Supercritical Water Gasification of Lactose as a Model Compound for Valorization of Dairy Industry Effluents
Bibliographic record
Abstract
The dairy industry effluents, including whey waste and milk-based residues, are enriched in lactose and minor amounts of glucose that could potentially be converted to biofuels and biochemicals. Lactose was used in this work as a model compound of dairy effluents for gasification in supercritical water using a continuous flow tubular reactor. Four parameters impacting supercritical water gasification were studied, namely, temperature (550–700 °C), residence time (30–75 s), feed concentration (4–10 wt %), and catalyst concentration (0.2–0.8 wt %). The best total gas yields, carbon gasification efficiency, H 2 yields, and other major gases (CO 2 and CH 4 ) were obtained at 700 °C using a feed concentration of 4 wt % lactose and a residence time of 60 s at fixed pressure of 25 MPa. Furthermore, catalytic lactose gasification involving 0.8 wt % Na 2 CO 3 resulted in maximum H 2 yield (22.4 mol/mol) compared to those obtained by 0.8 wt % K 2 CO 3 (21.5 mol/mol) and noncatalytic gasification (16 mol/mol).
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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".