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Record W4401582054 · doi:10.3390/met14080910

Influence of Top Slag Containing TiO2 and VOx on Hot Metal Pre-Desulfurization

2024· article· en· W4401582054 on OpenAlexaff
Biwen Yang, Bo Song, Liang Chen, Honghong Sun, Derek O. Northwood, Kristian E. Waters, Hao Ma

Bibliographic record

VenueMetals · 2024
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcGill UniversityUniversity of Windsor
Fundersnot available
KeywordsFlue-gas desulfurizationSlag (welding)MetallurgyMetalMaterials scienceEnvironmental scienceWaste managementEngineering

Abstract

fetched live from OpenAlex

The desulfurization capacity of top slag in the process of pre-desulfurization of hot metal containing vanadium and titanium was researched. The top slag system of CaO-SiO2-MgO-Al2O3-TiO2-VOx that was formed by blast furnace slag and a CaO desulfurization agent reduced the sulfur in hot metal from 0.08 wt.% to 0.02 wt.%. It was found that the resulfurization of the slag happened in the later periods of the desulfurization process. The vanadium–titanium oxides were both acidic in the desulfurization slag. TiO2 and VOx reacted with the basic oxides to form CaTiO3 and MgV2O4 at 1623 K, which reduced free CaO and was not conducive to top slag desulfurization. The results of calculation showed that the top slag desulfurization accounted for 15% of the total desulfurization. Using the ionic and molecule coexistence theory of slag structure, it is shown that the desulfurization efficiency could be enhanced by adjusting both the amount of desulfurization agent and the composition of the blast furnace slag before pre-desulfurization.

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 score0.002
Threshold uncertainty score0.005

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 head0.230
Teacher spread0.222 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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