Will crystallographic faces of a crystal keep their order in strength and friction coefficient when the contact force is reduced to nano/micro-Newton level?
Bibliographic record
Abstract
Properties of a crystal are generally anisotropic, which makes different crystallographic planes behave differently. By choosing a suitable crystallographic plane or textured polycrystalline surface, one may obtain optimum mechanical and tribological properties, e.g., the maximum strength and desired friction coefficient. Up to date, we have had sufficient knowledge about the relationship between mechanical properties and the crystallographic orientation for different crystal systems. However, when the contact force is decreased to nano/micro-Newton level, will the crystallographic faces of a crystal keep their order in strength and other properties? This article reports our recent studies on this issue using copper as a sample material and demonstrates that there are transitions in hardness and friction coefficient between different crystallographic planes of Cu. It has been demonstrated that the closely packed plane (111) is harder and has a smaller friction coefficient than the (001) plane; however, the situation is reversed when the load is reduced to nano/micro-Newton level that only results in distortion of a few atomic layers. Such changes are of particular importance to the application of crystalline materials in nanomachines or nanodevices.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".