Surface tension-induced unique phenomena for edge dislocations in a free-standing thin film
Bibliographic record
Abstract
We explore the effects of surface tension and surface elasticity on the elastic behavior of a line edge dislocation buried in a free-standing thin film. Using specific conformal mappings, we derive semi-analytic solutions for the dislocation-induced stress field in the film and the image force acting on the dislocation. It is shown that surface tension and surface elasticity are responsible for significant tractions on the film surface and therefore make an important contribution to the dislocation-induced stress field in the film and to the mobility of the dislocation when the film thickness approaches the nanoscale. In terms of the moving tendency and mobility of the dislocation (defined by the image force acting on the dislocation), it is identified that the effects of surface elasticity always play the role of reducing its mobility without reversing its moving tendency, while those of surface tension would reverse the moving tendency or increase the mobility in certain specific cases. In particular, it is found that for an edge dislocation located on the mid-plane of the film, when the Burgers vector or slip plane of the dislocation is parallel or at a small angle to the surface of the film, the presence of surface tension can alter the dislocation’s equilibrium from a stable to an unstable state as the thickness of the film decreases from the macroscale to the nanoscale (which, incidentally, cannot be achieved by the separate contribution of surface elasticity alone).
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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".