Postcombustion CO<sub>2</sub> capture using N‐(3‐trimethoxysilylpropyl)diethylenetriamine‐grafted solid adsorbent
Bibliographic record
Abstract
Abstract In this work, the performance of N‐(3‐trimethoxysilylpropyl)diethylenetriamine (DAEAPTS)‐grafted mesoporous SBA‐15 adsorbent for postcombustion carbon capture was studied. Wet grafting technique was adopted to functionalize SBA‐15 surface. The adsorption of CO2 on the amine‐grafted sorbent was measured by the thermogravimetric method over a CO2 partial pressure range of 0–90 kPa and a temperature range of 25–105°C under atmospheric pressure. The optimal amine loaded SBA‐15 adsorbent containing 40 wt% DAEAPTS exhibited capture capacity up to 2.3 mmol/g under simulated gas conditions (88.2% CO2/N2) at 75°C. The CO2 adsorption–desorption kinetics of the grafted sorbents were found to be sufficiently fast in both dry and humid CO2 streams and it was observed that the grafted adsorbent achieved 75% of the total capacity in 5 min of adsorption time in dry 8.8% CO2/N2 and in less than 3.5 min in humid 8.8% CO2/N2. It was also observed that 95% of the total desorption occurred in less than 7 min at 150°C under pure N2. The grafted sorbents showed good reversibility and multicycle stability and the drop in capacity after 100 cycles in dry and humid 8.8% CO2/N2 streams was around 7.09% and 11.65%, respectively.
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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) | 0.000 | 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) | 0.001 | 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".