Pulse smearing and profile generation in CO2 laser micromachining on PMMA via raster scanning. (January 2018)

• Record Type: Journal Article
• Authors: Prakash, Shashi; Kumar, Subrata
• Is Part Of: Journal of manufacturing processes. Volume 31(2018)
• Page Start: 116
• Page End: 123
• Publication Date: 2018-01
• Subjects: Microchannels -- PMMA -- CO2 laser; Production management -- Data processing -- Periodicals; Manufacturing processes -- Periodicals; Procestechnologie; Productietechniek; Production -- Gestion -- Informatique -- Périodiques; Fabrication -- Périodiques; Manufacturing processes; Production management -- Data processing; Periodicals; 670.5
• DOI: 10.1016/j.jmapro.2017.11.003
• Languages: English
• ISSNs: 1526-6125

Abstract

Abstract: CO2 laser micromachining is an efficient and cost effective way for fabricating many polymeric microfluidic devices. Apart from direct laser writing also called vector cutting, raster scanning of CO2 laser beam is an indispensable part of fabrication process. Raster scanning is commonly used to create different types of microstructures on the surface. Polymethyl methacrylate (PMMA) is an important polymeric substrate for various microfluidic devices. In this research work, CO2 laser based raster scanning process has been explored for generation of microstructures of different widths and depths. The influence of high raster speeds on individual laser pulse shape has been discussed. Pulse smearing phenomenon was found to be detrimental to intensity of the laser beam. Reduction in energy intensity due to pulse smearing has been determined experimentally. Effects of process parameters on micromachined structure's output parameters have been detailed. An unique theoretical model has been developed for prediction of micromachined depth and profile on the basis of conservation of energy principal and superposition of Gaussian beams. The model takes into account the vertical pulse overlapping as well as pulse smearing effect. Evolution of surface in raster scanning has been discussed theoretically and experimentally. Developed model was found to be predicting the depth and evolved micro-structure profile close to actual depths and profile. The maximum prediction error for different power and scanning speed settings were less than 7.23%.