The objective of this work was to improve our understanding of pulsed laser micropolishing (PLμP) by studying the effects of laser pulse length and feed rate (pulses per millimeter) on surface roughness. PLμP experiments were conducted with a multimode neodymium-doped yttrium aluminum garnet (Nd:YAG) laser (1064 nm wavelength) that was focused down to approximately 50 μm diameter and scanned over the stationary workpiece surface. Simulation results presented here and previous work suggest that longer laser pulses result in smoother surfaces. Results on microfabricated nickel samples using laser pulse durations of 300 ns and 650 ns test this hypothesis. Polishing with 300 ns and 650 ns pulse durations results in an average surface roughness of 66 nm and 47 nm, respectively; reductions of 30% and 50% compared with the original surface. Furthermore, PLμP is shown to introduce a minor artifact on the sample surface whose spatial frequency (1/mm) is directly related to the laser feed rate (pulses/mm).
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.
The relative surface accuracy (surface roughness/feature size) of meso/micro parts fabricated by emerging meso/micro manufacturing processes is generally worse than that of macro parts fabricated by conventional processes. Meso/micro parts have unique tribology issues and surface roughness strongly impacts their performance, hence there is a demand for effective polishing of their complex shapes. A laser micro polishing method based on rapid surface micromelting is described. To develop a fundamental understanding of the underlying processes, a nickel sample was fabricated using silicon-based microfabrication and electroplating techniques. Results demonstrating the effectiveness of laser polishing using a pulsed 1064 nm Nd:YAG laser are presented. These results show that brief (200–300 ns) laser pulses can significantly improve the sample surface roughness (Ra). Additionally, by examining surface profile data in the spatial frequency domain it is clear that using pulses (up to 300 ns), laser polishing can effectively remove surface roughness features greater than 200 mm−1 in spatial frequency.
This paper presents a novel approach for obtaining thermal data from the close vicinity (70–700 μm) of the tool-workpiece interface while machining hardened steel. Arrays of microthin film C-type thermocouples with a junction size of 5 μm × 5 μm were fabricated by standard microfabrication methods and have been successfully embedded into polycrystalline cubic boron nitride (PCBN) using a diffusion bonding technique. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) were performed to examine material interactions at the bonding interface in order to determine optimal bonding parameters. Static and dynamic sensor performances have been characterized. The sensors exhibit excellent linearity up to 1300 °C, fast rise time of 150 ns, and sensitivity of ∼19 μV/ °C. The PCBN inserts instrumented with embedded thin film C-type thermocouples were successfully applied to measure internal tool temperatures as close as 70 μm to the cutting edge while machining hardened steel workpieces at industrially relevant cutting conditions. Correlations between temperature and cutting parameters have been established. The embedded microthin film sensor array provided unprecedented temporal and spatial resolution as well as high accuracy for microscale transient tool-internal temperature field measurements. Tool-internal temperature maps were generated from acquired data. In the frequency domain, obtained thermal data indicated the onset of regenerative machining chatter earlier and more effective than conventional force measurement by dynamometer.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.