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Record W2016541909 · doi:10.1002/cjce.5450800518

A Mathematic Model for Direct Causticization of Na<sub>2</sub>CO<sub>3</sub> with TiO<sub>2</sub> in a Semi‐batch Reactor

2002· article· en· W2016541909 on OpenAlexvenueno aff
Le Zeng, Adriaan R. P. van Heiningen

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2002
Typearticle
Languageen
FieldMaterials Science
TopicCrystallization and Solubility Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFluidized bedSodium carbonateYield (engineering)DiffusionBatch reactorMaterials scienceCarbonateBatch processingConstant (computer programming)ThermodynamicsChemical engineeringChemistrySodiumMetallurgyEngineeringComputer sciencePhysicsCatalysis

Abstract

fetched live from OpenAlex

Abstract A mathematic model was developed for direct causticization of sodium carbonate with titanium dioxide in a semi‐batch reactor. The model predictions of the titanate yield and pentatitanate yield showed a reasonable agreement with the experimental data from a pilot‐scale fluidized bed operating in semi‐batch mode. The rate constant of the present model was generally consistent with those obtained from the small‐scale batch experiments in the literature. A new rate constant considering carbonate conversion to pentatitanate was introduced. All the results provided support that the solid‐state direct causticization of sodium carbonate with titanium dioxide in a semi‐batch fluidized bed follows the shrinking‐core diffusion model.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.183
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.207
Teacher spread0.189 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2002
Admission routes1
Has abstractyes

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