Hydrothermal carbonization of sawdust for hydrochar production to prepare solid fuels
Bibliographic record
Abstract
Abstract Hydrothermal carbonization (HTC) of sawdust for producing hydrochar was optimized using response surface methodology (RSM). After optimization, the combustion behaviour and other relevant fuel properties of hydrochar that was obtained at the optimized conditions were studied. Additionally, the aqueous phase obtained at the optimized conditions was recycled as the reaction medium for producing hydrochar and the influence of the aqueous phase recycling on the hydrochar yield and properties was evaluated. The results indicated that the highest hydrochar yield of 84.23 wt.% under the predicted optimum conditions of temperature of 162.23°C, 2.51 h, feedstock loading of 10.71 wt.%, and catalyst loading of 7.99 wt.%. Furthermore, it was found that the use of recycled aqueous phase as the reaction medium led to an increase in the hydrochar yield, higher heating value (HHV), and energy yield, and difference in combustion behaviour was minor. Overall, this study filled the gap in HTC literature regarding the effect of catalyst on hydrochar production and provided a practical solution to treat the aqueous phase.
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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".