Impact of the Solidification Rate on the Chemical Composition of Frozen Cryolite Bath
Bibliographic record
Abstract
Solidification of cryolite (Na3AlF6)-based bath takes place at different rates along the sideledge, and around alumina rafts and new anodes. The solidification rate has a significant impact on the structure and the chemical composition that determine the thermal conductivity and thus the thickness of sideledge, or the duration of the existence of the temporary frozen bath layers in other cases. Unfortunately, samples that can be collected in industrial cells are formed under unknown, spatially and temporally varying conditions. For this reason, frozen bath samples were created under different heat flux conditions in a well-controlled laboratory environment using the so-called cold finger technique. The samples were analyzed by X-ray Diffractometer (XRD) and Scanning Electron Microscope (SEM) in Back Scattering (BS) mode in order to obtain spatial distribution of chemical composition. Results were correlated with structural analysis. XRD confirmed our earlier hypothesis of recrystallization of cryolite to chiolite under medium heat flux regime. Lower α-alumina, and higher γ-alumina content in the samples obtained with very high heating rate suggest that fast cooling reduces α–γ conversion. In accordance with the expectation, SEM-BS revealed significant variation of the Na/Al ratio in the transient sample.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 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".