Development of Sinter-Resistant Core–Shell LaMn<sub><i>x</i></sub>Fe<sub>1–<i>x</i></sub>O<sub>3</sub>@mSiO<sub>2</sub> Oxygen Carriers for Chemical Looping Combustion
Bibliographic record
Abstract
This work investigates the possibility of using LaMn 0.7 Fe 0.3 O 3.15 @mSiO 2 as oxygen carriers for chemical looping combustion (CLC). CLC is a new combustion technique with inherent separation of CO 2 from atmospheric N 2 . LaMn 0.7 Fe 0.3 O 3.15 @mSiO 2 core–shell materials were prepared by coating a layer of mesostructured silica around the agglomerated perovskite particles. The oxygen carriers were characterized using different methods, such as X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), N 2 sorption, hydrogen temperature-programmed reduction (H 2 -TPR), and temperature-programmed desorption of oxygen (TPD-O 2 ). The reactivity and stability of the carrier materials were tested in a special reactor, allowing for short contact time between the fluidized carrier and the reactive gas [Chemical Reactor Engineering Centre (CREC) fluidized riser simulator]. Multiple reduction–oxidation cycles were performed. TEM images of the carriers showed that a perfect mesoporous silica layer was formed around samples with 4, 32, and 55 nm in thickness. The oxygen carriers having a core–shell structure showed higher reactivity and stability during 10 repeated redox cycles compared to the LaMn 0.7 Fe 0.3 O 3.15 core. This could be due to a protective role of the silica shell against sintering of the particles during repeated cycles under CLC conditions. The agglomeration of the particles, which occurred at high temperatures during CLC cycles, is more controllable in the core–shell-structured carriers, as confirmed by SEM images. XRD patterns confirmed that the crystal structure of all perovskites remained unchanged after multiple redox cycles. Methane conversion and partial conversion to CO 2 were observed to increase with the contact time between methane and the carrier. Indeed, more oxygen from the carrier surface, grain boundaries, and even from the bulk lattice was released to react with methane. Upon rising the contact time, less CO was formed, which is desirable for CLC application. Increasing the reaction temperature and methane partial pressure lead to enhanced conversions of CH 4 under CLC conditions.
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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".