Study of Formation of Bicarbonate Ions in CO<sub>2</sub>-Loaded Aqueous Single 1DMA2P and MDEA Tertiary Amines and Blended MEA–1DMA2P and MEA–MDEA Amines for Low Heat of Regeneration
Bibliographic record
Abstract
The formation of bicarbonate ions in an amine solution during CO 2 absorption results in lowering the heat duty for amine solvent regeneration in the CO 2 capture process because bicarbonate breakdown needs the lowest energy input to release CO 2 . In this study, bicarbonate formation was conducted for two mixed solvents consisting of tertiary amines (1DMA2P (1 M) or MDEA (1 M)) blended with MEA in order to determine both formation rate and capacity of bicarbonate ions as compared to MEA alone. The amines and concentrations used in the study were MEA (5 M), MEA–MDEA (5:1 molar ratio, 6 M total), and MEA–1DMA2P (5:1 molar ratio, 6 M total) at various CO 2 loadings. The formation of bicarbonate ions was evaluated using 13 C NMR technique at 293.15 K. The results show that for the single tertiary amine system higher concentrations of bicarbonate ions were formed for MDEA than for 1DMA2P for the same CO 2 loading. The results for the blended amine systems showed that bicarbonate ions were generated at CO 2 loadings lower with MEA alone than with MEA–1DMA2P generating bicarbonate ions at a CO 2 loading (0.34 mol CO 2 /mol amine) lower than that with MEA–MDEA (0.38 mol CO 2 /mol amine). Thus, as an additive in MEA, 1DMA2P has a better potential than does MDEA to generate bicarbonate ions at a leaner CO 2 loading with the attendant lowering of the regeneration energy.
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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".