Carbon Dioxide Adsorption on Amine-Impregnated Mesoporous SBA-15 Sorbents: Experimental and Kinetics Study
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Bibliographic record
Abstract
In this work, an experimental and theoretical investigation was conducted on the adsorptive removal of CO 2 onto tetraethylenepentamine (TEPA) functionalized mesoporous SBA-15. The functionalization of SBA-15 silica with TEPA was achieved using a conventional wet impregnation technique. The structural properties of the mesoporous silica sorbents were characterized by nitrogen adsorption/desorption, SAXS, SEM, TEM, and FTIR techniques. The adsorption of CO 2 on the amine-impregnated sorbent was measured by thermogravimetric method over a CO 2 partial pressure range of 10–100 kPa and a temperature range of 30–100 °C under atmospheric pressure. The effects on CO 2 adsorption capacity of temperature, partial pressure of CO 2, amine loading, and moisture were evaluated. All the impregnated SBA-15 sorbents showed reversible CO 2 adsorption behaviors with fast adsorption kinetics. The CO 2 adsorption capacity measured at different temperatures suggests that the optimal adsorption temperature is 75 °C. The CO 2 uptake of the amine-impregnated sorbent increased significantly in the presence of moisture. SBA-15 containing 60 wt % TEPA showed the highest CO 2 adsorption capacity of 5.22 mmol/g in pure and humid CO 2 at 75 °C. Temperature swing adsorption/desorption cycles were also explored using simulated flue gas in both dry and humid conditions, and it was found that CO 2 uptake after ten cycles was within 90% of CO 2 uptake of the first cycle. Different adsorption kinetic models have also been investigated to analyze the experimental data of CO 2 uptake. The model was validated with the experimental results of isothermal adsorption measurements of CO 2 on SBA-15/TEPA. It has been found that Fractional Order kinetic model ( Chem. Eng. J. 2011, 173, 72) is very good over the entire adsorption region of the study with a maximum average absolute deviation between experimental CO 2 uptake and that calculated from the model of about 2.42%.
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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 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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