Electrochemical potentiokinetic reactivation study of laser-surface-melted 3CR12 steel
Bibliographic record
Abstract
Laser surface melting (LSM) of ferritic/martensitic 3CR12 steel, using a 3 kW CW Nd:YAG laser with a line beam profile, provides improvement in the resistance to pitting corrosion in chloride-containing solutions to an extent dependent upon the final microstructure. In particular, LSM parameters that transform the dual-phase banded microstructure of the hot-rolled and annealed steel to a mainly ferritic structure generate relatively large increases in pitting potential. Under conditions of slower cooling, associated with smaller improvements of pitting potential, significant amounts of martensite, which is re-formed at ferrite grain boundaries, remain in the melted layer. Such regions, with reduced chromium content, are preferred sites for initiation of pits. The present study employs electrochemical potentiokinetic reactivation (EPR), using 0.1 M H2SO4 solution, to detect the presence of martensite in the laser-melted steel, and also chromium-depleted regions along the grain boundaries. Thus, the technique enables ready identification of microstructures with chromium deficiencies and hence, enhanced susceptibility to pitting and intergranular corrosion.
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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) | 0.001 | 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 | 0.001 |
| 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".