TGA and kinetic modelling of Co, Mn and Cu oxides for chemical looping gasification (CLG)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Oxygen carriers for biomass gasification are capable of absorbing oxygen from air and desorbing it in the gasifier. Based on thermodynamic equilibrium, copper, manganese, and cobalt oxides have the highest oxygen release capacities among the different oxygen carriers. These oxygen carriers were deposited on alumina via incipient wetness impregnation. The weight loss of the CuO–Cu 2 O carrier, as measured in a thermo‐gravimetric analyzer, was 10 % while it was 7 % for the Co 3 O 4 –CoO couple and only 3 % for the Mn 2 O 3 –Mn 3 O 4 couple. The optimum operating temperature for the CuO oxygen carrier was 100 °C higher compared to the other two at 950 °C. A modified nuclei growth model (MNG) characterizes the weight loss/gain during the reduction‐oxidation cycles. The reduction rate is 3 times higher at 875 °C compared to 825 °C while the oxidation rate decreases more than 10 times. The CuO carrier surface area decreased by 70 %, while it was 30 % and 60 % in the Co 3 O 4 and Mn 2 O 3 carriers, respectively. Cobalt has a lower tendency to sinter at high temperature compared to either copper or manganese and has a higher oxygen transport capacity and oxidation‐reduction rates. Therefore, despite its higher cost and toxicity, it might be considered as a potential oxygen carrier especially for solid fuel gasification.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it