Simulation study of deep eutectic solvent-based biogas upgrading process integrated with single mixed refrigerant biomethane liquefaction
Bibliographic record
Abstract
Deep eutectic solvents (DESs) comprise ChCl/urea, in combination with water, have been considered in removing acid gases (CO2 and H2S) from biogas. The evaluation of DES for biogas upgrading at relatively high pressure (i.e., >8.0 bar) has not been reported before. The aqueous DES performance has also not been analyzed compared to conventional amines-based solvent (MEA) and ionic liquid (IL). To the best of our knowledge, this is the first study that presents the integration of DES-based biogas upgrading with a mixed refrigerant liquefaction process to facilitate the safe and economical transportation of biomethane over long distances. The biogas considered in this study consisted of 60% CH4, 39% CO2, and 1% H2S. The aqueous ChCl/urea (70 wt%) results in biomethane with ≥99.0 wt% purity and ≥97.0 wt% recovery. Then, this biomethane was liquefied with ≥90% liquefaction rate. Based on the results obtained herein, overall capital, operating, and total annualized cost savings of 2.8%, 25.82%, and 14.26% were achieved using the 70% DES-based integrated process in comparison with the MEA-based integrated process. Whereas 1.41%, 16.85%, and 8.71% capital, operating, and total annualized costs could be saved in comparison with the IL (i.e., [Bmim][PF6])-based integrated process. It could be deduced that the overall cost of the biomethane value chain can be reduced using the proposed approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".