The Physical Characteristic of Activated Carbon-Derived Sugarcane Bagasse/FeF <sub>3</sub> Composite
Bibliographic record
Abstract
Abstract Sugarcane bagasse is one of the major agricultures wastes that is enormously produced in agro-industrial complex in Indonesia. Considering the carbon content of this bio waste as well as the cost-effective in the preparation, sugarcane bagasse is an ideal candidate to fabricate an activated carbon that has a potential to be used in energy storage applications. This study presents a pyrolysis technique to fabricate activated carbon derived from sugarcane bagasse (SBAC) combined with FeF 3 composite (SBACF) after a complete activation process. SBAC was prepared by applying a two-step technique that is pyrolysis and subsequential chemical activation process. The SBACF composite was fabricated by applying planetary dry ball-milling technique. The BET measurement indicated a preferable physical characteristic of SBAC properties regarding the adsorption, including high specific surface area and pore volume. The specific surface area of the composite’s material has a large surface area of 1749-1940 m 2 g − 1 with total pore volume of 1.05 – 1.17 cm 3 g −1 . This high surface area of this composite properties is comparable to most of the activated carbon produced from another bio waste source, fulfilling the criteria often expected for commercial use. The results of SEM characterization show surface structure of the SBAC/FeF 3 composite is amorphous, characterized by a variety of particle shapes and sizes. The Raman spectroscopy examination of these composites indicates that the I D /I G ratio are 0.91 to 0.97. The low I D /I G ratio indicates that the carbon structure maintains a high level of order. This result suggested that the additional FeF 3 strategy could significantly enhance the physical properties of the SBAC which has potential to be used for energy storage application such as supercapacitor and battery electrode where a large surface area is one of the essential features.
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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".