Eggshell as a Carbon Dioxide Sorbent: Kinetics of the Calcination and Carbonation Reactions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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 (CO2) 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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it