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Record W1976292701 · doi:10.1021/ie0508280

Development of an Improved Chemical Model for the Estimation of CaSO<sub>4</sub> Solubilities in the HCl−CaCl<sub>2</sub>−H<sub>2</sub>O System up to 100 °C

2006· article· en· W1976292701 on OpenAlexafffund
Zhibao Li, George P. Demopoulos

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2006
Typearticle
Languageen
FieldChemical Engineering
TopicChemical and Physical Properties in Aqueous Solutions
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolubilityAnhydriteHemihydrateChemistrySolubility equilibriumThermodynamicsActivity coefficientWork (physics)Aqueous solutionMineralogyPhysical chemistryGypsumMaterials science

Abstract

fetched live from OpenAlex

A self-consistent chemical model based on a single set of model parameters for all three CaSO 4 modifications namely, dihydrate, hemihydrate, and anhydrite was developed and described in this work. The model was successfully tested for the estimation of CaSO 4 solubilities in concentrated (up to 20 m) mixed HCl−CaCl 2 −H 2 O systems up to 100 °C. The new model makes use of the OLI Systems software platform. Via regression of experimental solubility data, new Bromley−Zemaitis model parameters were determined for the Ca 2+ −SO 4 2- and Ca 2+ −HSO 4 - ion pairs. Moreover, for the first time, the new model incorporates data for hemihydrate modification (CaSO 4 · 1 / 2 H 2 O). After validation, the model was calibrated by determining new temperature-dependent parameters of the solubility product constants of the hemihydrate and anhydrite. With the aid of the newly developed model, the bell-shaped solubility curves for dihydrate and anhydrite, as a function of HCl concentration, were successfully explained, based on the bisulfate ion formation and ion-activity coefficient.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.068
GPT teacher head0.294
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2006
Admission routes2
Has abstractyes

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