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Record W1996751362 · doi:10.1021/ie049535h

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

2005· article· en· W1996751362 on OpenAlexafffund
Jesús Casas, Vladimiros G. Papangelakis, Haixia Liu

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2005
Typearticle
Languageen
FieldChemical Engineering
TopicChemical and Physical Properties in Aqueous Solutions
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversidad de ChileUniversity of Toronto
KeywordsTernary operationAqueous solutionThermodynamicsActivity coefficientSolubilityChemistryTernary numeral systemEquilibrium constantLeaching (pedology)Inorganic chemistryPhysical chemistryGeologyComputer sciencePhysicsSoil science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.005
Science and technology studies0.0020.003
Scholarly communication0.0010.002
Open science0.0060.003
Research integrity0.0060.019
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.038
GPT teacher head0.243
Teacher spread0.206 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations23
Published2005
Admission routes2
Has abstractyes

Explore more

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