Relationship between surface μ‐roughness and interface slurry particle spatial distribution during glass polishing
Abstract During optical glass polishing, a number of interactions between the workpiece (i.e., glass), polishing slurry, and pad can influence the resulting workpiece roughness at different spatial scale lengths. In our previous studies, the particle size distribution of the slurry, the pad topography, and the amount of material removed by a single particle on the workpiece were shown to strongly correlate with roughness at AFM scale lengths (nm‐μm) and weakly at μ‐roughness scale lengths (μm‐mm). In this study, the polishing slurry pH and the generation of glass removal products are shown to influence the slurry particle spatial and height distribution at the polishing interface and the resulting μ‐roughness of the glass workpiece. A series of fused silica and phosphate glass samples were polished with various ceria and colloidal silica slurries over a range of slurry pH , and the resulting AFM roughness and μ‐roughness were measured. The AFM roughness was largely invariant with pH , suggesting that the removal function of a single particle is unchanged with pH . However, the μ‐roughness changed significantly, increasing linearly with pH for phosphate glass and having a maximum at an intermediate pH for fused silica. In addition, the spatial and height distribution of slurry particles on the pad (as measured by laser confocal microscopy) was determined to be distinctly different at low and high pH during phosphate glass polishing. Also, the zeta potential as a function of pH was measured for the workpiece, slurry, and pad with and without surrogate glass products (K 3 PO 4 for phosphate glass and Si( OH ) 4 for silica) to assess the role of interfacial charge during polishing. The addition of K 3 PO 4 significantly raised the zeta potential, whereas addition of Si( OH ) 4 had little effect on the zeta potential. An electrostatic DLVO three‐body force model, using the measured zeta potentials, was used to calculate the particle–particle, particle–workpiece, and particle–pad attractive and repulsive forces as a function of pH and the incorporation of glass products at the interface. The model predicted an increase in particle–pad attraction with an increase in pH and phosphate glass products consistent with the measured slurry distribution on the pads during phosphate glass polishing. Finally, a slurry “island” distribution gap ( IDG ) model has been formulated which utilizes the measured interface slurry distributions and a load balance to determine the interface gap, the contact area fraction, and the load on each slurry “island”. The IDG model was then used to simulate the workpiece surface topography and μ‐roughness; the results show an increase in roughness with pH similar to that observed experimentally.