Investigation of the optimal nanoscale chemical mechanical polishing depth for maximizing surface NiO removal efficiency without subsurface Ni global yielding via molecular dynamics simulations

In the chemical mechanical polishing of nickel, precisely controlling nanoscale polishing depth to maximize efficient surface NiO removal efficiency without subsurface Ni global yielding remains a critical challenge. To address this issue, this study establishes a quantitative yielding severity standard for subsurface Ni based on shear strain threshold and in combination with existing theoretical foundations. Nanoindentation and nanopolishing molecular dynamics simulations are conducted on Ni workpieces with NiO thickness ranging from 0 to 16.48 Å. The core objective is to determine the optimal nanoscale polishing depth for different NiO thicknesses, maximizing surface NiO removal efficiency without subsurface Ni global yielding. Nanoindentation simulations identify critical depths (h1, h2) for the subsurface Ni Incipient Plasticity Interval and reveal their linear relationship with NiO thickness. Gradient nanopolishing depth simulations demonstrate that polishing depth positively correlates with both surface NiO removal efficiency and subsurface Ni yielding severity. Optimal nanoscale polishing depths are determined for workpieces with varying NiO thicknesses, establishing a nonlinear predictive model for the optimal nanoscale polishing depth across the 0-16.48 Å range: dps(Δ)=0.00238Δ3-0.06312Δ2+1.12113Δ+2.05714. It is further revealed that the 6.12 Å NiO thickness represents a critical threshold: below this threshold, the optimal nanoscale polishing depth remains within the Incipient Plasticity Interval; conversely, beyond this threshold, the optimal nanoscale polishing depth falls below this interval due to increased tangential force contributions. The optimal nanoscale polishing depth prediction model established herein provides quantitative theoretical support and process guidance for nanoscale precision polishing of Ni within its scope of application, providing new insights into maximizing surface NiO removal efficiency without subsurface Ni global yielding.