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Record W6957952964 · doi:10.60692/8bb4r-kd602

Zircon dissociation in air plasma through a low power transferred arc plasma torch

2015· article· en· W6957952964 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2015
Typearticle
Languageen
FieldEngineering
TopicRecycling and utilization of industrial and municipal waste in materials production
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsZirconDissociation (chemistry)PlasmaMicrostructureArgonAnalytical Chemistry (journal)Oxide

Abstract

fetched live from OpenAlex

Thermal plasma dissociation offers a convenient and attractive route to prepare zirconium oxide from zircon mineral. Transferred and non-transferred arc plasma torches have been used to study zircon dissociation. The major thrust has been to accomplish complete dissociation and make the process simpler and cost effective. Technologically, this has been attempted in argon-fired plasma reactors using higher electrical power. The present work reports a cost effective low power transferred arc plasma (TAP) processing method for dissociating zircon by using air as the plasma forming gas. Phase composition and microstructure formation of the dissociated zircon were examined by XRD and SEM with EDX. Experimental results showed that the torch input power and processing time strongly influenced the dissociation percentage as well as the microstructure formation. Further, obtained results revealed that the air plasma medium significantly improved the percentage of zircon dissociation rather than argon plasma medium at 10 and 15 kW power levels. The air plasma gives complete zircon dissociation at 10 kW power with 5 min of processing.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

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 communication0.0000.001
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 head0.049
GPT teacher head0.221
Teacher spread0.172 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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