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Record W4401886596 · doi:10.1115/1.4066339

Investigation of Metal–H2O Systems at Elevated Temperatures: Part I. Development of a Solubility Apparatus Specialized for Super-Ambient Conditions

2024· article· en· W4401886596 on OpenAlexafffund
Olga Y. Palazhchenko, Matthew H. Kaye

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2024
Typearticle
Languageen
FieldChemistry
TopicRadioactive element chemistry and processing
Canadian institutionsOntario Tech UniversityUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolubilityCorrosionDissolutionPourbaix diagramOxideMaterials scienceThermodynamicsWork (physics)AlloyAqueous solutionInstrumentation (computer programming)MetalPhase (matter)Liquid metalProcess engineeringMetallurgyChemistryElectrochemistryComputer science

Abstract

fetched live from OpenAlex

Abstract Metals used in aqueous environments where high temperatures and pressures are present are susceptible to corrosion. This is the case for nuclear power plants, especially CANDUTM reactors, where the liquid water systems can reach over 300 °C at pressures well above 101.325 kPa (1 atm). In such situations, failure to control corrosion has economic and safety consequences. To extend corrosion modeling tools, such as Pourbaix diagrams, to harsh aqueous conditions, there is a need for experimental thermochemical data performed at elevated temperatures. This is particularly true for metal and alloy systems where such information is unavailable or unreliable. A relatively simple approach to obtaining temperature dependent thermodynamic properties is the investigation of solid–liquid phase, or solubility, equilibria. However, this requires specially designed instrumentation that can withstand harsh temperatures and extreme pH conditions, while providing accurate data. In this work, an apparatus developed for super-ambient highly acidic and alkaline solubility experiments is presented. Solubility measurements were made in the zinc oxide system, which has been extensively studied. Using these equilibrium data and comparing to the literature, allowed the instrumentation and analysis process to be validated. In situ pH measurements using a constant volume, batch reactor system are described along with a brief presentation of the ZnO dissolution equilibria results at 85 °C (358.15 K).

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 score0.032
Threshold uncertainty score0.268

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 head0.022
GPT teacher head0.261
Teacher spread0.240 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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