Physical Property Evolution of the Anode Mixture during the Baking Process
Bibliographic record
Abstract
The Hall-Héroult process uses prebaked carbon anodes as electrodes. The anode's quality plays a crucial role in the efficiency of the aluminium production process. During the baking process, the anode undergoes complex physicochemical transformations. Thus, the production of high-quality anodes depends, among others, on the efficient control of their baking process. This paper aims to investigate the evolution of some physical properties of the anode paste mixture during the baking process. These properties include the mass loss fraction, real and apparent densities, the ratio of apparent volume, the permeability, and porosities. For this purpose, experiments consisting of thermogravimetric analysis, dilatometry, air permeability, and helium-pycnometric measurements were carried out. The anode permeability at high temperatures was linked to the air permeability through a permeability correlator due to experimental limitations. Moreover, the real density at high temperatures was estimated by combining real densities of the coal tar pitch and coke aggregates. Different porosities, such as the open porosity and the closed porosity related to the pitch binder, were estimated by taking the permeability at high temperatures into account. In this context, the effect of the permeability correlator, which was introduced to link the permeability at high temperatures to the air permeability, was investigated through a sensitivity analysis. These results allow an estimation of the shrinking index, a new variable introduced to reflect the baking level of the anode mixture, which is linked to the volatile that is released in both open and closed pores. Afterwards, the pore pressure inside closed pores in the coal tar pitch was estimated. The obtained results highlight some new insights related to the baking process of the anode mixture. Moreover, they pave the way for better modeling of the thermo-chemo-mechanical behavior of anodes at high temperatures.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".