<scp>CO<sub>2</sub></scp> absorption kinetics and equilibrium solubility measurements in potassium salts of renewable amino acids from plant‐ and animal‐protein
Bibliographic record
Abstract
Abstract Aqueous solutions containing alkaline salts of natural amino acids, such as those from protein in plant seeds or high protein animal‐based waste, are green CO 2 ‐separation solvents. In the present work, potassium salts of nine such amino acids were chosen for an in‐depth study: alanine, arginine, aspartic acid, glutamic acid, glycine, leucine, proline, serine, and valine. The kinetics of CO 2 absorption in aqueous solutions of these salts was studied using a stirred cell. From the measurements of the absorption rate at different salt concentrations (molarity 0.1 and higher), CO 2 partial pressures (5–25 kPa), and temperatures (298–308 K), values of the reaction order, rate constant, and activation energy were determined. Additionally, the liquid‐side mass transfer coefficient (0.005 cm/s) was also found. Potassium salts of proline, glycine, and arginine were most reactive and, hence, were chosen for equilibrium study. The loading capacity of these salts was measured at 308 K in a vapour–liquid equilibrium setup at near‐ambient pressure. On the contrary, the other chosen acids were comparatively less reactive with CO 2 .
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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".