Correlating the Microstructure and Surface Morphology of Additively Manufactured 304L Series Stainless Steel to Its Corrosion Response
Bibliographic record
Abstract
In recent years a desire to rapidly prototype complex metallic parts has driven the advancement of metal additive manufacturing (AM). Powder bed selective laser melting (SLM) and laser engineered net shape (LENS) have emerged as prevalent techniques for producing a wide range of complex metal components. That said, the non-equilibrium processes associated with SLM and LENS techniques lead to microstructural heterogeneity and irregular surface structures throughout components, which can be cause for corrosion behavior considerably different from conventionally processed materials. This presentation will investigate and compare the corrosion behavior of 304L stainless steel produced by the SLM and LENS processes. An emphasis will be on how the heterogeneous microstructures of the AM components influence breakdown of passivity and repassivation in aqueous solutions. The impact of surface treatments, such as laser surface modification, have on AM component roughness and subsequently the corrosion response will be explored.
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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".