CO<sub>2</sub> capture efficiency in post‐combustion using MWNT‐PAA in a packed bed column
Bibliographic record
Abstract
The adsorption capacity of polyaspartamide (PAA) and multi‐wall carbon nanotubes with polyaspartamide (MWNT‐PAA) was investigated through a packed bed column with the flowing of flue gas composed of 15 % CO2, 5 % O2 and the balance N2. The adsorption performed at 25 °C, 110 kPa and inlet gas flow rate of 60 mL/min resulted in high CO2 adsorption capacity of 5.70 and 10.20 mmol‐CO2/g for PAA and MWNT‐PAA, respectively. The adsorption kinetics was very high, so 7 min were enough for the effluent gas to reach the breakthrough after saturation. The consistency of adsorbents in recurring regeneration was successful through a continuous TSA system of 10 cycle adsorption‐desorption with temperatures of 25–100 °C. The evaluation of heat through differential scanning calorimetry (DSC) resulted in exothermic adsorption with heat release of 45.14 kJ/mol and 124.38 kJ/mol for PAA and MWNT‐PAA, respectively. The heat release was found favourable to promote the desorption as the temperature could rise after adsorption. This is an advantage for energy efficiency, as it depicts the potential of energy recovery. Thus, both adsorbent PAA and MWNT‐PAA were demonstrated to be promising for CO2 adsorption capture in post‐combustion.
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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) | 0.001 | 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 | 0.001 |
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".