Microfluidic Adsorption-Based Biosensors: Mathematical Models of Time Response and Noise, Considering Mass Transfer and Surface Heterogeneity

Abstract

Adsorption-based microfluidic sensors are promising tools for biosensing. Advanced mathematical models of time response and noise of such devices are needed in order to improve the interpretation of measurement results, and to achieve the optimal sensor performance. Here the mathematical models are presented that take into account the coupling of processes that generate the sensor signal: adsorption–desorption (AD) of the target analyte particles on the heterogeneous sensing surface, and mass transfer (MT) in a microfluidic chamber. The response kinetics and AD noise (which determines the ultimate sensing performance) of protein biosensors are analyzed, assuming practically relevant analyte concentrations, sensing surface areas and MT parameters. The condition is determined under which MT significantly influences the sensor characteristics relevant for reliable analyte detection and quantification. It is shown that the development of improved mathematical models of sensor temporal response and noise can be used as one of strategies for achieving better sensing performance.

Biosensor Time Response and Noise Models That Take into Account Spatial Rearrangement of Adsorbed Biomolecules

“…In addition to producing the response of the sensor, this process, stochastic in nature, is also a source of noise that affects the performance of micro/nanosensors. There are several sensor response and noise models that take into account different additional processes coupled with adsorption, depending on a specific practical case [4][5][6][7]. The spatial rearrangement of adsorbed biomolecules is an additional process that changes the binding/unbinding kinetics to a two-step process behavior and, therefore, affects both the sensor's time response and its fluctuations.…”