Physicochemical Characterization Of Biochar Obtained From CoffeeHusk: A Circular Economy Approach
Bibliographic record
Abstract
This work presents the physical and chemical characterization of biochar obtained from the controlled calcination of coffee husks.Coffee husk, a residue from the pulping process in coffee production, was dried, pulverized, and sieved to obtain a fine powder.Thermal analysis (TGA-DTA-DSC) was performed under nitrogen and air atmospheres to determine the material's thermal decomposition and calcination temperatures.X-ray fluorescence (XRF) revealed the elemental composition, showing the presence of C, O, K, S, Ca, P, and Si.X-ray diffraction (XRD) analysis demonstrated significant structural changes due to calcination.The untreated coffee husk showed an amorphous structure with peaks corresponding to cellulose and hemicellulose.After calcination at 550°C, these organic phases disappeared, and new crystalline phases, including CaO, SiO₂, graphite, and Fe₂O₃, were identified.The formation of these phases suggests improved structural stability and potential benefits for soil applications.Decomposition stages were observed, with residue percentages of 7.6% in air and 25.8% in nitrogen at 1000°C.Based on these results, calcination at four temperatures (160°C, 330°C, 430°C, and 550°C) was selected, followed by analysis using infrared spectroscopy (FTIR) and scanning electron microscopy (SEM).Structural changes, including the disappearance of C=O bands and increased intensity of C-O bonds, indicated the potential to produce biochar at temperatures above 330°C.These findings suggest that coffee husk biochar could improve soil nutrient bioavailability, supporting its use in a circular economy framework.
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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 | 0.001 | 0.001 |
| 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".