Click on “Download PDF” for the PDF version or on the title for the HTML version.
If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.
Design and Analysis of a Flow Injection Based Biosensor by Computational Fluid Dynamics
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.orgCitation: Paper number 037003, 2003 ASAE Annual Meeting . (doi: 10.13031/2013.15341)
Authors: Jeroen Lammertyn, Pieter Verboven, Els Veraverbeke, Bart Nicolaï, Joseph Irudayaraj
Keywords: Biosensor, computational fluid dynamics, electrochemistry, glucose, modeling
This paper discusses the development of a convection-diffusion-reaction model to simulate the behavior of a flow injection analysis biosensor with respect to its design parameters such as flow rate, tubing dimensions, detector geometry and substrate and enzyme concentrations. The problem is described by the steady state incompressible Navier-Stokes equations for fluid flow, and transient convection-diffusion-reaction equations for the different dissolved species. The enzyme-substrate interaction was described by Michaelis-Menten kinetics. The substrate, enzyme and product concentration profiles in the tubing and the detector were calculated as a function of time. It was observed that due to the laminar flow pattern in the tubing the interface between the enzyme and substrate was much larger than expected for a plug flow scenario. Concentration profiles of substrate, enzyme and product illustrated that not all substrate was converted into product when the flow reached the inlet of the detector, given the specified set of design parameters. The model was successfully validated by comparing a measured and a simulated hydrogen peroxide concentration versus time profile. Both peaks matched well, however, a slightly longer tailing than expected from the model was observed in the measurements. This extra tailing could be attributed to some simplifications in the geometrical model of the detector. The simulated and measured calibration curves for glucose closely matched in the range between 0 and 2.5mM. For higher glucose concentrations the measured calibration was non-linear.(Download PDF) (Export to EndNotes)