Unveiling the Mechanism of Cyclic Indentation in a Fe–Mn–Al–C Alloy
Bibliographic record
Abstract
Abstract This study explores the cyclic elastoplastic deformation behavior of an Fe–Mn–Al–C alloy at room temperature by employing load-controlled nanoindentation with a Berkovich indenter, offering new insights into the competition between plastic and elastic energy. The dynamic nanoindentation tests were conducted with load ratios $$\left(R= {P}_\text{min}/{P}_\text{max}\right)$$ R = P min / P max ranging from 0 to 0.5 for 100 and 200 mN, considering 50, 300 and 500 loading cycles. Results revealed that at the maximum depth, the elastic (E e) and plastic (E p) energy remains constant, whereas the ability to absorb E p decreases by approximately 1.4 and the E e decreases by approximately 1.5 when R varies from 0 to 0.5. Additionally, the relationship between E e and E p is ~ 2 times regardless of the load or number of load cycles. The occurrence of pop-ins at low loads suggests potential interactions between dislocations and twins, given the austenitic nature of the alloy with a low stacking fault energy (SFE). Creep behavior was analyzed at loads ranging from 1 to 10 mN with a holding time of 30 seconds. The creep rate increases with increasing load and holding time, suggesting that at the macroscopic scale, the strain rate affects the strain hardening rate.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".