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Record W2015999137 · doi:10.1179/174328508x290849

Liquidus relationships of calcium ferrite and ferrous calcium silicate slag in continuous copper converting

2008· article· en· W2015999137 on OpenAlexaff
Florian Kongoli, Ian McBow, Akira Yazawa, Yoichi Takeda, K. Yamaguchi, R. Budd, S. Llubani

Bibliographic record

VenueMineral Processing and Extractive Metallurgy Transactions of the Institutions of Mining and Metallurgy Section C · 2008
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsLiquidusCopperMetallurgySlag (welding)FerrousSilicateCalcium silicateSmeltingFerrite (magnet)MineralogyPhase diagramCalciumMaterials scienceChemistryPhase (matter)Alloy

Abstract

fetched live from OpenAlex

While calcium ferrite slags have been successfully used in continuous copper converting for the past 30 years, ferrous calcium silicate slag was proposed ∼8 years ago as an additional alternative for copper smelting. Although these slags are normal extensions of each other, their phase relations have not been completely clarified. In this paper, liquidus relations for both slags have been quantified in some regions of common composition. Existing experimental data are reviewed and discussed in relation to the solidification procedure. An original physical model is then used to predict diagrams of the liquidus surface of both slags. It is shown that the ternary liquidus diagrams normally used for FeOx–SiO2–CaO system are not suitable for industrial slags. The new model diagrams of Fe/CaO versus SiO2 and Fe/SiO2 versus CaO, as well as Fe/CaO versus temperature and Fe/SiO2 versus temperature are proven much more convenient for ferrite and ferrous calcium silicate slags. Based on these diagrams, the effect of SiO2 and CaO on the melting temperature is quantified. The effect of Cu2O is also quantified through the model. Fe/CaO versus Cu2O and Fe/SiO2 versus CaO relationships at various copper contents are predicted. The results show good agreement with the experimental data. It is also shown that, in the presence of liquid copper, Cu2O is dissolved in the slag to an extent depending on the oxidation degree of the system, which may lower the liquidus temperature. Discussions are presented taking into account plant observations, and important conclusions are drawn for copper smelting and converting.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.058
GPT teacher head0.259
Teacher spread0.202 · 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 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

Citations11
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueMineral Processing and Extractive Metallurgy Transactions of the Institutions of Mining and Metallurgy Section CSame topicMetallurgical Processes and ThermodynamicsFrench-language works237,207