Exergy-based sustainability analysis of biogas upgrading using a hybrid solvent (imidazolium-based ionic liquid and aqueous monodiethanolamine)
Bibliographic record
Abstract
Energy may be generated in large quantities from fossil fuels, but this comes with environmental concerns. Thus, renewable resources like biogas, comprising carbon dioxide and methane, should be used alone or in combination with fossil fuels to mitigate the environmental footprints of energy generation systems. In this study, a new concept of hybrid solvent was presented, which combines 1-octyl-3-methylimidazolium tetrafluoroborate with aqueous mono diethanolamine for biogas upgrading process to provide high purity (≥ 99 wt%) and recovery (≥ 99 wt%) of biomethane. The process was simulated in ASPEN Plus® V.11. The thermodynamic framework was validated against experimental data, and rigorous regression was conducted to obtain binary parameters. To establish the efficacy of the suggested hybrid solvent, three scenarios were studied by altering the concentration of ionic liquid (5–20 wt%) linked with amine and compared to aqueous mono diethanolamine as the base case (50 wt%). The results showed that a hybrid solvent with 5 wt% 1-octyl-3-methylimidazolium tetrafluoroborate could increase CH4 purity to 99% (mol%). The hybrid solvent led to an energy saving of 64.94% compared to the amine-based system. Thermodynamic irreversibilities showed that 5 wt% 1-octyl-3-methylimidazolium tetrafluoroborate improved exergy efficiency by 54% over the amine-based procedure. Environmentally, the hybrid solvent system also achieved a higher capture rate (99%) and lower emissions (0.017 kW/kmol). Comparing the economic prospects, 5 wt% 1-octyl-3-methylimidazolium tetrafluoroborate saved 56% on total capital cost, making it competitive from an investment perspective.
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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 | 0.002 | 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".