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Record W4391068377 · doi:10.1016/j.corsci.2024.111845

Monitoring alterations in a salt layer’s deliquescence properties during the atmospheric corrosion of a metal surface using a quartz crystal microbalance

2024· article· en· W4391068377 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCorrosion Science · 2024
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsNuclear Waste Management OrganizationWestern University
FundersNatural Sciences and Engineering Research Council of CanadaNuclear Waste Management Organization
KeywordsQuartz crystal microbalanceCorrosionQuartzMetalMaterials scienceSalt (chemistry)Layer (electronics)Surface layerCrystal (programming language)Chemical engineeringInorganic chemistryMetallurgyComposite materialChemistryAdsorptionPhysical chemistry

Abstract

fetched live from OpenAlex

The deliquescence of salt residues on metal structures can exacerbate the atmospheric corrosion of these structures. However, the conversion of salt residues to corrosion products alters the metal surface time of wetness (TOW) in ways that are difficult to monitor. This study demonstrates the use of quartz crystal microbalance with acoustic impedance measurement (QCM-I) to simultaneously monitor the corrosion and the changing deliquescence properties of various chloride salt layers printed on copper surfaces. While the results herein apply to Canada’s proposed deep geological repository (DGR) for used nuclear fuel, the methodology applies to any combination of salts and metal surfaces.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.025
GPT teacher head0.263
Teacher spread0.237 · 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