Clumping Criteria of Vertical Nanofibers on Surfaces
Why this work is in the frame
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Bibliographic record
Abstract
The side–side, side–tip, and tip–tip clumping of nanofibers, including nanowires and nanotubes on surfaces, is a common problem that can diminish their optical, electrical, and mechanical performance. However, these different clumping configurations brought much complexity and confused researchers to predict or design the desired clumping or nonclumping. In this study, a universal model in the unified formula for the critical clumping criteria for three contact geometries of nanofiber arrays is derived in terms of two‐dimensionless geometric and mechanical parameters, based on the length, radius, spacing, Young's modulus, and adhesion energy of the nanofibers. The model provides an easy way to predict the sequences of the three clumping configurations, which are successfully verified by analyzing various clumping structures reported in the literatures. This study provides new insights into, and methods for, designing nanofiber arrays on surfaces to achieve desired clumping or nonclumping structures.
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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 it