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Record W2964564904 · doi:10.1115/1.4044409

Formation of Local, Transient “Acid Spikes” in the Fast Neutron Radiolysis of Supercritical Water at 400 °C: A Potential Source of Corrosion in Supercritical Water-Cooled Reactors?

2019· article· en· W2964564904 on OpenAlexaff
Md Mohsin Patwary, Sunuchakan Sanguanmith, Jintana Meesungnoen, Jean‐Paul Jay‐Gerin

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2019
Typearticle
Languageen
FieldEngineering
TopicSubcritical and Supercritical Water Processes
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSupercritical fluidRadiolysisNeutronNeutron fluxNuclear engineeringNeutron sourceMaterials scienceChemistryRadiochemistryNuclear physicsIrradiationPhysics

Abstract

fetched live from OpenAlex

Abstract The use of supercritical water (SCW) in GEN IV reactors is a logical approach to the ongoing development of nuclear energy. A proper understanding of the radiation chemistry and reactivities of transients in a reactor core under SCW conditions is required to achieve optimal water chemistry control and safety. A Monte Carlo simulation study of the radiolysis of SCW at 400 °C by incident 2 MeV monoenergetic neutrons (taken as representative of a fast neutron flux in a reactor) was carried out as a function of water density between ∼150 and 600 kg/m3. The in situ formation of H3O+ by the generated recoil protons was shown to render the “native” track regions temporarily very acidic (pH ∼ 1). This acidity, though local and transitory (“acid spikes”), raises the question whether it may promote a corrosive environment under proposed SCW-cooled reactor operating conditions that would lead to progressive degradation of reactor components.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.004
GPT teacher head0.184
Teacher spread0.180 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2019
Admission routes1
Has abstractyes

Explore more

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