Valorization of tree leaves waste using microwave‐assisted hydrothermal carbonization process
Bibliographic record
Abstract
Abstract Fallen leaves of landscape trees, as an emerging biomass waste, were valorized using conventional hydrothermal carbonization (HC) and microwave‐assisted hydrothermal carbonization (MHC) pretreatments, and were comparatively characterized for physicochemical properties and thermal degradation kinetics. The results show that MHC is superior to conventional HC operation, because at 200℃, the MHC process not only gives a higher hydrochar yield (45.09 vs. 39.47 wt%) with significantly reduced energy consumption (0.63 vs. 2.74 MJ g −1 ), but also is more effective in removing K and Si. For isoconversional kinetic analysis, the FWO method provides better results than the KAS method as the latter failed to fit the tree leaves sample ( R 2 < 0.9). The thermal degradation kinetics at high temperatures (>400℃) showed that the hydrochar obtained from the MHC process has a lower average activation energy of ~190 MJ kg −1 than the conventional HC process (~260 MJ kg −1 ). This study reveals the potential for valorization of the landscape tree wastes via the MHC process.
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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".