INVESTIGATION FOR MOLECULAR ATTRACTION IMPACT BETWEEN CONTACTING SURFACES IN MICRO-GEARS
Bibliographic record
Abstract
The aim of this research work is to provide a systematic method to perform molecular attraction impact between contacting surfaces in micro-gear train. This method is established by integrating involute profile analysis and molecular dynamics simulation. A mathematical computation of micro-gear involute is presented based on geometrical properties, Taylor expression and Hamaker assumption. In the meantime, Morse potential function and the cut-off radius are introduced with a molecular dynamics simulation. So a hybrid computational method for the Van Der Waals force between the contacting faces in micro-gear train is developed. An example is illustrated to show the performance of this method. The results show that the change of Van Der Waals force in micro-gear train has a nonlinear characteristic with parameters change such as the modulus of the gear and the tooth number of gear etc. The procedure implies a potential feasibility that we can control the Van Der Waals force by adjusting the manufacturing parameters for gear train design.
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".