In this paper, the process of pushing rough cylindrical micro/nanoparticles on a surface with an atomic force microscope (AFM) probe is investigated. For this purpose, the mechanics of contact involving adhesion are studied first. Then, a method is presented for estimating the real area of contact between a rough cylindrical particle (whose surface roughness is described by the Rumpf and Rabinovich models) and a smooth surface. A dynamic model is then obtained for the pushing of rough cylindrical particles on a surface with an AFM probe. Afterwards, the process is simulated for different particle sizes and various roughness dimensions. Finally, by reducing the length of the cylindrical particle, the simulation condition is brought closer to the manipulation condition of a smooth spherical particle on a rough substrate, and the simulation results of the two cases are compared. Based on the simulation results, the critical force and time of manipulation diminish for rough particles relative to smooth ones. Reduction in the aspect ratio at a constant cross-section radius and the radius of asperities (height of asperities based on the Rabinovich model) results in an increase in critical force and time of manipulation.
Application of four nano-contact mechanics models, JKR, DMT, Hertz and PT in manipulation of biological cells in biological environment based on atomic force microscope has been analyzed, and the sensitive and non-sensitive parameters and their sensitive ranges have been identified. To analyze sensitivity of contact theories to basic parameters of biological cell, the Sobol method was used. All the used models are small deformation contact mechanics models, but they are different in considerations and limitations. This selection was on purpose to analyze and compare theoretical and empirical models sensitivities. The results indicate that the deformation of biological nano-particle is very sensitive to the elasticity modulus in all models. Adhesion energy, Poisson ratio and particle radius have, respectively, the next ranks which the results of graphic SA confirm, but their effects are not the same in different models. Moreover, the results of the graphic sensitivity analysis SA show that the degree of sensitivity depends on the apparent values of input parameters, such that by changing the magnitude of a specific parameter, it could be possible to increase or decrease the sensitivity.
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