Examination of Selective Pulsed Laser Micropolishing on Microfabricated Nickel Samples Using Spatial Frequency Analysis

Abstract

The precision of parts created by microfabrication processes is limited by surface roughness. Therefore, as a means of improving surface roughness, pulsed laser micropolishing on nickel was examined numerically and experimentally. A one-dimensional finite element method model was used to estimate the melt depth and duration for single 50–300 ns laser pulses. The critical frequency was introduced to predict the effectiveness of polishing in the spatial frequency domain. A 1064 nm Nd:YAG laser with 300 ns pulses was used to experimentally investigate pulsed laser polishing on microfabricated nickel samples with microscale line features. A microfabricated sample with 2.5 μm wide and 0.2 μm high lines spaced 5 μm apart and one with 5 μm wide and 0.38 μm high lines spaced 10 μm apart were polished with 300 ns long pulses of 47.2 J/cm2 and 44.1 J/cm2 fluences, respectively. The critical frequency for these experimental conditions was predicted and compared with the reduction in the average surface roughness measured for samples with two different spatial frequency contents. The average surface roughness of 5 μm and 10 μm wavelength line features were reduced from 0.112 μm to 0.015 μm and from 0.112 μm to 0.059 μm, respectively. Four regimes of pulsed laser micropolishing are identified as a function of laser fluence for a given pulse width: (1) at low fluences no polishing occurs due to insufficient melting, (2) moderate fluences allow sufficient melt time for surface wave damping and significant smoothing occurs, (3) increasing fluence reduces smoothing, and (4) high fluences cause roughening due to large recoil pressure and ablation. Significant improvements in average surface roughness can be achieved by pulsed laser micropolishing if the dominant frequency content of the original surface features is above the critical spatial frequency for polishing.

Pulsed laser micro polishing: Surface prediction model

“…Perry et al [1][2][3] have shown that knowledge of the maximum melt duration, t m-max , can be used to determine the minimum critical frequency, f cr , above which there should be a significant reduction in amplitude of the spatial frequency content of a surface and its asperities. The critical frequency is…”

“…Perry et al [1][2][3] have demonstrated that pulsed laser micro-polishing (PLμP) with pulse durations of 300-650 ns and a spot size of 60 µm is a method by which the surface roughness of microfabricated and micro milled parts can be effectively reduced. Improved surface finish and smoothness can be achieved on select areas of different metallic surfaces, produced by meso/micro-manufacturing processes, which is difficult via other methods (like mechanical polishing, electropolishing and chemical mechanical polishing) as the feature sizes are approaching the same magnitude as the surface roughness [4][5][6][7][8].…”

“…These models are based on spatial Fourier analysis of the surfaces and examination of Navier-Stokes equation for each Fourier component. In the present work, we extend these analytical models and numerical models of Perry et al [1][2][3] to two dimensions and use the same to predict the surface finish, given the initial surface conditions. Perry et al [1][2][3] have proposed a critical frequency, f cr , which describes the cutoff point in the spatial frequency content of the surface, above which a significant reduction in the amplitude is expected.…”

“…Perry et al [1][2][3] have modeled PLµP as oscillations of capillary waves with damping resulting from the forces of surface tension and viscosity and a one-dimensional spatial frequency domain analysis was proposed. They have also proposed a critical spatial frequency, f cr , above which a significant reduction in the amplitude of the spatial Fourier components is expected.…”

Modelling of process parameters in laser polishing of steel components using ensembles of regression trees

“…Figure 2 is a schematic representation of the fundamental parts of the process, where a defocused beam is used to melt surface asperities in order to reach smoother topography. Once the material is melted, the attenuation of the asperities is given by several mechanisms such as capillary and gravitational forces, and recoil pressure [Perry, 2009] The process result depends mainly on three factors: the surface material, its initial topography and the energy density of the laser beam. The combination of these factors fixes the amount of melted material.…”