Experimental Analysis Of The Surface Roughness Evolution Of Etched Glass For Micro/Nanofluidic Devices

Roughness of channel surfaces, both deterministic and random, is known to affect the fluid flow behavior in micro/nanoscale fluidic devices. This has relevance particularly for applications involving non-Newtonian fluids, such as in biomedical lab-on-chip devices. While several studies have investigated effects of relative large, deterministic surface structures on fluid flow, the effect of random roughness on microfluidic flow remains relatively unexplored. In this study, the effects of processing conditions for wet etching of glass including etching time and etching orientation on centre-line average (Ra) and the autocorrelation length (ACL) were investigated. Statistical distribution of the roughness was also studied. Results indicated that ACL can be tailored in the range of 1-4 mu m by changing etching time in horizontal etching while Ra was found to increase weakly with etching time in all three etching orientations. Analysis of the experimental data using the Kolmogorov-Smirnov goodness-of-fit hypothesis test shows that the glass surface roughness does not follow a Gaussian distribution, as is typically assumed in the literature. Instead, the T location-scale distribution fits the roughness data with 1.11% error. These results provide promising insights into tailoring surface roughness for improving microfluidic devices.