Preparation of microporous activated carbon from <i>Aegle marmelos</i> fruit shell by KOH activation
Bibliographic record
Abstract
Abstract Activated carbon (AC) is well‐known for its unique properties; hence, the search for new precursors and the investigation of new methods for the preparation of AC is still drawing attention of many researchers. In the present work, microporous AC was prepared from Aegle marmelos fruit shell (AMFS) by potassium hydroxide (KOH) activation. The effect of process parameters such as impregnation ratio, carbonisation temperature and holding time on porous characteristics was investigated. The porous characteristics of prepared AC samples were analysed by N2 adsorption–desorption isotherms, and it was found that the isotherms obtained resemble typical microporous solids (Type‐I). The Langmuir surface area and total pore volume of the sample prepared at optimum conditions were found to be 937 m2/g and 0.33 cm3/g, respectively. The contribution of micropores to the porous characteristics of the prepared AC is very much appreciable, and about 97% of the total surface area and pore volume is attained by micropores. Pore size distribution (PSD) by Dubinin–Astakhov (DA) and micro‐pore (MP) methods confirmed the presence of micropores to a great extent with insignificant mesoporosity. © 2013 Canadian Society for Chemical Engineering
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".