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Characterization of an atypical intermediate layer formed in Vanyukov furnaces during smelting of charges with a high content of technogenic materials

2025· article· en· W4411804390 on OpenAlexaff
L. V. Krupnov, R. А. Pakhomov, A. V. Kaverzin, Ya. I. Kosov, P. V. Malakhov

Bibliographic record

VenueIzvestiya Non-Ferrous Metallurgy · 2025
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsNickel Institute
Fundersnot available
KeywordsCharacterization (materials science)SmeltingLayer (electronics)MetallurgyWaste managementMaterials scienceEnvironmental scienceEnvironmental chemistryChemistryNanotechnologyEngineering

Abstract

fetched live from OpenAlex

The growing need for recycling, along with the depletion of high-grade ore concentrates, has led to the inclusion of previously accumulated technogenic materials — such as metallurgical slags, sludge from settling ponds of recirculating water systems, and similar waste – into the charge of primary smelting units. The share of such feedstock in the furnace charge now reaches approximately 25 %, which has resulted in serious technological disruptions to the stable operation of primary autogenous smelting units. In Vanyukov furnaces, this is manifested by the appearance – alongside the typical smelting products (matte and slag) – of a new atypical phase, the so-called intermediate layer. The formation of this layer leads to adverse effects, including the obstruction of flow paths from the furnace hearth to the slag and matte siphons, ultimately causing a complete shutdown of the unit. A sample of this abnormal product, collected from an industrial furnace during a period of process instability, was analyzed using differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and differential thermal analysis (DTA). These methods allowed the determination of temperature ranges corresponding to phase transformations of the components comprising the intermediate layer. The results obtained can be used to define optimal parameters for stable smelting operation and to develop technical solutions that prevent conditions favorable for the formation of refractory accretions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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