Unexpected Corrosion of a Nickel-base Alloy in Acid Refiner Environments: a Mill Case Study
Bibliographic record
Abstract
Abstract The repeated failures of a wear sleeve in a primary refiner processing hardwood chips for bleached chemithermomechanical pulp (BCTMP) high-yield pulp is costly, and required scheduling for maintenance and replacement. Nickel-chromium thermal sprays can be used to protect wear sleeves in this environment because of their resistance to abrasion and aqueous corrosion. The formation of acetic or sulphuric acids within the refining zone was suspected as a corrodant due to naturally occurring acetyl groups during the pulping process, or from decomposition of residual sulphite impregnation liquor. This report describes a liquor drop test which that simulated vapor phase corrosion and demonstrate the ability of the acids to corrode the wear sleeve alloy. Surface morphologies were analyzed using a scanning electron microscope (SEM) with energy dispersive spectroscopy (EDS). Corrosion products were measured using x-ray fluorescence spectroscopy (XRF) and x-ray diffraction (XRD). The tests showed that the nickel phase in the coating is vulnerable to corrosion by both weak acids. This is circumstantial evidence that acid condensation in the refining zone is possible. Based on the test reported here, the two weld overlays tested are promising candidates for wear sleeve service in hardwood high-yield pulping.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".