Constant Thickness Porous Layer Model for Reaction between Gas and Dense Carbonaceous Materials
Bibliographic record
Abstract
Using oil-sands petroleum coke as the raw material and sulfur dioxide as the activating agent at 700 °C, the process of pore development in dense carbonaceous materials was studied. The time dependence of porosity was established from measured values of specific surface area (SSA), which could not be explained using conventional porous layer theories. Incorporating the Random Pore Model with measurements of particle size and porous layer thickness, a model was developed based on the existence of a porous layer of constant thickness. The model was found to accurately reproduce experimental time dependence of SSA. The results confirm a constant thickness of the porous layer for the activation conditions studied, which results from competing effects of carbon gasification reaction and penetration of the activating agent into the carbon particle interior. The model predicts a higher achievable SSA for a greater constant porous layer thickness, smaller initial particle size, and lower inorganic ash content. This model was found to be useful in predicting the maximum porous layer thickness of a dense material undergoing activation or gasification using only measured values of SSA, pore size distribution, and particle size as inputs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".