Synthesis gas production with simultaneous CO<sub>2</sub> capturing and consuming: Application of chemical looping combustion by employing Fe45‐Al<sub>2</sub>O<sub>3</sub> and Mn40/Mg–ZrO<sub>2</sub> oxygen carriers
Bibliographic record
Abstract
In this study, thermal coupling of chemical looping combustion (CLC) and dry reforming of methane (DR) via employment of Fe45‐Al2O3 and Mn40/Mg–ZrO2 oxygen carriers (OCs) were investigated. The main aim of this configuration (CLC‐DR) is the prevention of large CO2 emissions to the atmosphere by CLC and simultaneous consumption of the captured gas to synthesis gas through a DR reaction. For this purpose, a steady state one‐dimensional heterogeneous catalytic reaction model is applied to analyze the performance and applicability of the proposed CLC‐DR configuration using both OCs. Simulation results indicate that for both OCs, combustion efficiency reaches 1 in the fuel reactor (FR) of CLC‐DR. Additionally, results illustrate that CH4 conversion in the DR side of CLC‐DR reaches 0.7235 and 0.7213 with Fe45‐Al2O3 and Mn40/Mg–ZrO2 OCs respectively. Results show that application of CLC‐DR employing Fe45‐Al2O3 and Mn40/Mg–ZrO2 OCs produces 8611 and 8585 kmol h−1 of synthesis gas, respectively. Synthesis gases with H2/CO mole ratios of 0.9519 and 0.9612 are achieved using Fe45‐Al2O3 and Mn40/Mg–ZrO2 OCs respectively. In addition, results demonstrate that by increasing the feed temperature of CLC‐DR from 800 to 1000 K, synthesis gas production reaches 11 210 and 11 340 kmol h−1 when using Fe45‐Al2O3 and Mn40/Mg–ZrO2, respectively. Finally, thermal and molar behaviours of CLC‐DR configuration indicate that it is applicable, and by utilization of this configuration 547.8 tonne day−1 can be captured and converted to synthesis gas.
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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) | 0.000 | 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 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".