Hydrothermal Carbonization of Spent Coffee Grounds for Producing Solid Fuel
Bibliographic record
Abstract
Spent coffee grounds (SCG) are industrial biowaste resulting from the coffee-brewing process, and they are often underutilized and end up in landfills, thereby leading to the emission of toxic gases and environmental damage. Hydrothermal carbonization (HTC) is an attractive approach to valorize wet biomass such as SCG to valuable bioproducts (i.e., hydrochar). Thus, in this work, the HTC of SCG was carried out in a 500 L stainless steel vessel at 150, 170, 190, 210, and 230 °C for 30 min, 60 min, 90 min, and 120 min and a feedstock to water weight ratio of 1:5, 1:10, and 1:15, and the use of the resulting hydrochar as a solid fuel was evaluated. The results showed that a high energy recovery (83.93%) and HHV (23.54 MJ/kg) of hydrochar was obtained at moderate conditions (150 °C, 30 min, and feedstock to water weight ratio of 1:5) when compared with conventional approaches such as torrefaction. Following this, the surface morphology, functionality, and combustion behavior of this hydrochar were characterized by SEM, FTIR, and TGA, respectively. In short, it can be concluded that HTC is an effective approach for producing solid fuel from SCG and the resulting hydrochar has the potential to be applied either in domestic heating or large-scale co-firing plants.
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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".