Analysis and Prediction of Surface Topography Evolution in Laser Recovery of Monocrystalline Silicon

Surface defects generated during the machining of monocrystalline silicon optical components weakened the performance of optical systems. Recovery of the damage introduced by mechanical machining to optical components was a crucial approach to enhancing the overall performance of optical systems. In this study, a pulsed laser was employed to recover monocrystalline silicon mirrors post single-point diamond ultra-precision cutting. The surface topography evolution of monocrystalline silicon with varying laser fluence was investigated using white-light interferometry, and a predictive model for laser-recovered surface topography was established. The findings indicated that the recovery process could be divided into six regimes according to the evolution of surface topographical characteristics with varying laser fluence: bulge, coalescence, smoothness, groove, ripple, and ablation. When the laser fluence ranged between 16 and 23 J/cm², surface cutting textures were effectively eliminated, reducing surface roughness from 6 nm to 0.7 nm. The predictive model accurately calculated the post-laserrecovered surface topography, exhibiting a Root Mean Square Error of less than 1 nm in alignment with experimental results. Thermal stress, melting, and vaporization were the primary driving forces influencing surface shaping. By employing the predictive model to effectively coordinate these factors and optimize laser parameters, the recovery of monocrystalline silicon from machining damage was achieved.

Keywords: Laser recovery, Monocrystalline silicon, Surface roughness, Surface topography, Prediction model.

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