Thermogravimetric Study on Devolatilization Kinetics of Chinalco Anodes during Baking
Bibliographic record
Abstract
The production of aluminum requires the use of carbon anodes which are manufactured from coke, pitch, and recycled butts and anodes. Pitch acts as a binder. Green anodes are produced by mixing all these ingredients and then forming them in a compactor. The final step is the baking of green anodes, which determines the final anode properties. During baking, volatiles evolve from the pitch which carbonizes and binds the particulate matter. Anode quality greatly influences the performance of electrolytic cells and has an impact on carbon consumption, energy use, green house gas emissions, and cost.In this project, the effects of the baking conditions on some of the anode properties (air permeability, air and CO2 reactivities) were studied, and the devolatilization kinetics was determined for different cases. The results indicate that the lower heating rates and higher baking temperatures improve the above properties. In this article, the experimental work and the methodology for the determination of the kinetic expressions for devolatilization are described, and the results are presented. The position of volatile evolution in the baking furnace can be determined via these expressions, and this could be effectively used in controlling the volatile combustion to improve the furnace performance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".