Comparative Study on Ni/γ-Al<sub>2</sub>O<sub>3</sub> Prepared via Ultrasonic Irradiation and Impregnation Approaches as an Oxygen Carrier in Chemical Looping Combustion
Bibliographic record
Abstract
With the recent advancement of the chemical looping combustion (CLC) industry, the development of materials with high stability, high oxidation and reduction rate, and high oxygen transport capacity (OTC) has become a research hotspot. In this paper, the behavior of nickel oxide (NiO) as an oxygen carrier (OC) has been analyzed using thermogravimetric analysis. The influences of the preparation methods and Ni composition have been evaluated to develop Ni-based carriers with high reduction and oxidation rates over 10 redox cycles without changes in the chemical and structural properties. It has been observed that the carriers prepared by the ultrasound irradiation method showed excellent stability and higher reduction and oxidation rate (less than 1–3 min) during multiple redox cycles. However, their OTC values were lower than those of impregnated carriers. It was found that, in the ultrasound irradiation method, the 15NA (15 wt % Ni loading supported with gamma alumina) OC exhibited the highest OTC (3.17%) while 5NA (5 wt % nickel loading supported with gamma alumina) exhibited the lowest OTC (1.34%). A similar trend was observed for the impregnated OC, where 15NA exhibited the highest OTC value (3.67%), whereas 5NA exhibited the lowest OTC value (1.38%). Overall, the carriers prepared via the impregnation method possessed a high value of OTC at approximately 3.67% while the carriers prepared by ultrasound irradiation possessed an OTC value of 3.17%. In terms of physicochemical properties, the carriers prepared using the ultrasound irradiation approach possessed comparatively lower oxidation and reduction temperatures, smaller particle size, higher specific surface area, and more uniform metal distribution on the support. These findings suggested that the Ni-based OC prepared by ultrasound irradiation is a good candidate for CLC reactions.
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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".