High-Temperature Conductivity Measurements for Industrial Applications. 2. H<sub>2</sub>SO<sub>4</sub>−Al<sub>2</sub>(SO<sub>4</sub>)<sub>3</sub> Solutions
Bibliographic record
Abstract
A new conductivity cell, developed previously, was employed from 15 to 250 °C, in an effort to investigate the inter-relation between the measured conductivities and the solution chemistry of high-temperature H 2 SO 4 −Al 2 (SO 4 ) 3 solutions. These electrolytes exist in the laterite leach slurry of the pressure acid leaching process. It was found that, at 250 °C, the effect of Al 2 (SO 4 ) 3 on conductivity decreases with increasing Al 2 (SO 4 ) 3 . This is in agreement with our previous findings that aluminum mostly forms Al(SO 4 ) + at low molalities, whereas 85% of aluminum is associated as Al 2 (SO 4 ) 3 0 at near-saturation molalities. At 250 °C and constant H 2 SO 4 molality, the solution conductivity drops with increasing Al 2 (SO 4 ) 3 molality. It is suggested that this drop is caused by a sharp decrease in ionic equivalent conductivities of H +, HSO 4 -, and Al(SO 4 ) + . This drop was found to be similar in nature to the drop when H 2 SO 4 is added at very low concentrations. A new unified correlation for ionic equivalent conductivity in terms of one-third power of individual ionic strength was found. Finally, a simple mixing rule was developed to calculate the ionic equivalent conductivities in H 2 SO 4 −Al 2 (SO 4 ) 3 solutions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".