Corrosion Behavior of Chromium Coated Zy-4 Cladding under CANDU Primary Circuit Conditions
Bibliographic record
Abstract
The manuscript is focused on corrosion behavior of a Cr coating under CANada Deuterium Uranium(CANDU) primary circuit conditions. The Cr coating is obtained via the thermionic vacuum arc procedure on Zircaloy -4 cladding. The surface coating characterization was performed using metallographic analysis and scanning electron microscopy (SEM) with an energy dispersive spectra detector (EDS), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) investigations. The thickness of the Cr coating determined from SEM images is around 500 nm layers After the autoclaving period, the thickness of the samples increased in time slowly. The kinetic of oxidation established a logarithmic oxidation law. The corrosion tests for various autoclaving periods of time include electrochemical impedance spectroscopy (EIS) and potentiodynamic tests, permitting computing porosity and efficiency of protection. All surface investigations sustain electrochemical results and promote the Cr coating on Zircaloy-4 alloy autoclaved for 3024 h as the best corrosion resistance based on decrease in corrosion current density values simultaneously with the increase of the time spent in autoclave. A slow increase of Vickers micro hardness was observed as a function of the autoclaved period as well. The value reached for 3024 h being 219 Kgf/mm2 compared with 210 Kgf/mm2 value before autoclaving.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".