The nanomechanical deformations on a broad range of optical material surfaces (single crystals of Al2O3 [sapphire], SiC, Y3Al5O12 [YAG], CaF2, and LiB3O5 [LBO]; a SiO2-Al2O3-P2O5-Li2O glass-ceramics [Zerodur]; and glasses of SiO2:TiO2 [ULE], SiO2 [fused silica], and P2O5-Al2O3-K2O-BaO [Phosphate]) near the elastic-plastic load boundary have been measured by nanoindentation and nanoscratching to mimic the nanoplastic removal caused by a single slurry particle during polishing. Nanoindenation in air was performed to determine the workpiece hardness at various loads using a commercial nanoindenter with a Berkovich tip. Similarly, an atomic force microscope (AFM) with a stiff diamond coated tip (150nm radius) was used to produce nanoplastic scratches in air and aqueous environments over a range of applied loads (20-170N). The resulting nanoplastic deformation of the nanoscratches were used to calculate the removal function (i.e., depth per pass) which ranged from 0.18 to 3.6nm per pass for these materials. A linear correlation between the nanoplastic removal function and the polishing rate (using a fixed polishing process with colloidal silica slurry on a polyurethane pad) of these materials was observed implying that: (a) the polishing mechanism using colloidal silica slurry can be dominated by mechanical rather than chemical interactions; and (b) the nanoplastic removal function, as opposed to interface particle interactions, is the controlling factor for the polishing material removal rate. Furthermore, this correlation is consistent with the Ensemble Hertzian Multi-Gap (EHMG) microscopic material removal rate model described previously. The nanoplastic removal depth was also found to correlate to the measured nanoindentation hardness (H-1) of the optical material, scaling as H-1(-3.5). Two-dimensional (2D) finite element analysis simulations of nanoindentation showed a similar nonlinear dependence of plastic deformation with the workpiece material hardness. The findings of this study are used to determine an effective Preston coefficient for the material removal rate expression and enhance the predictive nature of the nanoplastic polishing rate for various materials utilizing their material properties.