Stochastic Time Response and Ultimate Noise Performance of Adsorption-Based Microfluidic Biosensors

Area of Science:

• Biomedical Engineering
• Physical Chemistry
• Sensor Technology

Background:

• Microfluidic biosensors require advanced models for accurate interpretation of measurement results and optimal performance.
• The stochastic nature of adsorption-desorption and mass transfer (MT) processes necessitates a stochastic approach for sensor response analysis.

Purpose of the Study:

• To develop and present a stochastic model for microfluidic biosensor time response.
• To analyze the impact of coupled adsorption-desorption and MT processes on sensor kinetics and noise performance.

Main Methods:

• Development of a stochastic mathematical model incorporating coupled adsorption-desorption and MT processes.
• Analysis of sensor response kinetics, noise performance, and signal-to-noise ratio (SNR).

Main Results:

• Slow MT was shown to decelerate sensor response kinetics.
• Increased MT rates led to higher noise levels and reduced maximal achievable SNR.
• Degradation of sensor performance impacts minimal detectable/quantifiable analyte concentration.

Conclusions:

• The presented stochastic model is significant for interpreting measurement data and estimating sensor noise performance.
• The model aids in optimizing biosensors for lower detection/quantification limits.
• Investigating MT influence is crucial for nanoscale sensors to prevent false-negative results.