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Record W1846917069 · doi:10.1039/c5cp02828k

Radiation-induced formation of Co<sub>3</sub>O<sub>4</sub> nanoparticles from Co<sup>2+</sup>(aq): probing the kinetics using radical scavengers

2015· article· en· W1846917069 on OpenAlexafffund
L. M. Alrehaily, Jiju M. Joseph, J. Clara Wren

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2015
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRadiolysisKineticsChemistryChemical kineticsRadiation chemistryNanoparticleChemical reaction kineticsRadicalRadiationPhysical chemistryPhotochemistryChemical reactionMaterials scienceNanotechnologyPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

The effects of the Co(2+) content and different radical scavengers on the kinetics of γ-radiation-induced Co3O4 nanoparticle formation and growth were investigated. There are four distinct stages of particle formation with different oxidation rates. Scavengers and [Co(2+)]0 affect the oxidation kinetics in the different stages and consequently the final size of the particles formed. Radiolysis model calculations were performed to obtain the time-evolution of the concentrations of key oxidants and reductants, and the effect of scavengers on those concentrations. Based on the model results and experimental data a reaction mechanism for Co3O4 particle formation by γ-irradiation of solutions containing Co(2+)(aq) is proposed. The main cobalt oxidation reaction changes with time. Oxidation of Co(2+)(aq) to Co(3+)(aq) by radiolytically produced ˙OH occurs first in the solution phase. This is followed by spontaneous co-precipitation of mixed Co(II)/Co(III) hydroxide nucleate particles. Adsorption of Co(II)(ad) followed by surface oxidation of Co(II)(ad) to CoOOH(ad) by H2O2 grows particles with a solid CoOOH(s) phase. In parallel, the solid-state transformation of CoOOH(s) and Co(II)(ad) to form Co3O4(s) occurs.

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 categoriesMeta-epidemiology (narrow)
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 score0.075
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.266
Teacher spread0.241 · 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.

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

Citations26
Published2015
Admission routes2
Has abstractyes

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