Smart ceramic materials are next generation materials with the inherent intelligence to adapt to change in the external environment. These materials are destined to play an essential role in several critical engineering applications. Machining these materials using traditional machining processes is a challenge. The laser beam micromachining (LBMM) process has the potential to machine such smart materials. However, laser machining when performed in air induces high thermal stress on the surface, often leading to crack formation, recast and re-deposition of ablated material, and large heat-affected zones (HAZ). Performing laser beam machining in the presence of a liquid medium could potentially resolve these issues. This research investigates the possibility of using a Liquid Assisted-Laser Beam Micromachining (LA-LBMM) process for micromachining smart ceramic materials. Experimental studies are performed to compare the machining quality of laser beam machining process in air and in a liquid medium. The study reveals that the presence of liquid medium helps in controlling the heat-affected zone and the taper angle of the cavity drilled, thereby enhancing the machining quality. Analytical modeling is developed for the prediction of HAZ and cavity diameter both in air and underwater conditions, and the model is capable of predicting the experimental results to within 10% error.
Under the application of magnetic field, magnetic fluids exhibits magnetoviscous effect. We have observed large magneto viscous effects by dispersing magnetic and non-magnetic anisotropic micron size magnetic particles in a ferrofluid , the mixture is known as ferrodispersion. For both the samples density and volume concentrations of large particles are kept identical i.e. 25, 50 and 75 vol %. It is observed that for 25% and 50% vol. concentration the magnetoviscous effect for both the samples is comparable, however for 75% concentration the field dependent viscosity of non-magnetic bentonite anisotropic particles are much larger than its counterpart. This shows even non magnetic particle can also enhance the magneto viscous effect. Results can be useful to develop a novel kind of bidispersed magnetorheological fluids to increase its commercial applicability.
Liquid Assisted Laser Beam Micromachining (LA-LBMM) process is advanced machining process which can overcome the limitations of traditional laser beam machining processes. LA-LBMM process uses a layer of a liquid medium such as water above the substrate surface during the application of laser beam. During LA-LBMM process, the liquid medium is used both in static mode in which the water is still or in a dynamic mode in which the water flows over the substrate with a specific velocity. Experimental studies on LA-LBMM process have shown that the cavity machined has a better surface finish due to a reduction in the amount of re-deposition and recast material. While LA-LBMM process promises significant improvement in laser-based micromachining applications, the process mechanisms involved in LA-LBMM process is not well understood. In the past, finite element simulation studies on LA-LBMM process is studied which could only find the temperature distribution on the substrate during machining. A clear understanding of the role of water medium during the LA-LBMM process is lacking. This research involves the use of Molecular Dynamics (MD) simulation technique to investigate the complex and dynamic mechanisms involved in the LA-LBMM process both in static and dynamic mode. The results of the MD simulation are compared with those of Laser Beam Micromachining (LBMM). The study revealed that machining during LA-LBMM process showed higher removal compared with LBMM process. The LA-LBMM process in dynamic mode showed lesser material removal compared with static mode as the flowing water carrying the heat away from the machining zone. Formation of nanoscale bubbles along with shockwave propagation is observed during the simulation of LA-LBMM process. The findings of this study provide further insights to strengthen the knowledge base of LA-LBMM process.
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