Effect of magnetic field on the ammonia‐based CO<sub>2</sub> absorption process
Bibliographic record
Abstract
Abstract The performance of ammonia‐based CO2 absorption under static magnetic field conditions was discussed. The removal efficiency of CO2, CO2 load, and absorption capacities were studied using a bubble reactor system. The CO2 removal efficiencies, CO2 load, and absorption capacity under static magnetic field conditions were calculated at four kinds of different operating conditions, which included CO2 concentration in flue gas, gas flow rate, concentrations of aqueous ammonia, and reaction temperature. The results indicated that the initial removal efficiency of CO2 can reach 98.5 % by 10 wt% ammonia solution under static magnetic field conditions, and it is 7 % higher than that under the no magnetic field conditions. The effect of magnetic field on CO2 load and absorption capacity is more obvious when the inlet CO2 concentration in the simulated flue gas is 10 vol%, the CO2 load increases 11.7 % from 1.45 mol/L to 1.62 mol/L, and the absorption capacity rises from 0.668 kgCO2/kgNH3 to 0.738 kgCO2/kgNH3. Compared with the absorption of CO2 under static magnetic field conditions and no magnetic field conditions, the absorption process of CO2 is enhanced by the magnetic field, and the removal efficiency of CO2, CO2 load and absorption capacity show superior performance.
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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".