Characterization of Wastes and Coproducts from the Coffee Industry for Composite Material Production
Bibliographic record
Abstract
This study characterizes and compares coffee chaff (CC) and spent coffee grounds (SCG), the two most useful coffee waste products, and evaluates their performance as fillers and/or reinforcing agents in polymer composites. The morphologies of the CC and the SCG were studied using a scanning electron microscope (SEM). Detailed compositional and elemental analyses of the samples were carried out using several techniques. The thermal stabilities of the two types of biomass were evaluated using thermogravimetric analysis (TGA). Infrared spectroscopy was performed to investigate the functional groups available on the surface of the biomass. It was found that the CC had higher thermal stability, lower fat content, and a denser fibrous structure than the SCG, making it potentially a more suitable material than the SCG for use as a reinforcing filler in polymer composites. To verify this potential, CC and SCG filled polypropylene composites were produced and evaluated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".