Acoustic streaming induced elimination of nonspecifically bound proteins from a surface acoustic wave biosensor: Mechanism prediction using fluid-structure interaction models

Abstract

Biosensors typically operate in liquid media for detection of biomarkers and suffer from fouling resulting from nonspecific binding of protein molecules to the device surface. In the current work, using a coupled field finite element fluid-structure interaction simulation, we have identified that fluid motion induced by high intensity sound waves, such as those propagating in these sensors, can lead to the efficient removal of the nonspecifically bound proteins thereby eliminating sensor fouling. We present a computational analysis of the acoustic-streaming phenomenon induced biofouling elimination by surface acoustic-waves (SAWs) propagating on a lithium niobate piezoelectric crystal. The transient solutions generated from the developed coupled field fluid solid interaction model are utilized to predict trends in acoustic-streaming induced forces for varying design parameters such as voltage intensity, device frequency, fluid viscosity, and density. We utilize these model predictions to compute the various interaction forces involved and thereby identify the possible mechanisms for removal of nonspecifically-bound proteins. For the range of sensor operating conditions simulated, our study indicates that the SAW motion acts as a body force to overcome the adhesive forces of the fouling proteins to the device surface whereas the acoustic-streaming induced hydrodynamic forces prevent their reattachment. The streaming velocity fields computed using the finite element models in conjunction with the proposed particle removal mechanism were used to identify the optimum conditions that lead to improved removal efficiency. We show that it is possible to tune operational parameters such as device frequency and input voltage to achieve effective elimination of biofouling proteins in typical biosensing media. Our simulation results agree well with previously reported experimental observations. The findings of this work have significant implications in designing reusable, selective, and highly sensitive biosensors.