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Record W2112722279 · doi:10.1149/1.3557748

Gamma Radiation-Induced Carbon Steel Corrosion

2011· article· en· W2112722279 on OpenAlexafffund
Kevin Daub, James J. Noël, J.C. Wren

Bibliographic record

VenueECS Transactions · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRadiation Effects and Dosimetry
Canadian institutionsWestern University
FundersCanada Research Chairs
KeywordsCorrosionMaterials scienceCarbon steelPolarization (electrochemistry)IrradiationX-ray photoelectron spectroscopyDielectric spectroscopyOxidizing agentRaman spectroscopyRedoxElectrochemistryGamma rayMetallurgyChemical engineeringElectrodeChemistry

Abstract

fetched live from OpenAlex

Carbon steel waste containers have been proposed in a number of national nuclear waste management programs. Although redox conditions in the sedimentary clay environments in which these containers would be placed will be anoxic, gamma irradiation would produce oxidizing conditions at the container surface. The effect of gamma radiation on carbon steel corrosion in de-aerated solutions was studied as a function of pH and temperature. The corrosion kinetics were studied by monitoring the corrosion potential (Ecorr) in-situ, and periodically performing linear polarization and electrochemical impedance spectroscopy measurements to determine polarization resistances. The surfaces, and cross sections of irradiated carbon steel coupon samples were also examined using SEM, XPS, and Raman spectroscopy. Preliminary results indicate that gamma irradiation increases the corrosion potential from a region where the anodic oxidation is limited to Fe(OH)2 and Fe3O4 to a region where the oxidation of Fe(OH)2 to gamma-FeOOH and Fe3O4 to gamma-Fe2O3 is possible.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.999

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)0.0020.000

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 head0.027
GPT teacher head0.208
Teacher spread0.181 · 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

Citations7
Published2011
Admission routes2
Has abstractyes

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