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Record W4327947048 · doi:10.26434/chemrxiv-2023-chwf0

Nickel-based alloy corrosion in CANDU steam generators: E-pH diagrams of the Ni-NH3-H2O and Ni-CH3COO−-H2O ternary systems

2023· preprint· en· W4327947048 on OpenAlexaff
Mohammad Amin Razmjoo Khollari, Hamid Zebardast, Edouard Asselin

Bibliographic record

VenueChemRxiv · 2023
Typepreprint
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of British ColumbiaKinectrics (Canada)
Fundersnot available
KeywordsNickelCorrosionMaterials scienceAmmoniaAlloyNon-blocking I/OMetallurgyTernary operationIonInorganic chemistryNuclear chemistryChemistryCatalysis

Abstract

fetched live from OpenAlex

Nuclear power plant steam generator (SG) tubes contain nickel as the main alloying element and there is concern about their corrosion. We optimized models for calculating the high-temperature and high-pressure thermodynamic properties of common nuclear alloy elements and then, calculated the E-pH diagrams for nickel in different concentrations of ammonia or acetate ion between 100 to 260 ℃ at 4.7 MPa. This information is used to predict the corrosion behaviour for nickel in the secondary circuit conditions of CANDU SGs. Based on the results, nickel ammonia and nickel acetate complexes are not stable at low concentrations of ammonia or acetate ion. However, increasing the ammonia or acetate ion concentration resulted in the predominance of Ni(NH3)n2+ or Ni(Ac)n(2−n) at the expense of Ni2+ and NiO, indicating a higher risk of nickel corrosion. Calculations showed that under normal operating conditions with [NH3]tot=5×10−5 and [CH3COO−]tot=10−8 m at 260 ℃ and 4.7 MPa, nickel will be passivated as NiO, preventing the rapid degradation of nickel-based alloys. However, in the presence of a crevice that allows the acetate ion to concentrate, nickel would dissolve in the form of the Ni2+ ion, endangering safe operation of CANDU SGs.

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 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 score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.034
GPT teacher head0.259
Teacher spread0.225 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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