Colloidal Interactions for Nanopatterned Surfaces Based on Surface Element Integration (SEI) Approach
Bibliographic record
Abstract
In this study, van der Waals and electrostatic interaction energies on a nanopatterned rough surface was investigated. Surface element integration method (SEI) was applied to determine the interaction between a nanostructured substrate and an infinite flat plate. Hemispherical protrusions or depressions were mathematically generated on a square lattice to represent the rough surface. The size of the asperities and the pitch (separation) between their centers were varied. From the above calculations, we have analyzed the coupling between the range of the interactions and the roughness features of the substrate by comparing the ratios of the rough surface to smooth surface interaction energies per unit area. At small separations, the rough surface van der Waals interaction is seriously attenuated in the presence of protruding asperities. This attenuation is less pronounced for depressions. The attenuation of the van der Waals interaction due to asperities diminishes at large separations. In contrast, attenuation of the electrostatic interaction is independent of the separation.
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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 | 0.001 |
| 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".