Large-Scale Density Functional Theory Investigation of Failure Modes in ZnO Nanowires
Bibliographic record
Abstract
Electromechanical and photonic properties of semiconducting nanowires depend on their strain states and are limited by their extent of deformation. A fundamental understanding of the mechanical response of individual nanowires is therefore essential to assess system reliability and to define the design space of future nanowire-based devices. Here we perform a large-scale density functional theory (DFT) investigation of failure modes in zinc oxide (ZnO) nanowires. Nanowires as large as 3.6 nm in diameter with 864 atoms were investigated. The study reveals that pristine nanowires can be elastically deformed to strains as high as 20%, prior to a phase transition leading to fracture. The current study suggests that the phase transition predicted at approximately 10% strain in pristine nanowires by the Buckingham pairwise potential (BP) is an artifact of approximations inherent in the BP. Instead, DFT-based energy barrier calculations suggest that defects may trigger heterogeneous phase transition leading to failure. Thus, the difference previously reported between in situ electron microscopy tensile experiments (brittle fracture) and atomistic simulations (phase transition and secondary loading) (Agrawal, R.; Peng, B.; Espinosa, H. D. Nano Lett. 2009, 9 (12), 4177-2183) is elucidated.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".