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Record W2915222762 · doi:10.1111/jace.16397

Synthesis and thermal stability of (Co,Ni)O solid solutions

2019· article· en· W2915222762 on OpenAlexafffund
Saeed Mohammadkhani, Emmanuel Schaal, Ali Dolatabadi, Christian Moreau, Boyd Davis, Daniel Guay, Lionel Roué

Bibliographic record

VenueJournal of the American Ceramic Society · 2019
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsKingston Process Metallurgy (Canada)Concordia UniversityInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCalcinationThermogravimetric analysisSolid solutionMaterials scienceThermal stabilitySolid-stateBall millChemical engineeringContext (archaeology)ElectrolyteMetallurgyChemistryCatalysisPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract (Co,Ni)O solid solutions are considered as promising protective materials of O 2 ‐evolving anodes for Al production. In this context, two solid‐state synthesis methods, namely high‐energy ball milling (HEBM) and calcination, have been evaluated for the synthesis of (Co,Ni ) O solid solutions. In all cases, Co x Ni 1− x O solid solutions can be formed over the whole composition range. However, undesired WC contaminant is observed using the HEBM method due to the erosion of the milling tools. Their thermal stability in air has been analyzed by thermogravimetric analyzes (TGA) complemented by X‐ray diffraction (XRD) analyses. It is shown that Co x Ni 1− x O solid solutions are stable at 1000°C over the whole composition range whereas they are only stable for x ≤ 46 and x ≤ 22 at 800°C and 700°C, respectively. For higher Co contents, the formation of Co 3 O 4 is observed. This is a relevant information for their future use for Al production, which can be done at different temperatures (~700‐1000°C) depending of the electrolyte composition.

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)0.001
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 score0.087
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.283
Teacher spread0.264 · 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

Citations13
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Ceramic SocietySame topicAdvancements in Solid Oxide Fuel CellsFrench-language works237,207