Eggshell as a Carbon Dioxide Sorbent: Kinetics of the Calcination and Carbonation Reactions
Bibliographic record
Abstract
This study investigates the calcination and carbonation reaction kinetics of eggshell. Nonisothermal (dynamic) thermogravimetry using multiple heating rates was conducted to study the calcination process. On the other hand, isothermal conditions were applied to report on the carbonation process in a carbon dioxide (CO 2 ) atmosphere. Several model-based and isoconversional kinetic methods were used to evaluate the calcination kinetic parameters. The methods include the Friedman, Coats and Redfern, modified Coats and Redfern, Kissinger, Flynn–Wall–Ozawa, and Kissinger–Akahira–Sunose methods. Furthermore, an analytical solution method was developed to evaluate the kinetic parameters and to predict the experimental conversion. The carbonation reaction was modeled with a modified form of the shrinking core model. Both the rapid surface reaction-controlled and the slow diffusion-limited stages of carbonation were analyzed. The results showed that the kinetic parameters obtained with the various methods are in good agreement with each other, and the computed average activation energies for calcination are in the range of 209–221 kJ mol –1 . It is also observed that the activation energy of the calcination reaction varies with the extent of conversion, suggesting that the mechanism is not a single-step type. In addition, the results showed that the carbonation reaction mechanism of the eggshell is controlled by the combination of surface reaction and product layer diffusion. An activation energy of 49.6 kJ mol –1 was obtained for the chemical reaction stage and 72.5 kJ mol –1 for the diffusion-limited stage for carbonation temperatures from 500 to 700 °C.
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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) | 0.001 | 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".