Metal Seed Loss Throughout the Nanowire Growth: Bulk Trapping and Surface Mass Transport
Bibliographic record
Abstract
The physical and chemical properties of metal-catalyzed semiconductor nanowires are very sensitive to their composition and morphology, which are very sensitive to the behavior of the catalyst nanodroplet during growth. Herein, we identify and investigate the main atomic pathways and processes governing the metal mass transport and the associated variation in the nanodroplet size throughout the growth of metal-catalyzed silicon nanowires. This includes surface diffusion and catalyst trapping in addition to the shift in phase boundaries of the eutectic nanodroplet to count for surface effects, capillarity, and related nanoscale stresses. On the basis of thermodynamic and kinetic considerations, a theoretical framework is presented to elucidate these catalyst nanodroplet instabilities. Moreover, we also address the influence of these phenomena on the shape and impurity concentration in silicon nanowires. Modeling results along with experimental data demonstrate that the combined effects of the kinetically driven catalyst trapping and surface diffusion play the key role in tailoring the nanowire morphology and composition. The proposed model can be extended straightforwardly to describe the evolution of the morphology during the growth of any other system of metal-catalyzed semiconductor nanowires.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".