Anisotropic crystal orientations dependent mechanical properties and fracture mechanisms in zinc blende ZnTe nanowires
Bibliographic record
Abstract
The orientations of crystal growth significantly affect the operating characteristics of elastic and inelastic deformation in semiconductor nanowires (NWs). This work uses molecular dynamics simulation to extensively investigate the orientation-dependent mechanical properties and fracture mechanisms of zinc blende ZnTe NWs. Three different crystal orientations, including [100], [110], and [111], coupled with temperatures (100 to 600 K) on the fracture stress and elastic modulus, are thoroughly studied. In comparison to the [110] and [100] orientations, the [111]-oriented ZnTe NW exhibits a high fracture stress. The percentage decrease in fracture strength exhibits a pronounced variation with increasing temperature, with the highest magnitude observed in the [100] direction and the lowest magnitude observed in the [110] direction. The elastic modulus dropped by the largest percentage in the [111] direction as compared to the [100] direction. Most notably, the [110]-directed ZnTe NW deforms unusually as the strain rate increases, making it more sensitive to strain rate than other orientations. The strong strain rate sensitivity results from the unusual short-range and long-range order crystals appearing due to dislocation slipping and partial twinning. Moreover, the {111} plane is the principal cleavage plane for all orientations, creating a dislocation slipping mechanism at room temperature. The {100} plane becomes active and acts as another fundamental cleavage plane at increasing temperatures. This in-depth analysis paves the way for advancing efficient and reliable ZnTe NWs-based nanodevices and nanomechanical systems.
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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) | 0.000 | 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".