Uncertainty Quantification in Models of Microfluid Systems

Abstract

Uncertainty quantification (UQ) in models of physical systems is a necessary tool for both model validation and engineering design optimization. We have applied UQ tools using stochastic spectral polynomial chaos techniques to the modeling of fluid flow in an electrokinetically driven microchannel, allowing for detailed buffer electrochemistry and finite rate analyte reactions. The model includes full coupling of wall electric double layer potential with variations in PH and local electric field. Allowing for uncertainties in species mobilities, buffer equilibrium constants, and wall properties, we have computed the resulting uncertainty in predicted model outputs, illustrating the impact of growth of uncertainty on confidence in model predictions. We present details of the computational UQ techniques with specific focus on their application in the electrochemical micro fluidic context. We also present UQ results pertaining to model protein labeling in an electokinetically-pumped microchannel flow.