MétaCan
Menu
Back to cohort
Record W2884064296 · doi:10.1115/1.4040889

Performance of Aluminide and Cr-Modified Aluminide Pack Cementation-Coated Stainless Steel 304 in Supercritical Water at 700 °C

2018· article· en· W2884064296 on OpenAlexafffund
Nick Tepylo, Xiao Huang, Shengli Jiang, Sami Penttilä

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2018
Typearticle
Languageen
FieldEngineering
TopicSubcritical and Supercritical Water Processes
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAluminideMaterials scienceMetallurgyTitanium aluminideSupercritical fluidCoatingScanning electron microscopeCementation (geology)AlloyComposite materialIntermetallic

Abstract

fetched live from OpenAlex

The choice of materials is of great concern in the construction of Gen IV supercritical water reactors (SCWR), particularly the fuel cladding, due to the harsh environment of elevated temperatures and pressures. A material's performance under simulated conditions must be evaluated to support proper material selection by designers. In this study, aluminide and Cr-modified aluminide coated 304, as well as bare stainless steel 304 as a reference material, were tested in supercritical water (SCW) at 700 °C and 25 MPa for 1000 h. The results showed that all three samples experienced weight loss. However, the aluminide coated 304 had 20 to 40 times less weight loss compared to Cr-modified aluminide coated and bare stainless steel 304 specimens, respectively. Based on scanning electron microscope/energy dispersive X-ray spectroscopy (SEM/EDS) and X-ray diffraction (XRD) analysis results, spinel and hematite Fe2O3 formed on bare 304 after 1000 h in SCW while alumina was observed on both coated specimens, i.e., aluminide and Cr-modified aluminide surfaces. Oxide spallation was observed on the bare 304 and Cr-modified aluminide surface, contributing to a larger weight loss. Based on the results from this study, pure aluminide coating with Al content of 10–11 wt % demonstrated superior performance than bare 304 and Cr-modified aluminide coated 304.

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 categoriesnone
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 score0.657
Threshold uncertainty score0.315

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 communication0.0000.001
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 head0.010
GPT teacher head0.226
Teacher spread0.217 · 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

Citations3
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Nuclear Engineering and Radiation ScienceSame topicSubcritical and Supercritical Water ProcessesFrench-language works237,207