Surface roughness of gold substrates at the nanoscale: An atomistic simulation study

Abstract

The statistical properties of rough surfaces at the nanoscale are studied using classical molecular dynamics. Atomistic fcc blocks of gold are generated with different crystal orientations, and with rough surfaces having the same root-mean-square roughness with variable power spectral density (PSD) slopes and roll-off wavenumbers. The process of rough surface generation may result in thermodynamically unstable sharp spatial features. In order to relax the structure, the blocks are equilibrated at 300 K. It is found that all surfaces experience changes in their roughness, regardless of their crystal orientation or temperature, although the changes are only temperature-independent when ≤ 0.4 m. Based on the analyzed PSDs of the equilibrated substrates, two methods for generating pseudo-stable rough surfaces are introduced and discussed.

Modeling and simulation in tribology across scales: An overview

“…This suggests that attempts to measure the real contact area with indirect methods, e.g., measuring conductance, have the intrinsic difficulty of measuring two quantities which depend very differently on the PSD content. The reader should keep in mind that the high-frequency cutoff may very well be related to the atomistic nature of the contact [375], which is usually challenging to measure and which goes beyond the continuum description of matter.…”

A note on the effect of surface topography on adhesion of hard elastic rough bodies with low surface energy

“…The choice of the cut-o frequency represents a critical step in modelling rough contacts. However, Solhjoo and Vakis [27] suggested that the limit of the high cut-o frequency can be identi ed via the PSD of relaxed atomic structures. They found q ≈ .…”

Effects of loading conditions on free surface roughening of AISI 420 martensitic stainless steel

“…Other methods for studying surface roughness were reported in literature, as in Wouters et al (2005), for example, who studied the surface roughness of polycrystalline aluminum alloys during uniaxial tensile deformation and, under the assumption of self-affinity, analyzed surface roughening using height-height correlation functions. In another work (Solhjoo and Vakis, 2017), without the assumption of self-affinity for the roughness, the authors proposed a hybrid roughness parameter (connecting RMS roughness, RMS gradient and lateral correlation length) for evaluating surface roughness. Herein, the surface roughness is characterized in terms of different statistical parameters, including a , q , skewness and kurtosis, because they are sufficient for describing the degree of randomness of surface roughness in the current study.…”