A Fourier Transform-Induced Data Process for Label-Free Selective Nanopore Analysis under Sinusoidal Voltage...

Area of Science:

• Biophysics
• Nanotechnology
• Analytical Chemistry

Background:

• Resistive-pulse nanopore analysis offers single-molecule detection but lacks selectivity.
• Current methods often rely on analyte labeling, adding complexity.
• Improving selectivity is crucial for diverse nanopore sensing applications.

Purpose of the Study:

• To develop a label-free data processing method for enhanced nanopore analysis selectivity.
• To convert resistive current signals into more specific frequency domain phase angle features.
• To demonstrate the utility of phase angle analysis for distinguishing various nanoparticles and biological entities.

Main Methods:

• Utilized sinusoidal voltage excitation and Fourier transform for signal processing.
• Investigated the role of transmural capacitance during nanoparticle translocation.
• Developed a novel data analysis technique for label-free nanopore sensing.

Main Results:

• Successfully converted resistive current signals to distinct phase angle features.
• Demonstrated that transmural capacitance significantly enhances phase angle specificity.
• Achieved direct differentiation of SiO2, Ag, and Au nanoparticles and HeLa/LoVo cells via unique phase angles.
• Distinguished a mixture of nanoparticles with high accuracy.

Conclusions:

• The developed label-free method significantly improves nanopore analysis selectivity.
• Phase angle analysis provides a powerful, label-free approach for single-molecule characterization.
• This technique shows promise for complex biological and material mixture analysis.