Performance of Three Chemical Models on the High-Temperature Aqueous Al<sub>2</sub>(SO<sub>4</sub>)<sub>3</sub>−MgSO<sub>4</sub>−H<sub>2</sub>SO<sub>4</sub>−H<sub>2</sub>O System
Bibliographic record
Abstract
This work involves chemical modeling of concentrated aqueous sulfate solutions during an industrial process: pressure acid leaching of laterites at high temperature of interest to the metals and minerals industries. Equilibrium constants of Al and Mg complexes were estimated or extrapolated. Three activity coefficient models were used: the B-dot equation, the Pitzer model, and the Bromley−Zemaitis model. The B-dot and Pitzer models were implemented with EQ3/6 software (version 7.0), and the Bromley−Zemaitis model was implemented through OLI-Systems software (version 6.2). Original databases in all cases were modified in order to include the equilibrium constants of Al and Mg species. Calculated values are in good agreement with the experimental solubility data for MgSO 4 −H 2 SO 4 −H 2 O and Al 2 (SO 4 )−H 2 SO 4 −H 2 O ternary systems with all three models. However, significant differences were found in the predicted speciation and pH in both ternary and quaternary systems because of the different correlations and assumptions employed in the models. A self-consistent model and new thermodynamic data for high-temperature aqueous processes are highly recommended to handle concentrated solutions of interest to the process industry.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".