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A series of static and sliding indentation (ie, scratching) was performed and characterized on a wide range of optical workpiece materials [single crystals of Al2O3 (sapphire), SiC, Y3Al5O12 (YAG), CaF2, and LiB3O5 (LBO); a SiO2–Al2O3–P2O5–Li2O glass ceramic (Zerodur); and glasses of SiO2:TiO2 (ULE), SiO2 (fused silica), and P2O5–Al2O3–K2O–BaO (Phosphate)] at various applied loads using various indenters (Vickers, 10 µm conical, and 200 µm conical). Despite having different load dependencies, the lateral crack depth formed during sliding indentation quantitatively scales with that formed during static indentation, explaining why static indentation has been historically effective in describing various grinding parameters. Depending on the indenter geometry, the amount of residual trench damage (plastic deformation and local fracturing) during sliding indentation was often enhanced by more than an order of magnitude compared with static indentation. A simple ploughing scratch model, which considers both tangential and normal stresses (where the tangential stress is amplified by relatively small tangential contact area), explains this enhancement and other observed trends. Accounting for the high correlation between residual trench depth and volumetric fracturing, the model is extended to estimate the amount of fracture damage as a function of the material properties of the workpiece, indenter geometry, and applied load. Such a model has utility in the design of optimized grinding processes, particularly the abrasive geometry. Finally, at higher loads (>1 N), lateral cracks were often observed to preferentially propagate in the forward scratching direction, as opposed to perpendicular to the scratch as typically observed. High‐speed imaging of the scratch process confirms that these cracks propagate ahead of the sliding indenter during the scratching event. Finite element stress analysis suggests the ploughing frictional forces increase the mode I tensile stresses at the leading edge of the sliding indenter explaining the direction of crack propagation of such cracks. [ABSTRACT FROM AUTHOR]

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 (150 nm radius) was used to produce nanoplastic scratches in air and aqueous environments over a range of applied loads (~20‐170 μN). 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 3.6 nm 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 (H1) of the optical material, scaling as H1−3.5. 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. [ABSTRACT FROM AUTHOR]

A partial charge‐based chemical polishing model has been developed, which can serve as metric for describing the relative polishing material removal rate for different combinations of slurries and workpieces. A series of controlled polishing experiments utilizing a variety of colloidal polishing slurries (SiO2, CeO2, ZrO2, MgO, Sb2O5) and optical materials [single crystals of Al2O3 (sapphire), SiC, Y3Al5O12 (YAG), CaF2, and LiB3O5 (LBO); a SiO2‐Al2O3‐P2O5‐Li2O glass ceramic (Zerodur); and glasses of SiO2:TiO2 (ULE), SiO2 (fused silica), and P2O5‐Al2O3‐K2O‐BaO (Phosphate)] was performed and its material removal rate was measured. As previously proposed by Cook (J Non‐Cryst Solids. 1990;120:152), for many polishing systems, the removal rate is governed by a series of chemical reactions which include the formation of a surface hydroxide, followed by condensation of that hydroxyl moiety with the polishing particle, and a subsequent hydrolysis reaction. The rate of condensation can often be the rate limiting step, thus it can determine the polishing material removal rate. By largely keeping the numerous other factors that influence material removal rate fixed (such as due to particle size distributions, interface interactions, pad topography, kinematics, and applied pressure), the material removal rate is shown to scale exponentially with the partial charge difference (δwp‐s) between the workpiece and polishing slurry particle for many of the slurry‐workpiece combinations indicating that condensation rate is the rate limiting step. The partial charge (δ) describes the equilibrium distribution of electron density between chemically bonded atoms and is related to the electronegativity of the atoms chemically bonded to one another. This partial charge model also explains the age‐old experimental finding of why cerium oxide is the most effective polishing slurry for chemical removal of many workpieces. Some of the slurry‐workpiece combinations that did not follow the partial charge dependence offer insight to other removal mechanisms or rate limiting reaction pathways. [ABSTRACT FROM AUTHOR]

Various ceria and colloidal silica polishing slurries were used to polish fused silica glass workpieces on a polyurethane pad. Characterization of the slurries' particle size distribution ( PSD) (using both ensemble light scattering and single particle counting techniques) and of the polished workpiece surface (using atomic force microscopy) was performed. The results show the final workpiece surface roughness is quantitatively correlated with the logarithmic slope of the distribution function for the largest particles at the exponential tail end of the PSD. Using the measured PSD, fraction of pad area making contact, and mechanical properties of the workpiece, slurry, and pad as input parameters, an Ensemble Hertzian Gap ( EHG) polishing model was formulated to estimate each particle's penetration, load, and contact zone. The model is based on multiple Hertzian contact of slurry particles at the workpiece-pad interface in which the effective interface gap is determined through an elastic load balance. Separately, ceria particle static contact and single pass sliding experiments were performed showing ~1-nm depth removal per pass (i.e., a plastic type removal). Also, nanoindentation measurements on fused silica were made to estimate the critical load at which plastic type removal starts to occur ( Pcrit~5 × 10−5 N). Next the EHG model was extended to create simulated polished surfaces using the Monte Carlo method where each particle (with the calculated characteristics described above) slides and removes material from the silica surface in random directions. The polishing simulation utilized a constant depth removal mechanism (i.e., not scaling with particle size) of the elastic deformation zone cross section between the particle and silica surface, which was either 0.04 nm (for chemical removal) at low loads (< Pcrit) or 1.0 nm (for plastic removal) at intermediate loads (> Pcrit). The simulated surfaces quantitatively compare well with the measured rms roughness, power spectra, surface texture, absolute thickness material removal rate, and load dependence of removal rate. [ABSTRACT FROM AUTHOR]