Issues in characterizing parameters influencing nanometric friction (CROSBI ID 652315)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa
Podaci o odgovornosti
Perčić, Marko ; Zelenika, Saša
engleski
Issues in characterizing parameters influencing nanometric friction
Friction and wear are one of the most challenging problems in micro- and nanosystems’ technologies. In fact, friction is a nonlinear stochastic effect with a marked time, position and temperature variability. While frictional phenomena on the macro- and meso-scales are well described and can generally be efficiently compensated, in the nanometric domain friction is still a matter of studies. In fact, the understanding of friction at the level of atomic interactions was enabled only in the last couple of decades by the affordable availability of scanning probe microscopy (SPM) methods based on normal forces in the range of µN to nN in the lateral force microscopy (LFM) configuration. The presented research aims at providing a contribution to the study of friction by characterising the parameters influencing its value at the nanometric scale, and especially the dependence of friction on material properties, surface topography, loading conditions, velocity of motion and, possibly, temperature and lubrication. In this work, we thus present preliminary results of experimental measurements characterising the parameters influencing nanoscale friction. The experimental research is carried out by using the LFM mode on a Bruker Dimension Icon SPM device. The methodology used to calibrate the normal and lateral stiffness of SPM probes, and the initial results of measurements of nanoscale friction coefficients of various materials (fused silica, molybdenum- disulphide, highly oriented pyrolytic graphite and titanium-dioxide) vs. varying normal force, sliding velocity and temperature conditions are presented. By employing the support vector regression (SVG) method implemented in the GoSumD® software, the obtained experimental data is used next to generate a model that will allow obtaining the correlation functions linking the process variables to the value of nanometric friction, and hence to eventually extend the mathematical formulation of established friction models to the nanometric range.
nanometric friction ; experimental determination ; scanning probe microscopy ; cantilever calibration ; machine learning ; friction model
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Podaci o prilogu
40-41.
2017.
objavljeno
Podaci o matičnoj publikaciji
Book of Extended Abstracts - My First Conference 2017
Kvaternik, Sanja ; Torbarina, Fran ; Vitali, Natalija ; Čanađija, Marko ; Travaš, Vanja ; Vukelić, Goran
Rijeka: Tehnički fakultet Sveučilišta u Rijeci
978-953-6326-92-1
Podaci o skupu
My First Conference 2017.
predavanje
29.09.2017-29.09.2017
Rijeka, Hrvatska