Micro/nano scale surface roughness tailoring and its effect on microfluidic flow

The rapid growth of applications of lab-on-chip and bio-MEMES (Micro-electromechanical systems), arranging from cell culture and drug delivery to the microscale energy harvesting, microelectronics cooling, requires an understanding of microfluidic flow. Surface roughness, even at micro and nano scale, both deterministic and random, is considered an important parameter to affect fluid flow at the microscale. Over the past several decades, a variety of studies have been carried out on the impact of surface roughness on microfluidic flow behavior, including pressure drop, friction factor, heat transfer, laminar-turbulent transition, etc. However, most of the current studies focus on the large, deterministic roughness with patterned shapes formed by micromachining or microfabrication techniques. The effect of micro/nano scale random roughness on micro fluid flow remains relatively unexplored. As the size of microfluidic chip shrinks, the effect of realistic surface roughness on the microchannel walls cannot be simply ignored. In this work, the effect of realistic random surface roughness on fluid flow at the microscale was investigated through experiment and numerical simulation. Methods for roughness generation were explored. Chemical wet etching was used to vary the surface roughness on glass substrate. The evolution of roughness with etching parameters and the surface distribution was studied to provide a better understanding of random roughness characterization. In addition to this study, a hybrid surface tailoring process combining particle masking and reactive ion etching was developed to generate and control roughness on quartz substrate. A mathematical model was built to predict the roughness parameters, which was validated by the Atomic force microscopy (AFM) measurement. It was proved mathematically that the process is able to produce a random surface with controllable amplitude and spatial parameters.