Advances in principal factors influencing carbon dioxide adsorption on zeolites
Bibliographic record
Abstract
We report the advances in the principal structural and experimental factors that might influence the carbon dioxide (CO2) adsorption on natural and synthetic zeolites. The CO2 adsorption is principally govern by the inclusion of exchangeable cations (countercations) within the cavities of zeolites, which induce basicity and an electric field, two key parameters for CO2 adsorption. More specifically, these two parameters vary with diverse factors including the nature, distribution and number of exchangeable cations. The structure of framework also determines CO2 adsorption on zeolites by influencing the basicity and electric field in their cavities. In fact, the basicity and electric field usually vary inversely with the Si/Al ratio. Furthermore, the CO2 adsorption might be limited by the size of pores within zeolites and by the carbonates formation during the CO2 chemisorption. The polarity of molecules adsorbed on zeolites represents a very important factor that influences their interaction with the electric field. The adsorbates that have the most great quadrupole moment such as the CO2, might interact strongly with the electric field of zeolites and this favors their adsorption. The pressure, temperature and presence of water seem to be the most important experimental conditions that influence the adsorption of CO2. The CO2 adsorption increases with the gas phase pressure and decreases with the rise of temperature. The presence of water significantly decreases adsorption capacity of cationic zeolites by decreasing strength and heterogeneity of the electric field and by favoring the formation of bicarbonates. The optimization of the zeolites structural characteristics and the experimental conditions might enhance substantially their CO2 adsorption capacity and thereby might give rise to the excellent adsorbents that may be used to capturing the industrial emissions of CO2.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".