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Record W3088625204 · doi:10.1149/09801.0011ecst

The Thermal-Oxidation Behavior of Pristine and Doped Magnéli Phase Titanium Oxides

2020· article· en· W3088625204 on OpenAlexaff
Joseph T. English, David P. Wilkinson

Bibliographic record

VenueECS Transactions · 2020
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceDopingActivation energyThermogravimetric analysisArrhenius equationPassivationThermal stabilityTitaniumKineticsThermal oxidationPhase (matter)DiffusionChemical engineeringElectrochemistryAnalytical Chemistry (journal)Inorganic chemistryPhysical chemistryThermodynamicsChemistryNanotechnologySiliconElectrodeMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Magnéli phase titanium oxides (Ti n O 2 n –1 , 4 ≤ n ≤ 10) are promising alternatives to carbon-based materials in aqueous electrochemical technologies, but their passivation during operation remains an important challenge to address. To elucidate the mechanism for their oxidation and investigate the influence of doping on their oxidation stability, the thermal-oxidation behavior in air of Ti 4 O 7 doped with V, Cr, Fe, and Ga was investigated by thermogravimetric analysis. V-doping and Fe-doping improved the thermal stability of Ti 4 O 7 as evidenced by higher onset temperatures in their thermograms. Three-dimensional diffusion reaction models adequately describe the solid-state kinetics of thermal oxidation of Ti 4 O 7 in air as demonstrated by linear model-fitting. Doping shows a mixed influence on the kinetics for thermal oxidation in air reducing both the Arrhenius pre-exponential factor and the activation energy. Cr-doping significantly shortens the lifetime of Ti 4 O 7 in ambient conditions as determined by kinetic predictions.

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 score0.163
Threshold uncertainty score0.341

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 head0.018
GPT teacher head0.254
Teacher spread0.236 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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