Elucidating the Onset of Plasticity in Sliding Contacts Using Differential Computational Orientation Tomography

Abstract

Depending on the mechanical and thermal energy introduced to a dry sliding interface, the near-surface regions of the mated bodies may undergo plastic deformation. In this work, we use large-scale molecular dynamics simulations to generate “differential computational orientation tomographs” (dCOT) and thus highlight changes to the microstructure near tribological FCC alloy surfaces, allowing us to detect subtle differences in lattice orientation and small distances in grain boundary migration. The analysis approach compares computationally generated orientation tomographs with their undeformed counterparts via a simple image analysis filter. We use our visualization method to discuss the acting microstructural mechanisms in a load- and time-resolved fashion, focusing on sliding conditions that lead to twinning, partial lattice rotation, and grain boundary-dominated processes. Extracting and laterally averaging the color saturation value of the generated tomographs allows us to produce quantitative time- and depth-resolved maps that give a good overview of the progress and severity of near-surface deformation. Corresponding maps of the lateral standard deviation in the color saturation show evidence of homogenization processes occurring in the tribologically loaded microstructure, frequently leading to the formation of a well-defined separation between deformed and undeformed regions. When integrated into a computational materials engineering framework, our approach could help optimize material design for tribological and other deformation problems. Graphic Abstract .

A review of advances in tribology in 2020–2021

“…The results showed that the friction force is related to the dislocation slip direction, and the effect of grain boundaries and grain size on tribological behaviors were revealed: the grain boundary structure showed a strengthening effect, which hindered propagation of stacking fault; as the grain size decreased, the material softened, resulting in a decrease in friction coefficient and increase of wear depth. Furthermore, in order to better capture [931] innovatively proposed the "differential computed orientation tomography" (dCOT) method, based on large-scale MD simulations (Fig. 77(a)).…”

“…Fig 77. Mechanism of friction and wear at atomistic scale[931,934,935,937]. Reproduced with permission from Ref [931],.…”

“…Mechanism of friction and wear at atomistic scale[931,934,935,937]. Reproduced with permission from Ref [931],. © The author(s), 2021; Reproduced with permission from Ref [934],.…”

Does speed kill or make friction better? — Designing materials for high velocity sliding

“…The computational tomographs of the polycrystalline CuNi sample shown and discussed throughout this work are colored according to grain orientations as in electron backscatter diffraction (EBSD), using the inverse pole figure (IPF) coloring standard (see Ref. [51] for an in-depth discussion). Orientations were calculated using polyhedral template matching [52] as implemented in OVITO [53], and the EBSD-IPF style colors were produced using the MTEX toolbox [54,55] for Matlab.…”