Mass-transfer studies of solid-base catalyst-aided CO2 absorption and solid-acid catalyst-aided CO2 desorption for CO2 capture in a pilot plant using aqueous solutions of MEA and blends of MEA-MDEA and BEA-AMP
Bibliographic record
Abstract
Abstract Mass-transfer studies of catalyst-aided CO2 absorption and desorption were performed in a full-cycle, bench-scale pilot plant to improve CO2 absorption using 5M MEA, 5M MEA-2M MDEA and 2M BEA-2M AMP. A solid-base catalyst, K/MgO, and an acid catalyst, HZSM-5, were used to facilitate absorption and desorption, respectively. Absorption and desorption mass-transfer performance was presented in terms of the overall mass-transfer coefficient of the gas side (KGav) and liquid side (KLav), respectively. For non-catalytic runs, the highest KGaV and KLaV were 0.086 Kmolm3.kPa.hr and 0.785 1hr for 2M BEA-2M AMP solvent. The results showed 38.7% KGav and 23.6% KLav increase for 2M BEA-2M AMP with only HZSM-5 catalyst in desorber and a 95% KGaV and 45% KLaV increase for both K/MgO catalyst and HZSM-5 catalyst. This was attributed to the role of K/MgO in bonding loosely with CO2 and making it available for the amine reaction.
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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) | 0.001 | 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 | 0.001 | 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".