Comparative studies of co-conversion of waste activated sludge and lignocellulosic wastes through hydrothermal liquefaction
Bibliographic record
Abstract
The effects of feedstock type on hydrothermal liquefaction were explored through the co-conversion of waste activated sludge and various lignocellulosic biomass sources, including birchwood sawdust, cornstalk, and waste newspaper. This investigation aimed to produce bio-oil under consistent conditions at 310 °C and a 10-min reaction time, with subsequent comparison to results obtained using single feedstocks. The co-feeding of sludge with cornstalk and sawdust demonstrated the highest bio-oil yields at 34.2 % and 33.7 % wt%, respectively. The comprehensive characterization of the bio-oil products revealed that feedstock type influenced elemental composition and, consequently, the higher heating value of the bio-oils. Bio-oils derived from co-feeds exhibited a significant presence of nitrogenous compounds, esters, and fatty acids in contrast to the high percentage of phenolic compounds found in bio-oils from single feedstocks. Furthermore, these co-feed bio-oils displayed lower molecular weights, higher quantities of low boiling point compounds, increased volatile matter content, and reduced fixed carbon content compared to bio-oils produced from single feedstocks. • Co-conversion of wastewater sludge and lignocellulosic biomass was investigated. • A maximum bio-oil yield in the range of 33–34 wt% was obtained using mixed feedstock. • Co-conversion resulted in higher quality bio-oils compared to single feedstock. • By-products of the process can be used for energy generation or as fertilizers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".