Effect of the Tempering Process on the Corrosion Performance of Wire Arc Additively Manufactured 420 Martensitic Stainless Steel
Bibliographic record
Abstract
With the aim of modifying the microstructure and improving the corrosion performance of a wire arc additive manufactured 420 martensitic stainless steel, heat treatment cycles consisting of austenitizing at 1,150°C followed by air cooling and subsequent tempering at different temperatures (300°C, 400°C, 500°C, and 600°C) were applied to the as-printed alloy. Microstructural analysis revealed that the austenitization and subsequent air-cooling treatment led to the removal of retained austenite and delta ferrite from the as-printed structure, while the tempering process resulted in the precipitation of a variety of carbide particles at different tempering temperatures. Electrochemical tests performed in an aerated 3.5 wt% NaCl solution showed that tempering at 400°C led to the highest corrosion resistance, while tempering at 500°C deteriorated the alloy’s resistance against localized corrosion. The most stable passive layer was found to form on the 400°C tempered sample due to the uniformity of Cr-concentration in the formed carbide precipitates and their surrounding matrix. However, Cr-rich carbide precipitates formed in the 500°C tempered sample were found to deteriorate the passive film stability throughout the immersion time in the electrolyte.
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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) | 0.000 | 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".