Influence of Electron Beam Irradiation on Surface Roughness of Commercially AISI 5140 Steel
Bibliographic record
Abstract
In this study, a commercially AISI 5140 steel with two different levels of initial surface state (initial high-roughness (IHR) and initial low-roughness (ILR)) was surface-treated by large-area pulsed electron beam irradiation (LPEBI). Surface morphology in 2D and 3D of the two types of samples after LPEBI treatment was characterized. The results show that the surface roughness of IHR samples decreases clearly with increasing LPEBI pulse numbers, while an opposite trend is found in the ILR samples. It is considered that the final surface roughness is influenced by surface remelting and formation of crater-like structures (CLSs) in local regions. For the IHR samples with amounts of mechanical scratches, the remelting plays the leading role, owing to the high surface energy which provides extra driving force for remelting during LPEBI. In contrast, such extra driving force is less due to the relatively flat surface of the ILR samples, instead remelting the surface suffers from the formation of CLSs in localized region. Compared to the formation of localized CLSs, the surface remelting is beneficial to surface roughness of the LPEBI processed samples.
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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".