Pilot Plant Studies of the CO<sub>2</sub> Capture Performance of Aqueous MEA and Mixed MEA/MDEA Solvents at the University of Regina CO<sub>2</sub> Capture Technology Development Plant and the Boundary Dam CO<sub>2</sub> Capture Demonstration Plant
Bibliographic record
Abstract
Evaluations of the benefits of using a mixed MEA/MDEA solvent for CO 2 capture in terms of the heat requirement for solvent regeneration, lean and rich loadings, CO 2 production, and solvent stability were performed by comparing the performance of aqueous 5 kmol/m 3 MEA with that of an aqueous 4:1 molar ratio MEA/MDEA blend of 5 kmol/m 3 total amine concentration as a function of the operating time. The tests were performed using two pilot CO 2 capture plants of the International Test Centre for CO 2 Capture (ITC), which provided two different sources and compositions of flue gas. The University of Regina CO 2 plant (UR unit) processes flue gas from the combustion of natural gas while the Boundary Dam CO 2 plant (BD unit) processes flue gas from a coal-fired electric power station. The results show that a huge heat-duty reduction can be achieved by using a mixed MEA/MDEA solution instead of a single MEA solution in an industrial environment of a CO 2 capture plant. However, this benefit is dependent on whether the chemical stability of the solvent can be maintained.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".