Production and characterization of lignocellulosic biomass-derived activated carbon
Bibliographic record
Abstract
The goal of this work is to establish the technical feasibility of producing activated carbon from pulp mill sludges. KOH chemical activation of four lignocellulosic biomass materials, two sludges from pulp mills, one sludge for a linerboard mill, and cow manure, were investigated experimentally, with a focus on the effects of KOH/biomass ratio (1/1, 1.5/1 and 2/1), activation temperature (400-600 °C) and activation time (1 to 2 h) on the development of porosity. The activation products were characterized for their physical and chemical properties using a surface area analyzer, scanning electron microscopy and Fourier transform infrared spectroscopy. Experiments were carried out to establish the effectiveness of the lignocellulosic biomass-derived activated carbon in removing methylene blue (MB), a surrogate of large organic molecules. The results show that the activated carbon are highly porous with specific surface area greater than 500 m²/g. The yield of activated carbon was greater than the percent of fixed carbon in the dry sludge, suggesting that the activation process was able to capture a substantial amount of carbon from the organic matter in the sludge. While 400 °C was too low, 600 °C was high enough to sustain a substantial rate of activation for linerboard sludge. The KOH/biomass ratio, activation temperature and time all play important roles in pore development and yield control, allowing optimization of the activation process. MB adsorption followed a Langmuir isotherm for all four activated carbon, although the adsorption capacity of NK-primary sludge-derived activated carbon was considerably lower than the rest, consistent with its lower specific surface area.
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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 | 0.001 |
| 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) | 0.000 | 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".