Effect of NaCl, MgCl<sub>2</sub>, FeCl<sub>2</sub>, FeCl<sub>3</sub>, and AlCl<sub>3</sub> on Solubility of CaSO<sub>4</sub> Phases in Aqueous HCl or HCl + CaCl<sub>2</sub> Solutions at 298 to 353 K
Bibliographic record
Abstract
The effect of various chloride salts (NaCl, MgCl 2, FeCl 2, FeCl 3, and AlCl 3 ) on the solubility of three CaSO 4 modifications, namely, calcium sulfate dihydrate, hemihydrate, and anhydrite in aqueous HCl or HCl + CaCl 2 solutions up to 353 K was investigated. The concentration ranges (at ambient temperature) studied are up to 6 mol·dm -3 for HCl; 1.5 mol·dm -3 for CaCl 2; 3 mol·dm -3 for NaCl, MgCl 2, and FeCl 2; and 2 mol·dm -3 for AlCl 3 and FeCl 3 . The solubility of CaSO 4 phases in all cases investigated was found to increase with temperature. In 0.5 mol·dm -3 HCl, the effect of metal chlorides on the solubility of dihydrate was a complex one with solubility increasing up to a certain metal chloride concentration and then decreasing in higher range of metal chloride concentration. On the other hand at higher HCl concentration (3 mol·dm -3 ), the solubility of dihydrate and anhydrite was found to consistently decrease with increasing metal chloride concentration. The only exception was NaCl, which was found not to influence to a significant degree the solubility of dihydrate in HCl solutions. The solubility of dihydrate in pure AlCl 3 solution smoothly passes through a maximum value in the (0 to 1.5) mol·dm -3 AlCl 3 concentration range. The presence of CaCl 2 causes the solubility of both dihydrate and hemihydrate to decrease due to common ion effect.
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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 | 0.000 | 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) | 0.001 | 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".