Assessment of Direct Laser Writing using Nd YAG Lasers for Microfluidic Applications

Assessment of Direct Laser Writing using Nd YAG Lasers for Microfluidic Applications

Muneer Khan Mohammed (FARCAMT, Advanced Manufacturing Institute, King Saud University, Riyadh, Saudi Arabia), Abdulrahman Al-Ahmari (FARCAMT, Advanced Manufacturing Institute, King Saud University, Riyadh, Saudi Arabia & Industrial Engineering Department, King Saud University, Riyadh, Saudi Arabia) and Usama Umer (FARCAMT, Advanced Manufacturing Institute, King Saud University, Riyadh, Saudi Arabia)
DOI: 10.4018/ijmmme.2015040103

Abstract

The rapid growth in the use of Micro/Nano products in variety of industries such as Micro electromechanical systems (MEMS), microelectronics, Biomedical/Bio-MEMS, automotive (motion sensors), telecommunications etc, has demanded new micro manufacturing methods. The challenge with the manufacturing of Microfluidic devices/biochips is that they often make use of broad range of materials within a single chip, making it difficult to manufacture these devices with conventional photolithographic based techniques. Laser processing of materials has proved to be an important tool for the development of these devices because of the accuracy, flexibility and the most important one material independence it offers. This research focus on optimization of laser process parameters for the machining of Microfluidic channels with AISI 1045 steel. Design of experiments (DOE) technique was used in order to study the effect of laser process parameters on rectangular and semicircular cross-section channels.
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Introduction

Lasers in manufacturing industry are widely used in drilling, cutting, marking, milling and micromachining applications because of the various advantages it offers such as absence of mechanical forces and tool wear, ability to machine difficult to cut materials, precise operation and flexibility etc. Although laser processing of materials offers lot of advantages; it is a complex process involving large number of factors and the quality of machining depends on the proper selection of parameters.

Laser micromachining works on the principle that when a high energy density laser beam is focused on work surface the thermal energy is absorbed which heats and transforms the work volume into a molten, vaporized or chemically changed state that can easily be removed by flow of high pressure assist gas jet. Laser micromachining is a layer by layer material removal process and is affected by factors like laser pulse frequency, laser scan speed, layer thickness, track displacement and scan strategy.

A lot of research is being done in order to study the effect of process parameters during laser processing of materials by using various advance statistical tools. Ghoreishi et al. (Ghoreishi, Low, & Li, 2002) applied CCD and Response surface methodology to analyze the effect of laser process parameters on hole taper and circularity in laser drilling of stainless steel. Almeida et al. (Almeida et al., 2006) used the factorial design approach to determine the effects of laser process parameters on the surface roughness and dross formation on the Nd: YAG laser cutting of pure titanium and titanium alloy (Ti–6Al–4V). Mathew et al. (Mathew, Goswami, Ramakrishnan, & Naik, 1999) used central composite design for the process optimization of pulsed Nd:YAG laser cutting of fibre reinforced plastic composite sheet. Chen et al. (Chen, Tam, Chen, & Zheng, 1996) applied Taguchi methodology for optimization during micro-engraving of photo-masks. Campanelli et al. (Campanelli, Ludovico, Bonserio, Cavalluzzi, & Cinquepalmi, 2007) used Full Factorial Design to evaluate the influence of the laser process parameters on the success of the ablation process in terms of depth of removed material (DP) and surface roughness (SR). Pham et al. (Pham, Dimov, & Petkov, 2007) conducted single factor experiments for the laser milling of ceramics using a Nd: YAG laser with a wavelength of 1024nm. Yousef et al. (Yousef, Knopf, Bordatchev, & Nikumb, 2003) used artificial neural networks to model and analyze the material removal process.

Microfluidic systems have been a topic of extensive research in the recent times. Microfluidic devices are basically the miniaturized biological assays such as DNA sequencing and separation, polymerase chain reaction (PCR), enzymatic assays, immunoassays, cell counting and separation, cell culture etc, these devices are generally disposable and used only once to avoid sample contamination. Because the micro-fluidic chip can perform multiple tasks in a typical biochemical analysis laboratory, such as mixing, reaction, separation, and detection, etc., it is often called as LOC (lab-on-a-chip) or µTAS (micro total analysis system) (Reyes, Iossifidis, Auroux, & Manz, 2002; Song & Lee, 2006). A lot of research is being done in development of practical methods for mass production and rapid prototyping of these devices.

Silicon and glass based Microfluidic systems are generally fabricated by bulk micromachining, surface machining. Bulk micromachining include wet etching, dry etching, DRIE (deep reactive ion etching), SCREAM (single crystal reactive ion etching and metallization).

Recently polymer based Microfluidic systems have attracted attentions due to their lower fabrication costs. A number of mass production methods have been explored in the recent past such as hot embossing and micro injection molding. These methods require mold masters which will be used as a negative for the actual replication. Most common methods for the fabrication of mold masters are LIGA (lithography, galvanoforming and plastic molding) and soft-lithography techniques. LIGA produces high aspect ratio features but at higher cost (Abgrall & Gue, 2007). Laser machining because of the various advantages it offers such as high resolution and flexibility is also being used for the fabrication of mold masters via laser cutting of micro-channel features. Kam et al. (Kam & Mazumder, 2008) used laser machined silicon structure as a mold for making Microfluidic patterns on PDMS.

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