The Effects of ECAP and Recovery Treatment on the Microstructure and the Mechanical, Tribological, and Corrosion Properties of 316L Steel
Bibliographic record
Abstract
316L steel is widely used in various industries and is also one of the metallic materials used for biomedical applications because of its excellent mechanical properties, corrosion resistance, and biocompatibility. This article reports a comprehensive study on the effects of equal channel angular pressing (ECAP) and subsequent recovery treatment on the microstructure and the mechanical, tribological, and corrosion properties of 316L. The process includes an initial annealing at 1050 °C for 2 h to obtain a homogenous microstructure, ECAP at room temperature with a 120° inner angle, and subsequent recovery treatment at 340 °C for 1 h. The microstructure was investigated with an optical microscope and a transmission electron microscope. The mechanical properties were evaluated with hardness and compression tests. The corrosion behavior was analyzed with dynamic polarization tests. The wear test was performed using a scratching tester, and the volume loss was measured with a profilometer. The results of the study demonstrate that the ECAP–recovery sample exhibits improved properties compared to both the annealed sample and the ECAP sample. The corrosion tests show that the ECAP sample has a corrosion resistance higher than that of the annealed sample but lower than that of the ECAP–recovery sample. The ECAP–recovery sample shows the highest wear resistance and corrosive wear resistance among the three 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".