A Novel Technique for Hydrogen Production from Hog-Manure in Supercritical Partial Oxidation (SCWPO)
Bibliographic record
Abstract
In this study, the catalytic hydrogen production from hog manure using supercritical water partial oxidation was investigated in a batch reactor at a temperature of 500 °C, and pressure of 28 MPa using several metallic catalysts.Hog manure was characterized by a total and soluble chemical oxygen demand (TCOD, SCOD) of 57000 and 28000 mg/L, total and volatile suspended solids (TSS, VSS) of 25000, 19000, and ammonia of 2400 mg/L, respectively.The order of H 2 production was the following: Pd/AC > Ru/Al 2 O 3 > Ru/AC > AC > NaOH.The order of COD reduction efficiency was as follows: NaOH > Ru/AC > AC > Ru/Al 2 O 3 > Pd/AC.The behaviour of the volatile fatty acids (VFA's), ethanol, methanol, ammonia, H 2 S, and Sulfate was investigated experimentally and discussed.A 35 % reduction in the H 2 and CH 4 yields was observed in the sequential gasification partial oxidation (oxidant at an 80 % of theoretical requirement) experiments compared to the gasification experiments (catalyst only).Moreover, this reduction in gas yields was coincided with a 45 % reduction in the liquid effluent chemical oxygen demand (COD), 60 % reduction of the ammonia concentration in the liquid effluent, and 20 % reduction in the H 2 S concentration in the effluent gas.
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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) | 0.000 | 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".