Reduction Kinetics of Ilmenite Ore as an Oxygen Carrier for Pressurized Chemical Looping Combustion of Methane
Bibliographic record
Abstract
Reduction kinetics of ilmenite ore as an oxygen carrier for methane chemical looping combustion under elevated pressures was studied using a pressurized thermogravimetric analyzer (PTGA). The reduction phase of the experiments was carried out in a mixture of methane and nitrogen with carbon dioxide and/or steam to simulate an actual combustion environment. The oxidation phase of the experiments was carried out with air. Effects of the temperature (1123–1223 K), total pressure (0.6–1.6 MPa), methane partial pressure (0.23–0.64 MPa), and particle size (45–300 μm) were studied. Tests were also carried out to examine the effect of higher redox cycle numbers on the performance of ilmenite ore. The results showed that increasing the total pressure reduced the rate of conversion during ilmenite ore reduction, e.g., when the total pressure increased from 0.9 to 1.6 MPa, the reduction conversion rate decreased by 6–14% depending upon the reaction temperature because the negative effect of the pressure was less pronounced at higher temperatures. However, this negative effect can be compensated for by increasing the methane partial pressure. Increasing the methane pressure while maintaining the same methane/carbon dioxide ratio and total pressure increased the rate of reduction of ilmenite ore without affecting the oxygen carrying capacity until 1198 K. A kinetic model based on a phase-boundary-controlled mechanism with a contracting sphere was developed in the Arrhenius form using these experimental data. The model shows activation energies of 28.2 and 76.4 kJ mol –1 K –1 at 0.9 and 1.6 MPa, respectively, and it was able to reproduce the test results with a conversion ratio of up to 70%.
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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".