Process intensification in methane generation during anaerobic digestion of Napier grass using supercritical carbon dioxide combined with acid hydrolysis pre‐treatment
Bibliographic record
Abstract
Napier grass was subjected to pre‐treatment techniques such as thermal acid hydrolysis and supercritical carbon dioxide (scCO2) and combination of both. Anaerobic batch digestion was conducted using activated sludge mixed microbial consortia for 15 days. Parameters influencing scCO2 hydrolysis were optimized. scCO2‐acid and acid pre‐treatment gave maximum production of biogas, which was 2.5 times higher than that without pre‐treatment. The optimum condition were 100 °C and 99 atm pressure, supercritical carbon dioxide, 0.6 % w/v sulphuric acid, time 1 h. The highest methane yield of the pre‐treated samples were 118 ml CH4/g total solids added. The production of hydrolysate and volatile fatty acids during pre‐treatment ensures increase in chemical oxygen demand levels which promotes methane productivity. These results indicated that scCO2 with acid hydrolysis pre‐treatment could be an effective method for increasing biodegradability and improving methane yield of Napier grass.
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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".