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Record W1967549968 · doi:10.1149/1.3446823

Corrosion of Uranium Dioxide Containing Simulated Fission Products in Dilute Hydrogen Peroxide and Dissolved Hydrogen

2010· article· en· W1967549968 on OpenAlexafffund
M.E. Broczkowski, Peter Keech, Jamie Noel, David W. Shoesmith

Bibliographic record

VenueJournal of The Electrochemical Society · 2010
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaNuclear Waste Management Organization
KeywordsNoble metalChemistryInorganic chemistryElectrochemistryMetalHydrogen peroxideRadicalHydrogenX-ray photoelectron spectroscopyUraniumCorrosionNoble gasFission productsMaterials scienceElectrodeRadiochemistryChemical engineeringMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

A combination of electrochemical methods and X-ray photoelectron spectroscopy has been used to study the combined influence of and dissolved on the oxidation of SIMFUEL ( electrodes fabricated to simulate spent nuclear fuel without the accompanying radiation fields) electrodes in 0.1 mol/L KCl (pH 9.5) at . The SIMFUEL electrodes contain (where RE is rare earth) ions at lattice sites within the matrix and noble metal particles dispersed throughout the solid. Under Ar-purged conditions, can be oxidized by by coupling to its direct reduction on the surface and on the noble metal particles that are galvanically coupled to the matrix. The radicals formed on the noble metal particles can be scavenged by reaction with in -purged solutions. Because the concentration is many orders of magnitude greater than concentrations, the rate of formation of radicals on the noble metal surface exceeds that of radicals, leading to the prevention, or even the reversal, of oxidation. A ratio is sufficient to completely protect the surface from oxidation.

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 score0.001
Threshold uncertainty score0.307

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 studies0.0000.000
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 head0.008
GPT teacher head0.217
Teacher spread0.208 · 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

Citations18
Published2010
Admission routes2
Has abstractyes

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