Reduction Kinetics of La Modified NiO/La-γAl<sub>2</sub>O<sub>3</sub> Oxygen Carrier for Chemical-Looping Combustion
Bibliographic record
Abstract
La modified Ni/La-γAl 2 O 3 oxygen carrier reduction kinetics is investigated using temperature programmed reduction (TPR) and a parameter nonlinear regression analysis. TPR profile study and XRD analysis of the completely oxidized samples show that NiO is the prevalent phase of the oxygen carrier. Hydrogen pulse chemisorption demonstrates that the nickel crystallite sizes remain unchanged over repeated reduction/oxidation cycles. A nucleation and nuclei growth model and an unreacted shrinking core model are developed based on the oxygen carrier characterization. Model discrimination is conducted based on SSQ, goodness of fittings, and minimum cross-correlation coefficients. On the basis of these statistical indicators, it is established that the random nucleation model describes the reduction of the oxygen carrier adequately. The estimated value of the activation energy for the La modified Ni/La-γAl 2 O 3 sample is found to be 73.4 ± 2.6 kJ/mol, with this being significantly lower than the activation energy for the unmodified Ni/γAl 2 O 3 sample (104.5 ± 3 kJ/mol). This suggests that the unmodified oxygen carrier requires higher activation energy, with this reflecting an increased difficulty of nickel phase reduction due to a strong interaction between nickel and alumina. The nucleation model, as established using TPR, is successfully validated for the reduction cycle using methane as a fuel gas in a CREC minifluidized riser simulator reactor operating under the expected operating conditions for large industrial scale chemical-looping combustion (CLC) units.
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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".