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Record W4383909039 · doi:10.3390/pr11072065

Kinetic Analysis of Boron and Phosphorus Removal from Si-Fe Alloy by CaO-Al2O3-SiO2-Na2O Slag

2023· article· en· W4383909039 on OpenAlexafffund
Golam Ismot Ara Taposhe, Leili Tafaghodi Khajavi

Bibliographic record

VenueProcesses · 2023
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcMaster UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSlag (welding)AlloyBoronMaterials scienceMass transferMetallurgySiliconMass transfer coefficientPhosphorusRefining (metallurgy)Phase (matter)Analytical Chemistry (journal)ChemistryChromatography

Abstract

fetched live from OpenAlex

A hybrid process of slag and solvent refining was used to remove boron and phosphorus from silicon. Quaternary slag of CaO-Al2O3-SiO2-Na2O was employed to remove boron (B) and phosphorus (P) from Si-20 wt% Fe alloy at 1300 °C. A slag-to-metal ratio of one was used at different reaction times. The mass transfer coefficient of B and P in the slag and alloy phases was calculated to determine the rate-limiting step. The mass transfer coefficients of B in the alloy and slag phases were 6.6 × 10−7 ms−1 and 2.8 × 10−7 ms−1, respectively. The mass transfer coefficients of P in the alloy and slag phases were determined to be 7.5 × 10−8 ms−1 and 3.5 × 10−7 ms−1, respectively. The rate-limiting stage of the slag–alloy reaction kinetics was mass transport in the liquid slag for B and mass transport in the alloy phase for P.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.008
GPT teacher head0.210
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 source (direct Gemma or distilled Codex), 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
Published2023
Admission routes2
Has abstractyes

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