Banana-peel derived activated carbon for microwave absorption at X-band frequency
Bibliographic record
Abstract
The rapid advancement in information technology, communication, and electronic devices elevates the need to develop suitable materials for microwave absorption (MA) which should have the properties of an ideal microwave absorber. Porous activated carbon from agricultural wastes has piqued the interest of MA researchers due to their distinct properties such as good specific surface area, high dielectric loss, good electrical conductivity, and low density. Herein banana peel activated carbon was prepared by activating banana peel precursor with KOH and carbonizing at different temperatures. The difference in the porous structure with varying carbonization temperature was visible in the FESEM image, validated by BET analysis. The Banana Peel Activated carbon samples exhibited good microwave absorption performance, with BP-AC700 displaying a minimum Reflection Loss (RL) of −40.62 dB at 10.72 GHz & 3.0 mm thickness. In addition, the obtained effective absorption bandwidth of 3.5 GHz spanned through the X band frequency. This exceptional microwave absorption was attained due to the sample's good conductive loss and Porous favourable morphology. This study inspires the development of future facile functional agricultural waste-derived microwave absorbers.
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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) | 0.002 | 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".