preheating and oxidation stages during supercritical water oxidation treatment of oily sludge
Bibliographic record
Abstract
The treatment of oily sludge presents significant environmental challenges due to its high organic pollutant content and the risk of soil and groundwater contamination. This study investigates the two-stage preheating-supercritical water oxidation (SCWO) process in treating oily sludge, focusing on the reaction mechanisms and organic component transfer across solid, liquid, and gas phases. During preheating, desorption, volatilization, and thermal decomposition of oil and solids drive organic migration; kinetic analysis reveals the limited reaction rates of preheating, leading to incomplete chemical oxygen demand (COD) removal and partial desorption at this stage. In the SCWO stage, rapid oil-solid desorption equilibrium is observed, with a reaction order of 2.11 ± 0.016 relative to sludge concentration and 0.82 ± 0.02 for oxygen concentration, underscoring oxidant effects in complex feedstock reactions. Preheating facilitates long-chain alkane cracking, ring-opening polymerization of cyclic siloxanes, and amine removal, while SCWO degrades macromolecular esters, opens cyclic structures, and enables nitrogen transfer. These insights improve process understanding, enhance treatment efficiency, and mitigate environmental impacts.
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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".