Influence of Galfan coating on tensile properties, microstructure and dislocation densities of CRS 1018 steel
Bibliographic record
Abstract
Abstract In the present work, zinc‐6 % aluminium alloy, Galfan, is coated through the hot dipping technique on tensile bars made from cold rolled CRS 1018 steel to study the influence of Galfan coating on tensile properties of mild steel. The tensile results indicate that Galfan coating prepared by the hot dipping process reduces the ultimate tensile strength and yield strength of the substrate, whereas the elongation at failure is significantly increased. The microstructure of the as‐rolled, hot‐dipping coated, and other comparing specimens is observed by optical microscopy. Nano indentation is used to evaluate the variation of dislocation densities in the tested specimens. The analyses of the hardness‐depth curves obtained from the nano indentation testing implies that the dislocation density of the coated steel might be lower than that of the uncoated specimen. The thermal energy received by the steel substrate during the heating stage of the hot‐dipping process should be responsible for the recovery of the substrate, which leads to the reduction in dislocation densities and the arrangement of the dislocations into lower‐energy configurations. As a result, the Galfan coating increases the elongation at failure considerably with a moderate decrease in strengths.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".