The description of friction of silicon MEMS with surface roughness: virtues and limitations of a stochastic Prandtl–Tomlinson model and the simulation of vibration-induced friction reduction

• W. Merlijn van Spengen,
• Viviane Turq and
• Joost W. M. Frenken

Beilstein J. Nanotechnol. 2010, 1, 163–171, doi:10.3762/bjnano.1.20

• that we would associate in the traditional Prandtl–Tomlinson model with ‘superlubricity’. This is the case even though we have corrected for the 10 nN measured adhesion (adhesion measurements with the MEMS tribometer are detailed in [25]). To investigate the effect of the long length scale ripples in

• force value and are shown with the green open triangles. There is no significant difference between the exponential and the ‘real’ autocorrelation simulations, and hence the effect of the ripples is negligible. Because we have carried out MEMS measurements resembling force–distance curves (as described

• Rxx(x) of a pristine sidewall surface measured with AFM, and theoretical exponential fit with a correlation length of 83 nm. The standard deviation on the height is 10.3 nm and the distribution is almost Gaussian. The long-range order is caused by the larger scale ripples. The result is that only one

A collisional model for AFM manipulation of rigid nanoparticles

• Enrico Gnecco

Beilstein J. Nanotechnol. 2010, 1, 158–162, doi:10.3762/bjnano.1.19

• scratches the polymer surface while scanning [11]. Linear and ‘travelling’ circular ripples were formed using a raster or a circular scan path, respectively. In the same way, a desired configuration of nanoparticles could be obtained by a proper choice of the scan pattern. Conclusion In conclusion, we have