Adhesion between Nanoscale Rough Surfaces.

Nanoscale surface roughness strongly affects the adhesion force between surfaces. In this investigation, a model that more accurately describes the size of an asperity based on the measurable parameters of root-mean-square (rms) roughness and the distance between the asperities is derived. The radius of the asperity from the proposed model is much larger than the radius used in previous approaches, considering the same surface with nanoscale roughness. Using the proposed geometry and previously suggested models, this paper elucidates the contributions from contact and noncontact interactions of a particle adhered to a surface with nanoscale roughness (approximately less than 20 nm rms). For most surfaces considered, the contact interaction of the asperity and the adhering particle are found to dominate the interaction. In the second paper of this series, the proposed model is compared to the experimentally determined force of adhesion in systems with nanoscale roughness. Copyright 2000 Academic Press.

Adhesion between Nanoscale Rough Surfaces.

In this investigation, the adhesion between particles and plates with root-mean-square, rms, surface roughness of 0.17-10.5 nm was measured by atomic force microscopy. Measurements obtained with particles both larger and smaller than the surface asperities are presented. Results indicate adhesion force decreases sharply with increasing surface roughness in the nanometer scale (<2 nm), followed by a gradual and slow decrease with further increase in roughness. Existing models were found to significantly underestimate adhesion force. Hence, a new model based on a geometry that considers both the height and breadth of asperities yielding an increased asperity radius compared to previous approaches, as detailed in Part I of this series, is applied using both van der Waals and elastic deformation/work of adhesion based approaches. For the system studied in this investigation, the adhesion forces predicted by the proposed model are considerably more accurate than those predicted by past models. Copyright 2000 Academic Press.