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Record W2086759578 · doi:10.1179/174328508x370048

Preparation of TiC powders and coatings by electrodeoxidation of solid TiO<sub>2</sub>in molten salts

2009· article· en· W2086759578 on OpenAlexfundno aff
X. Y. Yan, Mark I. Pownceby, Mark Cooksey, Marshall R. Lanyon

Bibliographic record

VenueMineral Processing and Extractive Metallurgy Transactions of the Institutions of Mining and Metallurgy Section C · 2009
Typearticle
Languageen
FieldChemical Engineering
TopicMolten salt chemistry and electrochemical processes
Canadian institutionsnot available
FundersRio TintoCommonwealth Scientific and Industrial Research Organisation
KeywordsElectrolysisMaterials scienceEutectic systemTitaniumGraphiteMolten saltMetalMetallurgyChemical engineeringCathodeElectrolyteAlloyElectrodeChemistry

Abstract

fetched live from OpenAlex

Porous TiC nanoparticles have been synthesised from sintered pellets comprising a powder mixture of TiO2 and graphite by electrodeoxidation in molten CaCl2–NaCl eutectic. Electrolysis was conducted at 850°C in argon at an applied constant voltage of 3·1 V. The formation of TiC from the oxides/C mixture occurred at less cathodic potentials than those for electrodeoxidation of TiO2 to titanium metal. No titanium metal was observed during electrolysis, as confirmed by XRD. These findings were consistent with the thermodynamic predictions. It was found that CaTiO3 was formed during electrolysis and all the titanium oxides disappeared after 4 h electrolysis in a eutectic CaCl2–NaCl melt at 850°C, leaving CaTiO3/C/TiC mixtures behind at the cathode. It was also found that the formed CaTiO3 was electrodeoxidised to form TiC by prolonged electrolysis. The present results further demonstrated that an adhesive layer of Ti0·55C0·45 was formed on graphite substrates by electrodeoxidation of TiO2 on the substrates.

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 score0.052
Threshold uncertainty score0.673

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 communication0.0000.000
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 head0.012
GPT teacher head0.267
Teacher spread0.255 · 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

Citations19
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueMineral Processing and Extractive Metallurgy Transactions of the Institutions of Mining and Metallurgy Section CSame topicMolten salt chemistry and electrochemical processesFrench-language works237,207