Mechanisms of friction reduction of nanoscale sliding contacts achieved through ultrasonic excitation
Bibliographic record
Abstract
Friction reduction is an important issue for proper functioning of nano-/micro-electromechanical systems (N-/MEMS) due to their large surface to volume ratios and the inability of traditional liquid lubricants to effectively lubricate sliding contacts. One efficient technique to achieve substantially lowered friction at the nanoscale, as well as superlubricity in some instances, was investigated with the coupling of ultrasonic actuation of the sliding contact in an atomic force microscope (AFM). Despite the successful application of ultrasonic AFM methods in achieving mechanical property measurements and nanoscale subsurface imaging of soft and hard materials, the mechanism of friction reduction in the microscopic contact and the influence of the ultrasonic parameters on friction reduction are still elusive. In this study, the effects of excitation amplitude, applied normal force, tip radius, and humidity on friction have been investigated in detail. Ultrasonic force microscopy (UFM) results are compared against those collected with conventional contact-AFM (C-AFM) and indicate that a reduction in the adhesive interaction between the tip and sample, as well as a reduction in the shear strength can explain the mechanisms of the friction reduction in UFM method. This study opens up a new door for the control of friction and wear, which is critical for the increased lifetime of AFM probes, N-/MEMS devices and would potentially bridge the gap between nanotribology and other fields, such as nanomachining, nanolithography and biomaterials imaging.
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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".