Probing Plasticity and Strain-Rate Effects of Indium Submicron Pillars Using Synchrotron Laue X-Ray Microdiffraction
Bibliographic record
Abstract
Mechanical behaviors and especially the strain-rate responses at the nanoscales of low melting temperature metals, such as indium, have not been studied much. Indium is one of the key materials or alloy components in advanced microelectronics and the nanotechnology industry, and understanding their mechanical behaviors at nanoscales becomes increasingly important to ensure lifetime reliability of their applications in novel nanoscale devices or advanced systems (for packaging at the nanoscales, for instance). Synchrotron X-ray microdiffraction has been utilized to examine defect structures of nanoscale materials as well as their strain-rate responses. Nanoscale or advanced microelectronics packaging, for instance, require acceptable levels of drop test results. For these low melting temperature materials especially, this technique offers a unique advantage as conventional methods such as transmission electron microscope and EBSD will expose the structure to high-energy electron beams that may significantly alter the microstructure and defect structure during analysis. Using this approach, we found interesting differences in term of X-ray peak broadening after deformation with different strain rates, which could indicate differences in plasticity mechanisms in the submicron pillars of indium, which could be important for their applications in nanodevices. Understanding these differences could lead to better control of mechanical properties of low melting temperature metals at the nanoscales and, thus, have important implications for nanodevice reliability.
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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 | 0.001 |
| 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".